It was a good choice. That's true. Thank you. Well, you saw him. He was great. Very good. Me. Yes. Always. Every new year at our jobs. Yeah. Everything's going well. Thank you. That's good to know. We're relegated to that. So we'll see. So we'll see. Yeah. Yeah. He's right. It's always something. Right. What are you talking about? More business. More business. Yeah. And people may have stuck with the consistency statement. Yeah. I've got to remember that he's a toddler. You know. Is it tough? I could swim. I only saw three things. This is coming up next month. Oh, he's got you. Hey, good to see you all. Hey. Well, how are you? Welcome to this here. This way here. Same seat. Easy. You think? Good afternoon. Welcome to the Durham Planning Commission. The members of the Durham Planning Commission have been appointed by the city and the county as an advisory board to the elected officials. You should know that the elected officials have the final say on any of the issues that are here before us this evening. If you wish to speak on any of the agenda items this evening, I encourage you to please sign up to my left on the table. You'll note that there are specifics on each of the items that will be in front of you and when we get to that case, we'll be invited to come speak in the microphone. When you do come and speak, we ask you to speak clearly into the microphone for your name and your mailing address as part of your testimony. Each side, those speaking in favor and those speaking opposed, will have 10 minutes to present for each side and the time will be divided among all the people wishing to speak. Finally, all the motions this evening will be stated in the affirmative so if a motion fails or ties, the recommendation is for denial. Thank you. May we have the roll call please? Commissioner Alturk. Commissioner Johnson. Commissioner Gauch. Commissioner Gauch has requested an excused absence. Commissioner Bryan. Commissioner Bryan has also requested an excused absence. Commissioner Satterfield. You can't let them all go. Commissioner Harris. I did not request. Here. Commissioner Hyman. Chair Busby. Commissioner Miller. President. Commissioner Kenshin. Commissioner Hornbuckle. Commissioner Mann. Commissioner Gibbs. Great, thank you very much. If we could have a motion to approve the three excused absences, that would be appreciated. Second. Moved by Commissioner Miller, seconded by Commissioner Harris. All those in favor, please say aye. Aye. Any opposed? The motion passes. We will next move to the approval of the minutes and the consistency statements from our December 12, 2017 meeting. And I will note that the staff has provided us the updated minutes. There was one motion that we have corrected in the minutes in front of you. Yes, Chair Busby. Grace Smith with the Planning Department. Actually on page four of seven, it was a consistency statement for Lumley Road had to be corrected. We had a couple of words that were left out that should have been in there. So we've done that. That's in the minutes you have before you. Thank you very much. Mr. Chair, I move that we approve the minutes, the updated minutes and the consistency statement. Second. Moved by Commissioner Harris, seconded by Commissioner Hornbuckle. All those in favor, please say aye. Aye. Any opposed? Great, the motion passes. We'll move to adjustments to the agenda. Any adjustments, Ms. Smith? Staff has no adjustments or recommends no adjustments. And we can affirm that all legal notice requirements have been met and are on file in the Planning Department affidavits for such or on file. Great, thank you very much. Oh, accept the motion to approve the agenda. So moved. Second. Moved by Commissioner Harris, seconded by Commissioner Alturk. All those in favor, please say aye. Aye. Any opposed? Great, the motion passes. We will move to our first public hearing this evening. This is Case A1700012 and a concurrent zoning case Z1700031. This is for 3404 Page Road. And we will start with the staff report. Good evening, Jamie Sanyak with the Planning Department. I will be presenting case number A1700012 Z1700031. This is 3404 Page Road. The applicant is Robert Schunk from Stewart. The property is located within the city's jurisdiction pending annexation. The site acreage is 32.827. The proposal is to rezone the site to allow for 190 townhouse units. The rezoning is from rural residential to plan development residential 5.788. And the flam request is industrial flam to low medium density residential 4 to 8 dwell units per acre. The site is located within the suburban tier and within the Neuse River Basin. Residential is the predominant uses surrounding the area. The Beth Page residential subdivision is located to the south and to the west to the north is the rural residential zone. One of which of the properties includes a cemetery which fronts on Page Road. That property has not been included as part of the rezoning and plan amendment request. But is included as part of the annexation case. To the east is warehouse and commercial uses located within the Wake County jurisdiction. The subject site is just north of the Pulitzer Lane intersection with Page Road. This is the existing conditions map. There are a number of existing structures and driveways which are proposed to be removed in the event that the request is approved. There are isolated wetlands found within the property in existing pond to be drained. A stream of the Neuse River extends into the property from the adjacent lot to the west. And north of the stream buffer is an immature pine forest as well as other areas of cleared understory trees. And south of the stream is mixed hardwood pine forest. This is the existing and proposed Flaum map. The property is highlighted in red. As you can see on the left, the property is currently designated an industrial Flaum. And the applicant is proposing to change the designation to low, medium density residential which would be consistent with the rezoning request. The context map shown here also has the property shown highlighted in red. The existing zoning is rural residential. And the applicant is proposing to change the zoning to plan development residential 5.788. This request has been reviewed by staff and determined to be consistent with the requirements of the unified development code. In terms of the requested district, again the site is, sorry, that's a typo. The site is 32.827 acres. The density is 5.788 dwelling units per acre. Maximum pervious coverage is 60%. Tree coverage 20%. Maximum height is 35 feet. And the open space requirement is 16%. The development plan, and I should say that the property meets the PDR district requirements in terms of density, maximum pervious coverage, tree coverage, building height, and open space requirements. The proposed development plan, which is shown here, shows the access points, the building and parking envelope, the tree preservation areas, the riparian buffers, and the project boundary buffers. In terms of summary of commitments, the dwelling units will be townhomes. There will be a 20 foot planted buffer located along the southern and western property lines. A bicycle lane and sidewalk will be provided along Page Road. There are other associated roadway improvements, design and graphic commitments. In terms of consistency with the comprehensive plan policies, it is currently, the site is currently industrial-flommed and not consistent with the low density residential. We have found that in terms of zoning map changes, it is consistent with policies 2.1 3D, 2.2 2B. It is contiguous with other residential developments incompatible with the surrounding uses. There is sufficient infrastructure in place to support the development. The proposed development is consistent with 8.1 4D, since they are committing to additional asphalt to account for the future bicycle lane. And there is sufficient infrastructure to support the site in terms of the school children generated from the development. That determines that this request is consistent with the comprehensive plan and applicable policies and ordinances. And I will be happy to answer any questions that you have. Thank you. We will now move to open the public hearing. And at the moment we have one individual signed up to speak, Robert Schunk. And if anyone else would like to speak, you can let us know. Good evening commissioners, commissioner Busby, fellow commissioners, my name is Robert Schunk. I live at 2627 University Drive here in Durham. I'm here representing Shanandoah Homes this evening. Thanks to Jamie for a good opening presentation. I pulled the zoning atlas to give a larger context to our project in relationship to the area. As you can see to the project, our project is identified there and the Bethpage community is to the south and west, to the north, or some smaller parts also, but the Bethpage community. This gives a little more zoomed-in layout as well. I'm going to move to the next slide. He is a little more zoomed-in layout as well. A view of both community side-by-side. We will be connecting, as Jamie said, to the community right here to the south. This community also has feature connections north and south up here for whenever that gets developed as well as to, you know, the north and west as well. This is an enlargement of our development plan. And I'll speak to this a little bit more about what we have. As Jamie said, we were requesting the land use plan change from industrial to low-medium density residential, as Bethpage did. Meetings that had occurred with planning staff that stated that this was not as desirable industrial land so that the request was suitable. We are requesting a 5.78 units per acre for up to 190 townhomes. Just to give some further context, Greek side at Bethpage is owned at PDR 4.77. And when you do the math to the 283 acres, it's roughly 13, a little over 1,300 acres. Or 1,300 units, excuse me. We're 33 acres. Their community is about 283. And when they did the math, we're about 11%, adding about 11% more area to that project.  We did have a neighborhood meeting back in August. We had about 50 residents. Neighbors attend that meeting. Some of them are here this evening. There were several issues discussed. Connectivity noted here at the bottom, providing a buffer, price of townhomes, or keeping the pond, removing the pond. But the main focus of the evening boiled down to a buffer between our community and their community. You know, while there's no community, there's, in looking at the site plan of Bethpage, there's no buffers provided within that community. You know, we did, by the end of the evening, we did proffer to give a providing 20 foot project boundary buffer along the southern and western edge, as depicted here in the development plan. As you might know, when a PDR is adjacent to a PDR, buffers are not required by the ordinance. When they develop to their plan, PDR is next to rural residential require a 10 foot buffer. So the aggregated buffer here will be a 30 foot project boundary buffer between their 10 foot and our 20. We will, while Bethpage consists of single family homes and some townhomes, this is our development, will consist of all of townhomes. Actually, I wanted to back up one point I skipped over. When you look at the, our proposed density and the unit count and the acreages of the size, and when you look at the projects together, while we're 5.8 units an acre, and Bethpage is about 4.8 acres, when you combine that together, gets you maybe to about 4.8, 4.9 units per acre, where it balances that out. All road improvements are being provided along the front edge, and basically we're extending the three lane widening section in front of Bethpage further north. We are providing a sidewalk. There's a cemetery in the northeast corner, and a lot of the headstones are almost within about 10 feet of the edge of pavement. We're required to dedicate 25 feet of driveway, so there's no room to put the sidewalk in front of the cemetery, so we'll be moving that around to the rear with a public easement to allow north and south, north-south traffic. We are, we did speak to planning today, and we're looking to add a proffer that a couple of proffers, or one proffer and a revision to one of the design commitments. The text here before you is that the developer commits to a minimum offset of 16 inches with two offsets per every building, four units to avoid repetitious placement. And the other request is the other thing we're providing is that we're going to remove the use of vinyl siding, driving through Bethpage. It's all hardy plank material, so removing the vinyl to speak more of a consistent material with their neighborhood. That completes my presentation. Thank you. Thank you very much. Is there anyone else who did not get a chance to sign up who would like to speak on this particular case? Seeing none, we will move to close the public comment period, and I will ask any commissioners if they would like to speak or ask any questions. There are two lonely commissioners down on the end. We'll start with Commissioner Alturk. Thank you, Chair. Thanks, Robert, for that presentation. I had a couple of minor questions. So I assume you're, or are you going to build any townhomes north of the stream? Yes. You are. Okay. And so there'll be a way to connect those to the ones to the south. That is correct. Okay. And so, and then you have three site access points. And I guess not knowing where the townhomes will be, I mean, do you anticipate which will be the main entrance or will you try to push for that to be on, you know, from Page Road or just so that I assume that's a concern maybe for some of the residents of Beth Page. The main entrance will certainly be from Page Road. Okay. There'll be entry monumentation there. And to announce the neighborhood and by ordinance were required to connect to anthology. And then we're connected to the north. Per the ordinance as well. So if and when the development to the north is developed, there's a connection there. We could not connect to the west because there's not a connection already provided there. Right. Okay. All right. Thank you. Commissioner Johnson. Thank you, Chair. Just another quick question in regards to the, to the proffered buffer. So what exactly would that look like in regards to all those shrubberies or is it just the setback essentially? What would that look like? So it'll be a 20% or it'll be a 20 foot 0.4 opaque buffer. Some of it will be preserved and some of it will be planted. If anybody of you have driven through the neighborhood, the Beth Page neighborhood, it doesn't have the most kind Topo, nor does this site. So where we are able to preserve vegetation, we certainly will cost the developer less money.  Is there a height range or something for this buffer? The height range will meet what the UDU calls for. So the mix of overstory trees, evergreen overstory, evergreen understory, mix of shrubs as well. And one follow up in regards to that, to the question that my peer here regarding the access from the north of the stream to the southern part, how would that look? Have you contemplated how that access point, or those access points will? So while we haven't, you know, certainly finalized any plans, I mean, the idea would be, you know, likely making a connection this way. So somewhere in here, there'll be a connection. And I mean, this is not wide enough. So I mean, not so wide. So you'll probably kind of have a big street network here. You'll likely have one east-west street with two cul-de-sacs. You know, this is too narrow to get through. You know, we have a SOAR connection down here where there's an existing manhole. So we have to get that to that as well. Thank you. Commissioner Miller. Thank you, Mr. Chairman. I have a question for staff really quickly. When I look at the future land use map, it's depicted in the staff report, the area to the east of Page Road up to the Wake County line is not colored in. Can I assume from that that that's outside the jurisdiction of Durham City County and it's in Wake County jurisdiction? That is correct. All right, thank you. That helps. And then when I drove out there today, I noticed that what seems to be happening, the trend for development in the areas tends to be towards this low-medium density residential in spite of our future land use maps designation for future industrial. And of course, in other cases, especially on the eastern side of town here, I've been a little concerned about the kind of confused relationship between our industrially designated land and our residential land and the future land use map. And so for because of those concerns and to the extent that this one property tends to move in the direction I think is correct for the area, I'm inclined to support the land amendment and the rezoning. It would be great, quite frankly, if we could go ahead and fill in that whole notch that is created by the existing residential neighborhood and Page Road and get it all re-designated and rezoned all the way up to kind of at least to the top of the notch there so that we have a cohesive residential area. I met with the developers and asked them for the design commitment proffer that they made today and I appreciate very much making that. I think it's a big deal while we have close similarity and density in this property. I think having some design connection, especially with materials will help since there is a form change between single family homes and townhouses. I think that'll make this fit in better with the neighborhood that it's clearly going to exist with. I'm assuming that five years after you guys have sold the last unit and move out, people who drive through there will have a very small sense of whether or not these are two separate developments and I think that's a desirable thing. So I intend to vote in favor of this and I appreciate your cooperation. And I'm sorry, I sound so funny. Thank you, Commissioner Gibbs. I just have a couple of quick comments. I want to commend the developer for the extra 10 feet of buffer. That was a very generous settlement, I think. And this could be for staff and any other submittal that comes in. I've been trying to read the contours, which is yellow on white. Even with my magnifying glass, it's really hard.  And this is a serious request. It does make it a lot easier to follow the lay of the land. Sometimes I can tell you more than a visit to the site. But that's my request. And I intend to support this. Thank you, Commissioner Gibbs. Any other commissioners who wish to speak on this item? And before we move forward with the motion, I just want to check in with staff on the proffers. These have been cleared with the staff. Yes, Jamie Sanyak with the planning department. We have reviewed the two proffers and find them acceptable. I also just wanted to add, if the applicant can provide the approximate stream buffer, I'm sorry, stream crossing location on the development plan map, moving forward, that is a UDO requirement. Thank you very much. Thank you. At this point, I'll entertain a motion. Mr. Chairman, I'd like to move that with regard to case A1700012, the Comprehensive Plan Amendment request that we send this forward to the City Council with a favorable recommendation, including the two proffers that were put forward today with regard to design issues. And also, with the understanding that between now and the time the City Council makes a final decision, I'll strike that that's a zoning matter. I'll hold that. With regard to the plan amendment case, send it forward just like it is with a favorable recommendation. Second. Great. Moved by Commissioner Miller, seconded by Commissioner Hyman. All those in favor, please raise your right hand. Motion carries 10 to 0. Okay. Got to ask for news. We'll move to the approval or motion on the zoning case. Mr. Chairman, because I've already rehearsed my motion on this, inadvertently, I'd like to move that we send case Z1700031 forward to the City Council with a favorable recommendation with the understanding that the request contain the two design proffers that were made tonight and that the development plan also be amended to show the approximate location of the stream buffer crossing that the staff says is required. Second. Great. Practice makes perfect. Moved by Commissioner Miller, seconded by Commissioner Alturk. All those in favor, please raise your right hand. The motion carries 10 to 0. Great. Thank you very much. We'll move to our next case. This is also a future land use map and zoning case concurrent. This is a case A1700014 and Z1700036, the park at South Point 2. And we'll start with the staff report. Good evening, Jacob Wiggins with the planning department. The two items before you are a future land use map amendment and zoning map change request for the park at South Point 2. This is a request submitted by Mr. Robert Schunk with Steward. This is in the city of Durham jurisdiction. The subject site is approximately 41 and a half acres. And the applicant is requesting a maximum of 55,000 square feet for vehicle cells and service areas. Specifically, the rezoning request is to resume office and institutional residential suburban multifamily commercial general all with a development plan to commercial general with a development plan as well as modified the future land use map from the office and medium density residential designations to a commercial designation.  This is the general area is located just a bit north of Interstate I-40. And it is also one will find NC 751 to the west as NC 54 to the north and east of the subject site. As you can see, the area is presently undeveloped. There is, you can see some auto use areas to the south of the subject site. Existing conditions, as I noted, the subject site presently contains three different zoning designations as well as a stream which traverses part of the property. Maybe a little hard to see on the screen, but it is located right there. Adequate buffers are shown for that stream. The future land use map for this area, as I noted, and as you can see on the left hand side, the site is designated as both office and medium density residential. And the applicant is requesting to unify that to a commercial designation. As you can see in this area, the commercial is, I would say, at least in this inset, probably the predominant use, especially along the stretches of I-40.  The zoning context map, the body colors here, the subject site is still highlighted in red and white. As you can see, this kind of green, blue dotted area to the north, that indicates area that is either owned or maintained by the Army Corps of Engineers, and therefore is unlikely to be involved. It's basically wetlands or bottomlands. The requested zoning district on the applicant is requesting the CG district. The ordinance requires a minimum of 20,000 square feet for this use, a maximum of 60% of building coverage, a minimum, please write the tree coverage area and that information isn't correct, but the maximum height of 50 feet is correct. So proposed conditions for the subject site. As I noted, the applicant is requesting to use the site for vehicle sales and services. The key areas here is where this will be located. As I noted, the stream on the subject site is buffered and no development is proposed in that area. Some area of some additional commitments. The applicant is committed to not having any outdoor PA system paging. The permanent closure of Johnson Victory Circle. So my hot back to the development plan. We'll go to the aerial map. You can see there is some pavement here. There is a street. It's not been, it was dedicated as public right away, but it was never accepted for maintenance by the city. So the applicant is proposing to close that street. They can speak more about that. I believe they intend to use it as a private street, but the intent is for that not to be maintained by the city of Durham. Required project boundary buffers are also shown on the development plan as well as the site access points. So some kind of pre-hensive plan policies that staff reviewed as part of this request. And as noted, the, the form category it is not currently consistent, which is why the applicant is requesting to change that to commercial. Otherwise staff found that this request was consistent with the comprehensive plan policies. So in summary, staff determines that this request is consistent with the comprehensive plan and applicable policies and ordinances. And I'll be happy to answer any questions that the commission may have at this time. Thank you very much. Thank you. This point will open the public comment period. At the moment we have two speakers signed up, Mr. Ken Spaulding and Mr. George Stanziel, both in favor. So you collectively have 10 minutes. Thank you very much. Mr. Chairman, members of the Planning Commission, good evening. My name is Ken Spaulding, 7913 Leonardo Drive here in Durham. We are seeking a plan amendment and rezoning of our property from a mixture of uses of office and multifamily to commercial. This property is immediately adjacent to our currently existing auto park. In essence, we are seeking to expand our current footprint. This will help provide an additional opportunity for both our auto park and our city to obtain a new dealership, the Volvo dealership. This will enhance our tax base and provide for new jobs. These office and multifamily parcels have remained dormant for over a decade. Our proposal is flanked by our auto park to the south and significant Army Corps of Engineer property to the north, and you've seen from the map there, multifamily to the east. Our proposal lowers traffic and school enrollment. Staff has presented their favorable review. We are consistent with our city's plans and policies as laid out by your staff this evening and as contained in your staff report. We thusly respectfully request your support as well, which will allow this vacant and overgrown property to be put to its best use and consistency, as Apple mentioned. Thank you for your consideration and George Stanziell, our land planner, will be our next presenter. Thank you. I'll try to be very quick. George Stanziell, President and Director of Design at Stewart. What I wanted to do is just give you a little bit of background because this was zoned so many years ago and just kind of tell you how we got here. The original concept for this project was always to be an auto park and was contemplated to be a high-end auto park. The project was zoned in 2002 to include a mix of uses that included hotel, office and residential, as well as auto dealerships at the strong urging of interim planning director of the interim planning director at the time. This was kind of all going on when all of South Point was kind of being rezoned and designed and master plan and so forth and there was a lot of focus on mixed use. This resulted in the parcels that we're discussing tonight being multifamily residential and in the northeast corner in O&I in sort of the central part of the site and the image that is before you is sort of the original master plan for this site so you see the orange buildings kind of in the middle that were O&I and then the residential portion to the upper right-hand corner. If you're familiar with this location you know that there's very limited visibility to any major thoroughfare which has resulted in little to no interest in developing these parcels under the current zoning. So 751 is where the Lexus dealership is today many of you have gone by there that's basically our visual window so these parcels to the back are very hidden essentially for retail particularly for retail or hotel and office uses. In addition, soils and subsurface conditions on these parcels, the parcels that we're rezoning have made development that is on these parcels have made development that requires substantial foundations extraordinarily difficult and expensive so we've had many people look at it and have walked away. This project has been developed with the highest level design including extensive landscape along the right-of-way along the parkway and particularly on the Johnson Lexus site nearly $500,000 was spent on landscape and stone walls along with 751 frontage which set the tone for the rest of the project and then there's a substantial amount of landscape that has been installed all the way along the parkway. While this project somehow weathered the recession the retail and auto landscape in South Durham has changed with the addition of the Hendrick Auto Mall south of South Point Mall. That project was a perfect opportunity to include in this project and allowing us to keep auto dealerships from lining our major streets unfortunately it didn't work out that way for a variety of different reasons. Mr. Johnson now wants to build out his project in the way that was originally intended. It will be done as we started it with quality landscape treatments and state-of-the-art lighting, signage and architecture. This project is adjacent to I-40 to the South Corp of Engineers to the north and very limited residential in northeast corner the closest single-family home which there is one as well as a church parking lot is some 250 feet away and is buffered by a jurisdictional stream buffer. We are adding an additional 50-foot undisturbed buffer and our property adjacent to that so that is a total of about 300 feet. We have also committed after some discussions that between now and City Council that we will at City Council proffer an additional buffer enhancement with evergreen planting for a limited length. We will work with planning on the location and language prior to the City Council hearing. One last note. During the original rezoning of this project which changed the original zoning the very original zoning of this project was 1,250 residential units. When we rezoned the property Mr. Johnson committed to paying the city's portion of the pedestrian bridge going over I-40 in the amount of $250,000 which we all sort of enjoyed today. He's made a major commitment there and we now want to finish this project after many years. Thank you very much. Thank you. Is there anyone else who would like to speak during the public comment period? Seeing none, I will move to close the public comment period. I will note that we did get an email sent to us earlier today from a resident and I'm trying to look up their name but they had raised concerns. Mr. Wiggins had sent this along to us and I just did want to mention it for the record. Mr. Mark Rodin had some concerns about the lighting issues but could not be here this evening so did send his comments in advance. Let me open it up for the planning commissioners. Anyone on the commission who would like to speak? Commissioner Gibbs, Commissioner Miller. Again, I just have a couple comments and one has to do with... I'm not really... I don't think I understand that the semi-circular drive is that going to stay in? It's called the Johnson Victory Circle? It will... The right of way is to be closed but the pavement and the access will remain right now the auto park is... South Point All-Part Boulevard is a public right-of-way. That was intended to be a public right-of-way but the decision's been made to... a decision's been made to just to turn it into private. So it can be utilized by the dealership at access to our displays and all? Yes, sir. That was really the only thing. Everything else looks really good and the first thing I thought of was just what you said, George, about the dealership down Fayetteville Road. I'm glad to see this come back. This, from its inception, I think was a good idea and this is the first time I've seen a layout of what was intended. I really like the concept and for any other developer and for you and anybody else that may be looking, I think I could find something else better to watch on TV but, in fact, there's a ballgame on that I'd like to be watching but... I do like the use of vegetation throughout wherever the cars are parked. This is something that I would like to see if not added to the UDO that we pay special attention to. It helps reduce the heat islands that can occur with all of the paving and this rule of thumb can be applied to not only car lots but to shopping center lots. It's been used in other places but I'd like to see more of it. It softens everything but anyway, I won't take up any more time. That's just something that jumped out at me and I wanted to put that out in the public realm and the staff realm and our realm. Anyway, thank you so much. Thanks Commissioner Gibbs. Commissioner Miller. Thank you, Mr. Chairman. In general, I have to say they've only been along the parkway that runs through this project a couple of times because for the reasons that you said there unless you're buying a car, not much reason to do it unless you're buying a Lexus until they put the Honda dealership in there was no reason at all but it is quite lovely and it's time I suppose to build it out I can understand the developer's frustration over the years to have planned one thing and not been able to realize it. I also like the idea that that we can have automobile dealerships in this sort of setting rather than along the major highway. It's also in my opinion an ideal use for the strip of property that separates a major arterial from the Corps of Engineers land. Now having said all of that and I've expressed this concern to the developers I know that we have two existing residential areas that when the original project went through thought they were going to have residential neighbors and they're now going to have pretty intense commercial neighbors so I have expressed that concern to the developers and I'm grateful that they're willing to work on a proffer to do supplemental screening I think it's exactly right to call it a boundary buffer because it's not what we're talking about but some additional planning where the graded area of these properties come close to the residential property to the north and the residential property to the east to assist with screening the auto dealerships from those residences especially in the winter months if you drove like I did up through Tudor Place and standing that cul-de-sac and look over the house there and across this property you can see way into the property and so a little bit of additional screening I think will be a welcome thing and make the neighbor relationship between the residences and the auto park a happier one so having said that and with gratitude to the developer for listening to my concerns I'm going to vote in favor of this plan amendment and rezoning Thank you Commissioner Miller Commissioner Johnson Thank you Chairman a number of my thoughts have been articulated particularly by Commissioner Miller I'm inclined to support this and I understand that with time comes like we evolved and what our thoughts and visions are and so the idea of a mixed-use development probably made sense or we were trying to start some kind of momentum but when I think about well I'm very familiar with this area and I drove it two or three times in the past couple days but the notion of there's nothing there really as stated but the idea of just like when you go and shop for furniture furniture you have multiple furniture stores so that people can actually have do their comparison shopping and they don't have to be on the road going to different places I think this is an opportunity to do this for automobile so I don't know how many or what the ultimate mix of automobile dealers and suppliers that will be a part of this but I think that that's a way to get more warm bodies up in this area and the concern that Commissioner Miller raised in regards to the lighting was what I was my only major concern when I went and actually drove back to the residential community on the backside it's like well I like at night time I like for my environment to be dark but there will be lighting and so I don't know to what degree that will assuage the concerns of the residents that highlighted this particular issue but you know from an economic development standpoint of this site has been dormant for a decade or more from what I've learned is that I don't think that there's anything that can be compelled upon the developer to make residential come to this particular parcel when I asked Mr. Spauldin when I had a conversation with him why can't we get residential on this site and that was the question of the soil and the rock under the ground I don't know unless the city ponies up money to do the remediation I don't think that's going to be like a viable option to force the compel the developer to do it so I think that this alternative west makes sense for west there and what can be put there and so with that I'll support this. Thank you. Commissioner Arturk. Thank you chair. This is a question for staff if this rezoning does go through will there be a sliver of office between this parcel and the parcel to the south or am I seeing something there's a on-page amendment three Jacob Wiggins of the Plain Department yeah what you're seeing there the future land use map that little slivers in the public right of way so by ordinance that will be updated so if this were approved you would see commercial in that entire area. Thank you. Any other questions or comments from the commissioners seeing none I'll entertain a motion. Mr. Chairman if I may I move that we send case a 17 triple zero one four to the city council with a favorable recommendation. Second. Moved by commissioner Miller and seconded by commissioner Hornbuckle all those in favor please raise your right hand. Motion passes ten to zero. Thank you and the zoning case with regard to case Mr. excuse me Mr. Chairman I recommend that we send case 17 zero zero zero three six forward to the city council understanding that between now and the time the case gets to the the city council that the developer will work with the staff on a plan to add supplemental vegetative screening in the areas on the property closest to the existing residential neighbors. Second. A move by commissioner Miller seconded by commissioner Hornbuckle for case z one seven triple zero three six all those in favor please raise your right hand. Motion passes ten to zero. Thank you very much and we'll move to our final case this evening. This is a zoning map change only this is case z one seven triple zero two nine for Arrington two and we'll start with the staff report. Good evening Jamie Sonjak with the planning department this is case number z one seven zero zero zero twenty nine the planning commission members have been provided with a short memo regarding this application I have not prepared a formal power point presentation my comments will be brief the the applicant has applied basically because they were seeking revisions to design commitments for the Arrington two site the property is the entire track is about 95 acres of land located on the east side of Page Road in the southeastern portion of Durham just west of Wake County boundary the city council approved a zoning map change and development plan for the area in January 2011 which was legacy case nine triple zero 15 and that essentially changed the zoning for that area to be mixed use with the development plan it allowed for a mixture of office retail commercial along with residential dwelling units a number of site plans have been approved for that area including 200 square foot office building multifamily apartment complex those are noted within the memo the applicant J Davis is currently requesting some minor revisions to the design commitments essentially to better differentiate the type of architectural materials used from the residential and the non-residential buildings and additional clarification has been provided to identify what materials would be used to address the scale of the buildings the main entrances of the buildings and the main entry points there are no other changes to the development plan per the unified development ordinance any revisions to design commitments are considered a significant change and require hearing and recommendation from the planning commission essentially why we're here today and ultimately adoption or approval by the city council staff has reviewed the changes to the design commitments and they are found to be consistent with the UTO requirements the staff report provides the context map the legacy case development plan and the development plan that's proposed as well as the application and I will be happy to answer any questions that you have thank you very much if we could it would be great to see the list of anyone signed up to testify we will open the public comment period and no one is signed up give the opportunity to speak if you'd like to speak please approach the microphone and share your name and address and please speak clearly into the mic and you can sign up when you're finished yes please good evening I'm Jonathan Parsons I'm with J Davis 501 South Bloomington street rally representing the applicant really just here to answer any questions on the development plan as Jamie discussed the whole reason for this tech change is just to provide a little more flexibility in what we're doing for our client which for the office building continuity with the original development plan so materials are staying generally the same we've just expanded a little bit of the portfolio to allow some of the materials are distinct to our client some stones some metal panel but we're still representing and honoring the original plans that's really what we're here tonight so if there's any questions I'm really just here to answer questions great thank you very much you can fill that out and leave that and some commissioners may have questions for you we will close the comment period and move to commissioners if any commissioners would like to speak we'll start with commissioner Miller so thank you mr. chairman I have to say that I read the memo and I heard the report I'm still not sure what we're doing here and I even had to get my magnifying glass out to try to read the the old and new version of the development plan and I'm not sure completely that I get it so I would like to try to understand by asking the applicants representative a question or two that question is what is it about the existing design commitments that prevents you from doing what you want to do or what is it that you need to add to the design commitments that permit you to do what you want to do in the future you're asking for this because you've got something specific in mind so when the original case went forward I will use the word the design guidelines or design commitments that were established were very prescriptive in terms of references to brick banding, types of brick detailing brick color even it was too prescriptive to allow us to add in things like things like bird beaking, flimish bond different types of patterns so our goal was to maintain brick masonry so we still have brick on the building we wanted to add metal panel that was not specifically listed in the design elements but because of the way the architecture has evolved in the area we wanted to add that material we also wanted to maintain our description of how the windows were being used but again it was a very broad term I think in terms of traditional windows so we wanted to provide clarity on what those windows are to allow our building to go forward with the type of windows we're using versus a residential building which is a we used to air post the traditional windows we wanted to help provide clarity so that when we submit our elevations to this case planters we didn't get confusions on our materials versus what we deemed as more residential i.e. that type of brick detailing which is we take the bird beak as we turn the brick 90 degree or 45 degrees so those are things that fit more in that residential character versus a commercial building so again and I got a little confused when I was trying to sort this out all by myself so if we approve this what will be the residential design commitments for the project as opposed to the non-residential design commitments because the report says it's to greater differentiate between the two so what we've done is we're pulling out we're doing a non-commercial project we're doing a commercial project so we've pulled out what original wording was it was all pushed together so what we've done is we've basically outlined the commercial uses and pulled out residential paragraphs and that's part of the text change we're making it clearer so that when our building goes forward we're having these types of uses and any commercial building comes forward will match to our commercial style the residential character is maintained the cementitious siding the traditional windows and repeated it in the second paragraph we're trying to add clarity and conciseness in commercial versus residential so anything that gets built will match the residential anything new commercial will tie into the commercial architecture so as I read it it looked like you were also wanting greater flexibility in commercial form going forward because again with the tiny print that we get like the original plans kind of wanted the non-residential buildings to have a residential character is that right or did I... that was part of the wording issue it was not the intent when we did the original planning for our previous client it's always shown a large format office building at the site we're at an office slash retail component to the left it was a mixed use community now it's part of the challenge tripping up the review was there wasn't clarity so we're trying to help fix that with this section so going forward as pertaining the because you've got what look like two distinct residential projects on the property today and they are not the same but it looks like they are guided by the same standards and those standards going forward will continue with regard to residential construction that's correct but going forward your commercial standards will be more flexible and any confusion that might have existed between the commercial or non-residential standards or residential standards will be eliminated by greater division and that was what the intent is of this change that's a very helpful thank you any other questions or comments by commissioners seeing none I'll entertain a motion we can't send case Z17 00029 forward to the city council with a favorable recommendation actually didn't check it as a city council is that right city council with a favorable recommendation moved by commissioner Miller seconded by commissioner al turk all those in favor please raise your right hand the motion carries unanimously that is it for tonight's agenda do want to give staff an opportunity to give us any additional updates before we adjourn seeing none of good news is we are not meeting on valentine's day this year so our regular meeting is the day before I'll see you then this meeting is adjourned thank you very much thank you


My name is Sergeant Zachary Curtis-Hassman. I am the Advanced Culinary NCO for 168 Armour Regiment. And today we are doing a state competition to give us an ability to show that we can do more than just the regular Army stuff. So today we did the competition on a standard CK, Containerized Kitchen. It's one of the main component, the pieces that we use to do field feeding. With that we were given the chance to have the soldiers and their NCO break into three teams, go out on the economy by enhancements for their product, and spice up the regular old Army steak meal, giving us the chance to show out on what we can truly do and we're not limited to just what is given to us in a box. So the only limitations they were given today was they had to use, for a base, they had to use what was put in the box. So for us it was the mashed potatoes, the green beans, and the steak. The evaluation method was broken down to six individuals. We had our brigade food service team come out and our chain of command, including our company commander, our first sergeant, our battalion serge major, and our battalion commander. Criteria was the basic food credit criteria, taste, look, and overall presentation. And then we added in a teamwork aspect. They were able to come up on the CK and watch us work, giving them the ability to see how the teams work together, communicate, stuff like that. I just would like to encourage all food service personnel to do stuff like this. Give yourselves and your soldiers a chance to show out and do more than just what's asked of you.


This video will demonstrate importing a Red Hat virtualization virtual machine to OpenShift virtualization. The virtual machine to be imported is a Windows Server 2012 R2 VM, which can be seen as powered on here. Viewing the console, it is a standard VM, and we can see the modest resource requirements of one CPU and 512 MB of RAM. Moving to the OpenShift virtualization interface, we will create a new VM by importing using the wizard. Choosing Red Hat virtualization as the provider, the interface then offers a choice of which Rev Manager instance to connect to. The import wizard collects information about the target Rev instance to populate the additional menu items. Here we will select the cluster, and then the virtual machine inside of that cluster to import before moving to the next screen. The virtual machine's current configuration has been retrieved and will be used for the new VM, including the CPU and RAM allocations. If needed, the network and storage configuration for the imported virtual machine can be modified to provide connectivity and performance in line with the source infrastructure. After starting the import, the virtual machine has been defined and the disk is now being imported from the Red Hat virtualization storage domain to a newly created persistent volume claim. The virtual machine has been powered off on the source Rev cluster prior to beginning the import. Detailed status of the disk import is available by viewing the logs for the importer pod. This process will take a few minutes depending on the size of the disk and the speed of the storage and network, so we will skip ahead. The status has changed from importing to off, indicating that it has finished. Since we checked the box to automatically power on after import, the virtual machine has started for us and after a moment we can see which node it was scheduled to along with the IP address. After finishing the boot process, the console for the Windows Server operating system shows that it has successfully returned to operation with only a few minutes of downtime. Thank you for watching this demonstration of importing virtual machines from Red Hat virtualization to OpenShift virtualization. For more information, please visit OpenShift.com.


So we're a week out from the Australian Open beginning, and there are some big exhibition tournaments happening this week, one of the Cuyon Classic, but a new exhibition has been brought up on Friday night, Australian time between Nick Kirios and Novak Djokovic, it's going to be called the Arena Showdown, but this has also come with a lot of scrutiny because of course Nick Kirios didn't play any warm-up tournaments. Let's go over to the reaction from some of the people about this exhibition event. This is what the announcement was on Twitter by the Australian Open. Get set for explosive action as tennis's most famous frenemies come together on RLA for an exciting practice match before hashtag AO 2023, but some of the comments under this post. One person said, this is so embarrassing, charging for the practice match. The AO really work in overtime to become the worst slam. Another person said, I just hope Nick is back to 100% health and doesn't injure himself. He had to withdraw from the Adelaide International. Another said, two of the worst attitudes playing equal hard pass. Hope Novak's convenient injury is healed. Another person came out and said, honestly, can't think of anything more depressing.  And one more comment said, Australian Open, you have lost your way. Charging for practice matches and allowing someone who lied on last year's visa about their vaccination status to compete. Nah, I used to like tennis, but it's not tennis anymore. There you have it, a lot of people coming out not happy about this exhibition event and most of the comments were talking about the pricing. $20 a ticket to watch this exhibition tournament or exhibition event. This practice matches a lot of people were calling it. And it's a practice match, it's an exhibition, but the money's going to charity. And I think that's what a lot of people are forgetting is that it's not $20 going to Kirios and Djokovic, it's not going in their pockets. It's for charity and these guys are both under injury clouds. Djokovic was injured in Adelaide, Kirios doesn't play it on year. So it's one last chance for them to at least get some warm-up and also put on a show for charity. So it's a good thing in the end and of course we're going to be watching it on Friday night. It is actually going to be streamed on the Australian Open YouTube channel as well. So a lot of people can watch it for free and I'm sure a lot of people there that are not happy about it will still end up watching it. But let me know down in the comments below, what are your thoughts on this event and also what have your thoughts been on exhibition events as a whole? Do you think they're a good thing? Do you think they're a good thing for tennis or bad thing for tennis? Exhibition event on Friday night, Kirios versus Djokovic, the arena showdown.


Hello, everyone, and welcome to this UK Data Service webinar, What is Synthetic Data? I'm Joe Fallon, a research associate with the UK Data Service in the University of Manchester, and thank you all very much for coming. So in this introductory webinar, we'll be covering some of the core concepts around synthetic data. So we'll ask ourselves, what is synthetic data? We'll ask why we should even bother making synthetic data. We'll cover some examples, benefits and purposes of that synthetic data, and discuss the sort of features that make those different purposes and forms of synthetic data slightly different. Beyond today's webinar, there are three more sessions in the series. Next week, we'll be running a session on masking and redaction, which are two broad categories of disclosure control. Then in the following week, we'll be covering coarsening and mimicking as disclosure control methods, and then we'll dive into simulation, which is sort of the meaty, fun part of synthetic data. And then two weeks after that, we'll be doing a code demo where we hopefully try and do some data synthesis ourselves. So as a definition, synthetic data is data that is created that no longer measures, but still represents a real-world observation. It may retain qualities of the real-world measurements, but it doesn't really have to. This definition might sound very vague, and that's because there is a variety in sort of the methods of synthetic data, the uses of synthetic data. We could argue that making up random numbers in our head and writing them down is technically data synthesis, but it might not be as useful as a sort of huge machine learning model, which generates realistic dice rolls thousands of times a second. And particularly in the world of machine learning, this term synthetic data specifically refers to data created by these models. And that synthetic data is also used to improve the training of models. So there's lots of very fluffy, different definitions of these terms, but we'll sort of cover that throughout this webinar. Again, something very similar, disclosure control. It's related to synthetic data, but it's not synthetic data, but I think it's really useful that we define this upfront as well. So disclosure control refers to methods that allow us to protect the confidentiality of subjects of research. Some simple examples of this might be just removing the first names from a dataset, adding noises to ages, weights, or any other numerical value, or it might even involve sampling the real data. So there doesn't actually have to be something to enhance confidentiality in that approach. It's all about the way we apply it. It's up to the researchers to determine which outputs of these processes count as safe or unsafe. And as such, there are no hard rules and the outcomes of this process is quite inconsistent. We could argue that synthetic data is kind of the solution to the problem disclosure control is trying to address. Another useful definition of synthetic data is simply any data generated by a computer simulation. Though through this definition, we could separate out what is considered those disclosure control methods, such as removing a column, sampling, and more. We could also get a little bit more philosophical with definitions like this. We could argue that our brain is doing this synthesis and imagining dice rolls and shouting out numbers does count as synthetic data. And in what ways is that even different from sampling? And in that regard, it would be disclosure control. So yeah, it's all very strange and we really are on the fringes of the data world when we talk about synthetic data. In an academic sense, the term synthesis specifically refers to the creation of some data. So again, any references to removing, replacing, or reducing precision data is not academically speaking synthetic data. Though these methods of disclosure control grant very similar benefits and there's such a large thematic overlap that we cover them in quite a lot of detail. Yeah, but let's move on to some examples. So a common example that you might have heard of is called Lorem Ipsum Text. So Lorem Ipsum is a placeholder text commonly used in design to allow designers to sort of step away from the meaning of text while focusing on visuals. It's just a repeating string of Latin text that obviously does have a meaning in Latin, but for our purposes, the meaning is not important at all. It's not the primary purpose. And Photoshop and other sort of graphic design tools have a plugin that would generate this text and visual elements for you. So all it is is it's the creation of something and we're kind of misusing it. So our eye count is synthetic data. You may have heard of generative adversarial networks. They're very popular in media at the moment, just referred as GANs as well. And they're famous for their ability to sort of make realistic photos of synthetic celebrities, baseball players, all sorts of weird stuff. But they're a really nice sort of visual example of data synthesis. And I'm sure if you look at these pictures you might think you recognize some of the celebrities, but they should only be inspired. I can definitely see Nick Cave, for example. Yeah. Another example of synthetic data would just be any random number generation. We can ask questions about, you know, just how random this generation is and is that fit for our purpose or is that adding some strangeness to it? For example, imagine using one of those random number generators to simulate the rolling of a six-sided dice. Well, difficult to exactly represent what we would call the sort of uniform distribution of a dice roll. An approximation might be fair. There may be an impact statistically from the small weight distributions from the different carving of numbers on different sides of the dice. But really we can abstract this away. We don't really care about that complexity for our simulation. But reasonably, we'd be concerned if I rolled the synthetic dice and it came up with a zero or a seven when we're expecting it to be six-sided. We would quickly lose trust in that synthesis and we would also be able to tell that it was synthetic data. And if we can tell, machine learning can often tell too. So even this example, as simple as it is just rolling dice, we could make mistakes here. It could be inadequate for the needs of our synthetic dice as well. Next we ask, why might a researcher even want to bother producing synthetic data? We have a problem. It's difficult to make data available for research and simultaneously protect the privacy of the people that data represents. For example, we might have records on crimes committed by individuals or medical records over a 10-year period. Researchers need to create and use data that does not represent real observations as a legitimate part of their research, processing increasingly that some journals are requiring open data sets for papers to even be published. This synthetic or fake data can be entirely artificially generated or can be based on real observations that have been manipulated or processed in various ways. This means that synthetic data can mimic sensitive data but without holding those sensitivities, I suppose, when it's done right. Some purposes we might have for synthetic data include improving a machine learning model, creating data to be analyzed by a third party, creating data to be used in a recruitment tech test, creating data to showcase a data set and sort of market that data set or to test an existing system. But we'll cover these in a lot more detail later on. Synthetic data is not yet a trivial problem for a number of reasons. A data set may have non-linear relationships that connect fields. For example, if we stored the age, weight and the heights of some children, it's not realistic to simply sample these values individually. There is a correlation between those fields. And if we sampled individually, we may end up with very tall, unrealistically underweight synthetic children. And yeah, we would recognize that and so would a model. So as a data set becomes more complicated, the process of synthesis becomes more complicated in tandem. It's much easier to simulate that dice roll than is to create these realistic synthetic individuals. You also need to understand the confidentiality concerns associated with your data. GDPR protects some fields. Personal data refers to any data which relates to a living individual who can be identified. A non-exhaustive list of data that you could never be sharing on names, identification numbers, location data, online identifiers. But there are always exceptions and that's your responsibility as the researcher to understand and showcase those. Further to this, we have special category data defined as any data consisting of race or ethnic origin, politics, religion or philosophy, trade union membership, genetics or biometric data, health and sex life or sexual orientation. Finally, we also need to be aware of indirect identifiers. For example, in many regions, a postcode can very accurately predict race and religion depending on how we open up this data, these individuals may still need protection. Again, as synthetic data does not represent real individuals, we could benefit from a simpler confidentiality concern here. It's important to be aware of the legal implications of synthetic data as well. Depending on the data you make use of, you may not have the right to distribute that data synthetic or not. Consider whether you can legally share any data you have created and the impact of that data. If in doubt, communicate with your data provider about the data you've created. The responsibility may fall on them to verify and distribute your methods. And finally, we need to watch out for any domain-based complexity. Different organizations have very different views on representing gender and databases as one example. They might use a column, is male, and then a true or false value. They might store an M for male and F for female. They might have an O for other or they might have all sorts of other things. As we get deeper into the complexities of an individual dataset, we see a lot of assumptions are made that are often unique to an organization and maybe even within that organization unique to that dataset. Data in one dataset may become dangerous when combined with another. We might have an ID value that is seemingly harmless, but when joined with transaction data, might expose an address or payment details. And without understanding the organization and the quirks of these datasets, we're likely to make mistakes. We need to understand this domain well before we can ethically process and synthesize any of its data. A solution here is communicating well with those domain experts, seeking out documentation if it exists. But with the above difficulties in consideration, there is not yet a one-size-fits-all solution to data synthesis. We need to ask ourselves if the benefits are even worth the time and cost. There are some questions to ask ourselves before we even engage in data synthesis and that's, are there any relationships between our variables? For example, is it realistic that a user, Joe Allen, might have the email AndyDeFriends at gmail.com? If we have data on individual weights and heights, should they correlate? This all depends on the purpose of our synthesis. And for machine learning purposes, the answer to those questions is almost always yes, we need correlation between variables. Next, should we mimic the real-world problems or try to fix them? There are countless news stories about models giving harsher criminal punishments based on race or postcode, again, in direct features. Or even the recent GCSE and A-level results use location as a factor in those grade predictions. So should your synthetic data try to perpetuate those historic biases or try to fix them? And I guess it's both to think that we understand all the biases we're going through now as well. And finally, should we apply some methods of disclosure control? So for machine learning purposes, using personal data can sometimes be justified. But if we're hoping to make that data open or verifiable, data needs to become non-identifiable. There needs to be almost a negligible risk of re-identification from that data. We should also ask ourselves, is there any benefit to this data synthesis? One benefit is that synthetic data can be made open, making your work verifiable and extendable with ease, and I suppose, crystallizable as well. The process of generating synthetic data itself could be an excellent exercise in understanding the problem. Generally models improve in accuracy. This is sometimes true, but generally it is true. This means well utilized synthetic data could improve your model. Many online competitions have been won using synthetic data techniques because it gives them access to a larger pool of data. Analysis of synthetic data might be a useful trial task before committing to hiring an employee or a PhD candidate to work with the full data set, and this ensures that they actually have the needed skill set and they're actually interested in the data itself. Synthetic data might be the most cost effective way of acquiring more data. And finally, safety. If you're investigating airplane crashes, cancer cases, it's not really feasible for us to wait for more to occur. To protect individuals, organizations protect their data. If there is no data on real individuals and our data set, we may not need to be concerned about privacy. There has been an increase in black box attacks on machine learning models. This is where attackers try to pass in data to reveal information about the individuals the model was trained on. This means that if a model was trained on synthetic data, we would only be exposing these synthetic individuals. And since it doesn't represent a real individual, these attacks would hopefully be meaningless. Anonymization is again heavily context dependent as with this entire webinar is going to suggest changing the name Joseph to BOSIF or the uppercase version of Joseph isn't really going to do anything to protect my data. We can still understand it. We still know who it's related to, especially if everything else in that same record highlights who I am, for example, my email still says my name. So we've not really saved me there. Instead of better technique might be to replace or remove these names altogether. So we might mask the name Joseph with Andy. We might mask the last name Alan with Shiki. But yeah, as I said, even though my name, Joseph Allen has now be completely wiped from those two columns that you would think hold my personal data, my email still exposes my record. It still identifies me uniquely. And so what we should do here is again, make use of those new synthesized or masked first name and last names and generate a new realistic email address. Saying so is trivial, but we could do this quite easily in Python, but that's an expectation that I have you all that might not be true. So it does become slightly more complicated already. And then finally, we course in our address. So this involves reducing the granularity to the first two characters of my postcode. Normally, that's enough to sort of get a decent area, but especially for the Manchester postcode, that's enough. So we can change this data in many ways, as you've seen here, to protect the anonymity of individuals in a dataset. One method is replacing those common details like emails, names, and addresses. But depending on your work, your data may become less useful without accurate addresses. So in this case, you have a case to make that you need those addresses and your research won't make sense if those addresses are course into such a high degree. If we generate a new name, then we are creating synthetic data. But in this case, it's likely that we sampled that name from our minds or from a data generation library or from a list of names online. So this is a method of disclosure control and not data synthesis. But I think this is where the lines get quite blurred between them. When we course in the address, that specifically is disclosure control because we're reducing the precision of that data to protect the sort of anonymity of that individual. There are fears that synthetic data is not GDPR compliant. According to Recycle26, if data does not contain personal data, then it complies with GDPR, even for statistical and research purposes. Also it's further stated that pseudonymization is appropriate protection for data. This is a process of replacing all identifiable information with artificial identifiers. It is of course possible that our data synthesis is simply a model which happens to replicate real data. In this case, obviously we're not in compliant with GDPR. So just because we're using synthetic data doesn't give us a golden ticket to use that data. On the other hand, our model could take that good data and just output random noise numbers. That would be compliant with GDPR, but it wouldn't be useful to us. So it's these shades in between each method where we need risk assessments. It's not enough for us as the researchers to say, my data is anonymous, please trust me. We must document our approach and verify our results to protect ourselves. As long as we can show that to the best of our knowledge, this data is anonymous, then we should be okay. Generating more data could be an effective way to improve the results of your model. So data augmentation is one successful method. It's very easy to see when applied to image recognition as well. So data augmentation is defined as techniques used to increase the amount of data by adding slightly modified copies of already existing data or newly created synthetic data from existing data. So for example here, instead of having 100 photos of handwritten digits, we could instead shift their position, rotate them, shear them slightly, change their colors and combine all of these different methods to create thousands of realistic images. Again, that's not synthesis there where taking what we have and moving it, synthesis would be creating new characters. But yeah, these techniques are mature enough now that they're often built into popular machine learning libraries. I know Kiris definitely has a data augmentation function just for images. Again, in cases such as car crashes, medical scans or fraudulent transactions, the obvious application of machine learning here is to try and predict those negative outcomes before they happen. Also in these cases, the majority of the data is hopefully on normal driving, healthy scans and real transactions. So generally, we won't be able to quickly discover more legitimate cases. We might be able to buy large data sets on these, but it might be expensive. The format might be incompatible with what we've done so far. So we would really have to invest time in correcting them. In many dangerous cases, as I said before, we don't have the luxury of waiting for more of these events to occur as well. And this is where synthetic data can help us enable us to begin to solve these problems. Whilst data synthesis can be very expensive, sometimes it's the most cost-effective way of collecting more data with limited resources as well. So for example, imagine you wanted to build your own realistic backgammon bot. How would you collect data to train this bot? You could hire players, record the games, oops. All right, you could hire players, record the games using a camera and personally convert moves into a backgammon notation. You might make mistakes in transcription, but you also might not make any mistakes. You could play the games yourself, inputting only your play style and again, dedicate many hours to transcribing games yourself. Again, you might make some mistakes here. You could pay for a huge data set of backgammon games and just hope that because you paid for it, it has good quality. Alternatively, the rules, notation and even backgammon engines already exist and we can make use of these to create synthetic games. This might be the most cost and time effective and you could now generate as much data as you can realistically afford to store. Would these synthetic games be any less valid than the real games for your purpose? I mean, we didn't really say what the purpose was, but if we needed to mimic human delays, if we were trying to make something that seemed like a human player, maybe we do need human delays, human mistakes instead of these backgammon engines. And this again is where the context of your problem is a key part of the synthesis techniques and tooling that you'll have to use. When organizations require a sign-up process, paperwork or permission, any sort of larger commitment they can often scare users away. When we make data open, it should be as easy to access as we can allow it whilst also protecting the individuals within. If your data is safe enough to be shared publicly, you can open your work up to other academics, industry leaders, third parties, all sorts of people and together we can crowdsource better answers to the same problems. Thanks to synthetic data, even your sensitive data sets and corresponding analysis and models could be made reproducible, criticizable and more importantly, extendable. And again, I must reiterate the warning from before. It's important that you always follow the rules of your data provider. If you aren't sure what those rules are, you can contact support at ukdataservice.ac.uk. As an example, let's say you're all my students. Over this school year, you're going to sit four tests and they're all out of 100 and your final grade will just be determined from the sum of these results. I could do this by hand, but I teach a lot of students, there's 46 people here, that might be too much work for me. So this repetitive task to me calls for a programming approach. So we'll look at code only for two slides here. So don't worry if you don't know any Python or any programming, but if you do know Python or you'd like to know more Python, make sure you sign up for the code demo that comes with this series. Personally, my language of choice is Python, especially for anything data related. I could start by writing a function to sum these values and assume it's correct. But there is this newer notion called test-driven development where testing is the priority and you write tests before you even write the code. I have a function I've written that expects a data frame of scores from zero to 100 of these test results. I have a function here that creates a new column sum. This column finds its results by summing up the values in other columns of the same record. An axis equals one while not intuitive basically means sum the rows instead of summing the columns. If it was axis equals zero, that would mean sum the columns, but that's not what we want here. Then finally, I'll just run df.head. df stands for data frame. Head refers to getting the top of the data frame and by default it will return five rows. So these sums look good, but they require me to sort of manually make up valid data, put it in the correct format. And I probably won't test it again until I get to the end of the school year and I put everyone's data into a spreadsheet or something unless I have synthetic data. So instead of just assuming that that function works and hoping that it's gonna work when I get to the end of the school year, let's write something that generates data in the format that we expect to test the function. Again, we're writing in Python. So I'm importing two libraries here, numpy, which adds support for large arrays and matrices and a bunch of more complicated maths functions. And pandas, which adds support for data manipulation. These two libraries encompass most of the Python data world. Next I'll create a variable df as we used in the page before. It's short for data frame that might be familiar to you if you use R or Python or anything like that, but basically it's a glorified table with some extra functionality. So we're creating that data frame and we're filling it with random integers from zero to 100 defining a size. And then I'm creating the column addings a, b, c, d. In the real world, you might expect some exams are slightly more difficult than others and the average will be brought down. We would probably expect that some students on average are better or worse than other students. And we would expect to see that consistency, but in the synthesis, we've lost that notion. We're happy with the uniform distribution that kind of looks random. We could dedicate more resources to generating meaningful synthetic students and good students, bad students, or maybe I should say bad at exam students instead of bad students. But yeah, my only purpose here is testing that sum function and this is more than adequate. Cool, just gonna have a little drink of water. Right, we've seen loads of benefits there. I'm obviously trying to sell synthetic data to you, but there are reasons that we might not want to make synthetic data and they're often equally valid. First of all, a lack of understanding about what synthetic data is, there is worry that synthetic data still contains personal information and it's possible that it could do depending on how you do it. So these same safeguards still apply regardless of that source. But yeah, if you do it correctly, that's not the case. Secondly, there's a concern about privacy breaches. So if the synthetic data was stolen, for example, if it's internal to an organization or to a particular university's research, if it was stolen, you would now be responsible for the identifiable individuals in that data if your synthesis wasn't done in a way that protected them. With good documentation of your methods and hopefully it's quite difficult for outsiders to understand what that data is even referring to, it should help us, but yeah, it's something to be aware of still. Thirdly, there's a concern about controlling narratives. If for example, we work for an organization where we are aware that our data may make it look like that particular employees are sexist, for example, or that there are known issues within our data that the media may spin or even truthfully represent, it may be in an organization's interest to claim privacy concerns to protect that organization. But again, as I've said, when it's done correctly, there shouldn't really be privacy concerns. Next concern about synthetic data being misinterpreted as real, if we have a dataset well documented with the same name, the same distributions and very realistic looking individuals represented within it, it could be a problem. Even internally, we could mix up datasets, we could mix up our synthetic customers with our real customers, but a solution here is a very clear separation between that real and synthetic data goes far as renaming all the files to synthetic transactions.csv, prepend all the columns with synthetic or test or something like that.  If you release it publicly with these clear flags, it can be a bit easier. But without them, somebody could claim to have real data and we wouldn't really know without someone internally looking at them. In the first synthetic dataset produced by SYLLS, all columns were prepended with SIN, short for synthetic and the data itself is actually watermarked with a synthetic data message, which makes it very clear in Excel, but that wouldn't really apply if we were opening it in Python or R or anything like that. So it's a good way to make it very obvious what you've got there. And then finally, it's okay to admit that we might lack resources. We don't have to be good enough to create synthetic data. We don't have to have a purpose for it. It might just be out of our remit. Data synthesis, as we've shown, grows in complexity with the complexity of our data.  Data synthesis discover information on the individuals. So that's use of real names, addresses, oh, yeah. Should be back now, is that all right? I got a warning about internet connection there. Anonymity, this refers to when, whether there are still methods by which we could discover information on individuals, the use of real names, addresses, or other protected features here are problematic. You have to be careful when training a model that we aren't exposing our outliers in particular. Next, we have structure. We ask, is that data in the same shape as the real data? Would it be useful to redact certain columns? For example, our models probably don't actually need the first name field. Do all columns still hold valid data? For example, if we have ages of minus one or we have missing values and do our columns hold similar distributions to the real data? Next, indistinguishability to a trained eye, could we separate the synthetic individuals from the real data? If we can, it's likely that a model could as well, but this is where we can have those sort of fake names and interesting ways of doing that in a way that won't affect models or analysis. Relationships, are the relationships between columns maintained as well as valid? Does weight and age correlate correctly as we saw before? Size is our data set the same size or larger than the original data. In some cases, we might need five or 10 rows to showcase data. Documentation, are the quirks and metadata well documented? Could we safely expose some averages or standard deviations of our columns? And do we understand the quirks of the data set? For example, how that gender column is used internally? And then these are five common purposes for synthetic data. It's not an exhaustive list, I'm sure there's more, but this is what I could think of. So machine learning, this synthetic data is used to improve the training of the model. Analysis, this is data that would be shared internally in an organization or with third parties for analysis, research, peer review, recruitment. This data could be used to assess a candidate's aptitude before applying for a PhD topic when hiring a professional to work at your company. Showcase data, to me this is sort of like marketing data. This is display data that you would use to encourage users to engage with a particular open data set, but they might have to apply to get full access to the unrestricted data set. It could just be a few simple rows or it could be a large data set constructed for use at a hackathon or something cool like that. It's purely to sort of demonstrate the layout of the data and convince people that it's easier to engage with than it might be. So yeah, you could alternatively say that this showcase data is primarily a marketing tool. And then finally, testing, this is data used to test existing systems. So invalid data here could cause an API to break, could cause a website to crash. So the purpose might be to sort of break those systems, but only within an understanding of what those systems are actually expected to receive. So we need an understanding of the requirements of those systems if we're gonna test realistically. Now these purposes all require different features and with each of these features potentially comes its own complexity. So to start with, we'll look at the machine learning purpose. So it must be anonymous, it doesn't have to be, but we're risking these black box attacks as we talk. So I would suggest try and make it anonymous if you can. If our synthetic data is showing the same weaknesses as real data, we're just exposing individuals and our predictions, we're getting half the benefit we could be getting really. The structure must be similar to or a subset of the real data, whatever your model expects really. Free text fields could be ignored, but most categorical or numerical data should be kept until it's shown it's understood or irrelevant. While we could get away with replacing free text with something less personal, it depends heavily on the context. Using nonsensical names might be a good way for humans to recognize this as synthetic data without affecting the model's training. The relationship between variables must be maintained. This is the crutch that machine learning is relying on. So if we deviate from this, our accuracy will suffer very quickly. The size of this data set should be at least as big as the real data set. And as synthetic data is hopefully at this point, a cost-effective way of generating more data were limited only really by the storage costs of that data or at the point where the training sort of tapers off in accuracy, I suppose. And finally, any quirks of this data need to be documented. Whoever's performing the machine learning needs to understand exactly how this data is relating with the problem context, otherwise we'll make assumptions and we'll end up with something that's just not correct at the end. They may also need to pre-process that data based on the context you've given them. So the analysis purpose, we may not need to anonymize the data if we're only sort of sharing this internally or it's staying within a particular team. That being said, anytime we are using personal data, whether it's in research and industry, wherever, we need clear justification for the use of that data within GDPR constraints. Also, you're limited in who you can ask for help. For example, if you did employ a third party to perform your analysis, there might be more hoops to jump through. The structure could be identical to the real data, but a subset of the data might be acceptable here. Again, data for analysis, when synthesized needs to be indistinguishable from the real data and maintain relationships between those fields. We could get away with approximating our full dataset so that the analysis can be performed in less time to understand those trends and documentation of quirks is still definitely needed. Otherwise the analysis is gonna be making a lot of assumptions. For the recruitment case, I think it's important to preface this because not everyone watching this is in industry or we'll be aware of this, but it's very common if you apply for any sort of data analyst or data science role to be given an interview and that interview will be based on a take-home task and that task will normally consist of some famous dataset or internal dataset that's been cleaned up and the prompt explore this dataset and find three insights or assess the quality of this data or something like that. But what could be even better here is generating a synthetic version of the internal data those candidates would actually be working with. And this way your discussion can exist in that domain very close to work in the real role instead of using the Titanic dataset of people who lived or died on the Titanic. It gives a, there's some cool stories but it's easy to be curious about a cool story over what the job might introduce. And yeah, when you're synthesizing the data yourself you can introduce errors, you can force distributions between columns and hope that candidates will find them and bring them up. So it can be a nice way to sort of improve the recruitment process. So yeah, again, for recruitment we must guarantee that anonymity. It's super important here because when people don't get jobs they can be quite spiteful, they can be malicious and they still have that data. The structure could be identical to or sort of simplified version of the real data. We might want to simplify it just out of respect for those candidates time. In this case, we could intentionally make it obvious that the status synthetic using those intentionally fake sounding values for names, emails, things like that. Depending on what we want to assess in the individuals we might want to maintain or tweak some of the existing relationships. We might limit the size so we can send it over email instead of having to upload to Dropbox just keeping things easy for us as the employer basically. And documentation of any quirks is needed for the candidate to understand that initial meaning. But we could hold back here. I personally think it's quite interesting to see what people do when they don't understand the dataset and see if they sort of silently assume things or if they get upset and maybe I shouldn't be saying this a little bit now but yeah, it can be quite interesting to see how people respond to that. Next for showcase data we can probably cut the most corners. As I've said, it could be as simple as five handcrafted rows that have the general shape of the data. And we might just list this in a GitHub page that describes how to access the full dataset or on the UK data service. It could be a nice sort of marketing tool for a new dataset. It could also be a large dataset that lets you sort of practice your analysis before you get access to the data, for example, in a secure lab. But the purpose here is to showcase what a user would get if they had the real data without requiring them to fill in that paper, you know, the paperwork go through the training or any of that. So if you maintain any data that's behind closed doors that could benefit from being open this would be my suggested first step, you know, get a showcase five rows out there somewhere. Of course we need to maintain anonymity in any dataset that will be freely seen. We can cut some corners on structure. Maybe we only show a few rows and a few valid columns. It doesn't matter if these rows use obviously fake data as users should hopefully know it's an example. We could, but we don't need to maintain any relationships here. As long as our data is valid as these showcase rows it's probably not going to be used for any final analysis or potential training. Again, for the size, we probably only need a few rows here but we could make it as large as we want. And as this is showcased data I would suggest that we have the clearest documentation we can. This is data that we're hoping to sort of entice people with the people outside of the context of the particular dataset might find interesting, might build an event around, might ask for more access to the unrestricted data, things like that. And then finally we have testing. So for testing data we can use clearly synthetic data and it might actually help us a lot to do so for example I used to work at a travel company and we would sort of place hotels in the middle of the ocean or we'd make them look like they were on the moon so that nobody would try to book them or think they were real because of the absurdity. This data can be nonsensical but it still has to be valid. It still has to conform to the rules of existing data. We don't have to actually try and support a hotel on the moon with a moon currency. We know that our system is probably only going to exist on earth. So we're not intentionally trying to break those systems but breaking them within a sort of safe environment rather than taking down those live services. Even though this data is used internally it's not ethical or safe to use personal data. With the right mistake we could accidentally make hundreds of bookings on a personal card if we were using real data. So it's best to create artificial users and test cards and things like that. The structure of the data must be identical to what these systems are used to receiving. So if there's functionality that should exist but doesn't, for example, maybe a first name field should accept handsy Chinese characters in the name field but we're just a small UK based company right now and we just happen to have not encountered that yet. That's useful testing. That's something that could break the system. We could already have encountered that in the real world. It just so happens we don't have users that want to write their name in handsy. Our data doesn't have to blend in with real data though. We could use intentionally nonsensical names like test, McTest person. So if anything does go wrong, our reporting will make that very clear that it's only an internal problem and we're not actually mistakenly making bookings for a real person. We may want to maintain relationships between columns. So this will depend entirely on sort of the business logic we're testing. In most cases, as long as it's valid in structure, I don't really think we need to worry about this. In terms of the size, we probably want to generate a handful of cases or one of each sort of realistic edge case. We might want to test our APIs every hour, for example. So we're probably talking about less than a thousand rows of data a day, though it might need to be generated in real time instead of picked from our heads and consistently ran every hour. But yeah, hopefully within an organization, if you care about testing, there should be enough access to this kind of knowledge that documentation should be the easiest out of all of them. Yeah, cool. Thanks for being with me on those very information dense slides. As we assess these different purposes and features, we find the context-specific solutions to the problems of data synthesis can vary quite a lot. So to make data fit for a machine learning purpose, for example, we should probably run some data processing, apply some machine learning, or alternatively, there are some really nice modern data synthesis packages, such as Synthpop, Faker, and Mockaroo. Again, we'll cover these a lot more in sort of the third webinar and the code demo. For the analysis purpose, we could probably ask, do we actually need synthetic data or is it enough that we apply statistical disclosure control? If we redact the private data, re-sample some other columns, add some random noise, that could be enough, and we might not even really need to dive into a programming language to do any of that stuff. For recruitment, we can cut a lot of corners. The context should be realistic, documentation should be okay, but the data doesn't really have to be. We could use a cool web-based tool like Mockaroo that allows you to generate 1,000 rows of data, modify it yourself, add outliers, add and valid data, force obvious relationships if you want to, showcase data. I think this is the easiest one. You could just get away with five rows of data really, could be done in Excel or Google Sheets, but if you need a larger data set, you can redact and re-sample and add noise from a real data set. And for testing data, we need realistic data that can be generated, hopefully at the time a test needs to run. It might be good enough to have a handful of hand-picked examples that we sort of randomly select from, but will probably benefit from real-time generation of data if the purpose there is to sort of push the limits of your system rather than break it. So Faker from Python is really good for that. And to conclude, so synthetic data can create sensitive data, minus sensitivities. I guess all of these come with the caveat that they can not as well if you sort of don't do it well, it won't help at all. Synthetic data can be a cost-effective way of improving models, but again, it might not improve the model. Synthetic data can make your work more reproducible, extendable and verifiable, but if you're not doing anything for privacy, you'll probably just get in more trouble than it's worth. And then finally, we could use synthetic data for a variety of purposes, including improving models, making data open and testing code. After this webinar ends, you should see a prompt to leave some feedback. So please go through this short survey. It helps us make better webinars. Yeah, and then there's some further reading. If you are interested in any of what you just heard, there's the data in government synthetic data blog that was really good. Most of this talk is based on that. There's a nice podcast on gradient descent with the founder of AI Reverie about how synthetic data is used in the industry. And then I wrote a blog post, which is pretty much this talk with some extra technical details. There's also some more practical technical frameworks. There is the synthetic longitudinal study that I mentioned before. And finally, if you want it, there's a book recommendation, Synthetic Data Sets for Statistical Disclosure Control. But otherwise, I'll see you in the next webinar and I'll take some questions now. If you do want to contact me outside of this, I'm very active on Twitter or you can email me at joseph.alan at manchester.ac.uk. Yeah, obviously some people might watch it on YouTube so that'll be useful for them. But I think that's everything.