What's up everybody, Jason here for jaspyscasebreak.com just sold out 2019-20 Panini Immaculate Basketball five box casebreak picker team number 12 on our website and looks like you guys were even getting 20% off every team discount shown in the cart. Well, we did do a little R&B here five box picker team that included the Grizzlies, Lakers, Heat Bulls, Cavs, Maths, Celtics, Hornets, Thunder Nets, and Clippers and that sold out and here you go. So here are the customers that bought in straight up and then the customers of course that won spots in the filler little R&B and then there's the customers here of course with the teams list right down the side so you know what teams are part of the R&B. So good luck guys Immaculate Basketball I'm gonna get you I'm reading the right one yeah. 19-20. I know Ryan I know you're really close on the first one man always tough to win those fillers though. I'll show you guys the list one more time.  OKC, R&B, 85, Gwena J. We got a little relic here of Terence Davis. 45 out of 99 for Toronto. Nick with Toronto. That'd be nice Ryan. We have Darius Basley or Basley. 4 out of 50. Look at that jumble patch right there. Jersey numbers. Another one for OKC. I think he's also gonna ball off this year too. Four. Gwena Brett. We got ourselves a little Langston Galloway for the Pistons. At a 75. Detroit Pistons. Gwena Josh Proust. Pre-season's already up Rebel. Basketball comes back on the 20 seconds. So next weekend. And we got a little veteran autograph patch auto. Three or sorry eight out of ten. A little Colin Sexton. Cavaliers. Part of the R&B. Eight. You guys can see that right? Number eight. Gary Meyers with that one. And how about a little future Hall of Famer Vince Carter on card. For the Atlanta Hawks. Matthew with that one. 48 out of 49. The weather system. That's part of the forecast for those that need to have a car. Alright. Next one. One person was killed in a time today. Suspected run driver early this morning in El Monte. It happened around 5.30 at Peck and lower disease of roads. El Monte told me to say a truck was collided with a passenger car. The driver of the car was taken to the hospital. The passenger in that car was pronounced dead at the scene. The low driver of the truck suspected of driving under the influence was also taken to the hospital. An LAPD officer is on the men tonight after being hit by some of the arrested for DUI. The officer was on patrol in San Pedro last night. Town horned tugger man who was balling. People want their autographs with him now again. 27 out of 49. 27 out of 49. Atlanta Hawks. There you go Matthew. Next one we got for the T-Wolves. D'Angelo Russell. 42 out of 49. Ooh, that Steve was speaking into existence. KG, I thought he was saying wolves auto coming up but it was a wolf's relic. There you go. Porzingus. 3 out of 6. Little patch there for the Dallas Mavericks. Dallas, R&B 3. Going to J. Next one we got is a little ML car. Celtics. 3 out of 75. Nas Reid. 75 out of 99. Another one for the T-Wolves. And nice. 3 color packs there of KPJ. Kevin Ford Jr. 4 the Cavaliers. 18 out of 25. Spot 8 going to Gary Myers. Alrighty, still 3 more boxes guys. Let's see what else we got here. I mean Steve, I know for sure when it's high end like this I think everybody can agree but I just think stickers are here to stay forever. And I don't always blame Panini and the companies. It's really the players. We should be getting mad at these players for not wanting to sign on card. Especially Redemptions. Not wanting them to be able to fulfill the redemption on time. Out of 49 Russell Westbrook. It's like what was it? Was it Zion and Panini 1? They literally couldn't get Zion probably to sign on card, right? So they had to just use stickers on him because I don't think they even wanted to try to get him to autograph starting his second year. So it's like they had to use a sticker for him which kind of sucks but at the same time we still got a Zion auto but it just sucked that it was a sticker. Anthony Davis. That's Pelicans edition. Remember we go by the team on the card. So Anthony Davis of course will go to the Pelicans here. Showing you when he was an All-Star in 2019 there before going with the Lakers. Whoa! Look at this. A little one of one tongue logo. Man, look at the tongue of the shoe. That is... wow. The dream. Sneak peek. That is very cool. Look at that. First of all, let me just put this in a little slider box already for a drop it or something. Matt Arnone has the Rockets first of all. This is all yours man. Oh wow, look at that. It is so sick. Backwards too on this side. That is so nice. Kind of shoes. Is this the shoe brand back then? Atonic? It is so sick. Definitely going to go on the ground. A little Chris Bouchard. A little pro duck right there. 58 out of 75. Toronto Raptors. Nick with that one. How about a little Andrew Wiggins for the T-Wolves. 69 out of 99. I don't know enough for you Steve. Hypnotic in his cup. And we have a Darius Basley out of 75. Thunder. 68. Going to Gary's. Spot 8. And we do have a blockchain guy so this will go to of course the team. And it is premium patch autographs. Ty Jerome. Nice JV. Did you look that up? That is cool. Suns. Phoenix Suns is going to brine. If it sells all Tyler, we have to sell the spots straight up. Plus that one little filler. That is it. So out of the mixer for the basketball mixer and football, I think the basketball, football one is much closer. Although the spots straight up seem a little farther away. I like 10, 12 left. But once we sell those out guys, we only have that one filler left and that is it. So there is no possibility. I mean I am still going to be here at least for another hour or two. And like I said, I would like to stay late if there is people wanting to continue to break tonight. But like I said, if not, we will be back tomorrow. So remember guys, I will say it again. I haven't really said too much. But oh really, it is down to 5 now? Then maybe Nick might have taken out some spots in Tyler. I will have to double check. If it is down that much, unless someone just grabbed the gazillion spots.  Let me see. So we were still, to my knowledge, we were 13 spots away. So if you got a spot, we were 12 spots away. So I am thinking that Nick took out 7 more spots and created 2 more fillers then. Yeah, we have our Christmas party tomorrow guys. A little employee Christmas party here. So I think I am planning to come live a little earlier than normal. Like around 12 maybe, maybe earlier. But for sure by 12. So yeah, we will be live probably until about 5 or so. Then we will go off air for a couple of hours, do our little Christmas party. And like I said, if it is still people wanting to break, our breaks are super super close. I am going to come back on for another couple of hours and probably stream until like 10 or 11. So tomorrow we will be a little on, a little off and then go back on if there is breaks that are really close we can break them. Alright, so there you go. Anthony Davis to start off. I will take a look Tyler, but that is what I am thinking because I make sure in my list how many we need to sell and how many we don't. But yeah, like I said, we can potentially get it done tonight. Hopefully that would be great. DeMar DeRozan, 26 out of 99. Also sorry that Lakers R&B is 47, so spot 7 going to Nicholas. And then DeMar DeRozan spurs Brad Bauer. Ooh, how about a little Zion Relic. 9 out of 99. Zion Relic. Zion Pelicans. Demetrius is bottom straight up. We have a little Lonzo Trier, 71 out of 75 for the Knicks. Winner Danny Connell. I am down with it. Well, that is actually a really close break too. That is like down to 8. We should try to get that done at least. We have a little Hidu Turkulu, 3 out of 75 for the Orlando Magic. And we have a redemption for the last one guys. Let's see what this is. Dual autographs, alright. Ooh, maybe a randomizer, who knows. Card number 45, Sean Bradley and Taco Fall. Alright, so I know that's Celtics. Are we talking Old School Sean Bradley? 76 to Sean Bradley, that's card number 45. So that would be out of 49 in the Dual autographs. So that would be between the 76ers and the Boston Celtics. So Celtics would be R&B. So if the Celtics win the randomizer, that would be going to spot 0 and Gary. If the 76ers win, then that would be going to Ryan. And the 76ers. So look at that right here. You guys are in the last box. Good luck. Still no huge rookie patch autograph either. No jaw. No Rui. No nothing yet. Come on man. Let's go. Hope we finish with a monster. We gotsta. We gotsta. Alright, we have a 9 out of 25 for the Lakers. Spot 9. Anthony Davis, winner J. We got a little Kyle Guy from the Sacramento Kings. 58 out of 99. Sacramento Kings are going to sew in. We got a little Kendrick Nunn Relic. 29 out of 99. Miami Heat. R&B. 29. Spot 9 going to J. We got a little Troy Brown Jr. 8 out of 10. 8 out of 10. The district. Randy with the Wizards. We got a little Arfini Simons for the Blazers. 68 out of 75. Portland Trailblazer is going to Gavin. Alright, we did end it with a nice monster. How about a little Acetate rookie patch autograph. 2 out of 25. Jammer act. 2 out of 25. That's going to be going to the random number block. And so men with spot 2, which is last spot mojo. The mojo. The mojo strikes. Right? I'm not blind. Spot 2. Yes. So men last spot mojo. Yes. There you go. Very nice. Alright, well that definitely does help out the case, but I think besides that big monster, I think this was the most beautiful one by far. This one-on-one tongue. That's pretty cool. Shoe tongue. Sneak peak. A little Hakim the dream. It's pretty nice. It's jammering, of course. Makes it so much nicer. Alrighty guys. So there you go. Sean Bradley, Sixers. Togglefall. Celtics. Let's see if we can get a customer of their first hit or potentially their second hit. Here's a dice roller. Here's a list. So we got 76ers. Celtics. That was nice. Roll it. And we got it three-on-one four times. Four times. Good luck. One. Two. Three. Four. Going to the 76ers. And there you go, Ryan. Not a sixer to be found. You're going to get a dual autograph of the two tallest player in NBA history right here. Besides Yaman I guess. There you go guys. Appreciate it. JaspysCaseBricks.com


Hi, everyone. Welcome to the UK data service workshop on data management basics. It is the second session. The first one was about or data management and my colleague and has done that. You can access the slides on that on our website under the events page and to the YouTube recording on our YouTube channel. So this session is about ethical and legal issues in data sharing. My name is Hina and I work as a senior research data officer. We are based at the University of Essex. My colleague Gail is also here today facilitating with the session. So this session includes presentation and you will get the slides after the session. As I said, I'll be using Mentimeter throughout the session which can be accessed on this link or using the QR code. You can use the Mentimeter on your mobile as well. So before I begin, please just a few couple of questions on Mentimeter. So just a couple of questions related to your background on Mentimeter. So you can see that people from diverse backgrounds, which is fantastic. There are some responses that that's great. And then another question. Is there any specific aspect of ethics and legal compliance that you are particularly interested in? So this question will help me to design this workshop for the next time if I miss something. Animal subjects, general overview. How can we share data, how to protect data, copyright and AI? Copyright and AI is an interesting one. And I think the most important topic these days. So that's good. I'm also interested in reading something about copyright and AI. So if someone all new to this, NHS data, how to best advise researchers who are new to compliance, consent, anonymization. So I will try to cover some of the information in today's workshop. But I'm running a complete workshop on consent in data sharing on 30th of November. You can find the link to register on our events page. And my colleague, I think they are running it. Running a workshop on anonymization, qualitative and quantitative both in the coming weeks. And you can check it on again on our events page. I'm running a workshop on copyright issues in secondary data use. It's in somewhere in November. And my colleague, Hannah, she's running a workshop on copyright and publishing. It's again in November. And there are many more workshops coming up in our autumn training series and all the links to register on our events page. You can check and register there. Yeah. So thank you for your responses, a lot of content that you are interested in. Thank you for your responses on the mentee. Overall aim of this session is to show you the key considerations in primary and secondary data sharing. The first section focuses on the key principles of ethical research set out by the ESRC. And it is then followed by the next section on legal frameworks that govern research data. We will also be covering the role of consent in research when it comes to data sharing. And finally, I will talk you through to the key considerations in secondary data use. And as I said, I will answer your questions in the end. So I know it is a lot of content to take in, but hopefully by the end of today's session you will be able to identify key principles for ethical research. And I'm sure you know these already, but just as a refresher, some people are new to this area. So that that would be helpful for them. However, I do hope that you will understand the legal frameworks that govern research data and understand the role of consent in research beyond asking participants for research participation and specifically in the context of data sharing for future use. And you will also understand the key considerations when using secondary data, especially in the context of copyright, but not I haven't covered the AI and copyright in this workshop. So as you may be aware that research data is of two types, primary data and secondary data. Primary data is data that is collected by a researcher directly from the original source through experiments, surveys, interviews, observations of focus groups. On the other hand, secondary data is an existing data gathered from studies. Surveys or experiments that have been run by other people or for other research, such as existing data sets that archives, essays, reviews or social media. So in the first section, which is related to primary data, I will briefly discuss the key principles of research ethics. And I'll also talk you through to some of the ethical considerations and best practices in data sharing, including some research ethic self assessment resources. So ethic issues are most likely to arise around privacy, equality, diversity and health and safety. And research ethics govern the standards of conduct for scientific researchers. So it is important to work to ethical principles in order to protect the dignity rights and welfare of research participants. So ESRC has set out key principles for ethical research. And according to these principles, researchers should ensure that their research is beneficial to participants. And they should be realistic about the benefits that it is likely to deliver. And research should be designed and conducted in a way that respects the rights, interest, values, dignity and autonomy if possible of participants, groups or communities. And researchers should inform participants that they have a right to refuse to participate and it should be free of consequences. And they can withdraw from the research for any reason. Integrity demands that there is a clear fit between what researchers say they will do and how they will conduct their research. And transparency means being clear about the nature of the research and communicating this to those involved. Researchers must exercise self critical responsibility in the planning and conduct of their research. And research ethics committees and research organizations have a responsibility to guide and support researchers, especially when the research involves difficult ethical decisions. And researchers should maintain the independence of their research and their conflict of interest cannot be avoided. It should be made explicit. And independence of research is founded on academic credentials, professional standards, expertise and experience. And it should always be free from personal, organizational and political bias dishonesty and considerations of being should be provided at all times. So these are some of the ethical principles and I'm sure that everyone is aware of this. So it is important that researchers do not just consider what can be done with the data method expertise and technology available to them. It is equally important that researchers consider what should be done. So National statisticians data ethics advisory committee provide a framework to help all researchers to think about the ethics of their research at an early stage and give them confidence that their plans address ethical principles and practices. So they have designed a very useful ethics self assessment tool to review the ethics of the project to be undertaken. And this tool enables researchers to identify and mitigate any ethical issues. So it is based on six main principles you're asked to assess your project against 22 items group against these six ethical principles on a scale. And it is beyond the scope of this session to go into further details of this tool. But I have added a link on the slide for you to have a look into your own time. And I found it very, very helpful. So that's quite a useful tool. Then there is another useful resource called data ethics framework by the UK government. I have added a link on the slide. This is a very nice framework. It provides guidance on the appropriate and responsible data using government and the wider public sector. And it helps to understand ethical considerations, address these considerations within the projects. I want to show you this tool. And so I'll add it the link in the chat at the end, or we can go through this tool at the end at the moment. I just, but it is a very, you can Google it. It's called data ethics framework. And it is, I think it has some overarching principles like transparency, accountability, and it outlines specific actions that covers the entire process of a project. And each section includes questions that will guide you through ethical considerations for your project. And it is very, very useful. So I'll go through it in the end if we have time. Otherwise you can just Google and you can find that out that that's quite useful. So some of the best practices are that that ethical obligations should be considered throughout the research life cycle from panning and research design stage to the data collection stage and all the way to the future uses. That includes publications, archiving, sharing and linking of data. And it is essential to have a knowledge about the standards and requirements of the relevant research organization. So always comply with these relevant laws, avoid social and personal harm. And you can always check with data centers such as us as we facilitate ethical and legal reuse of the research data, including the protection of participants and safeguarding of personal data. So the second section is all about legal frameworks that govern research data. But before we start on this, just a quick question on mentee about what type of data you are familiar with and tend to use or are using. So health data, quantitative, qualitative, administrative. Again, a very diverse types of data you are working with. That's interesting. Radiology reports, primary data, anyone working with secondary data? I see a response just okay. Education, migrant, migrant data would be interesting. Animal data as well. DNA sequencing. So very interesting types of data you all are working. I could see the tab on my laptop regarding that framework I was just talking about. Let me just click and show you. Can you see? Okay. I think you can. Yeah. Yeah. So this is the framework I was telling you about. This is a guide. I have added it on the slide. So some basic information, what is it for? Who is it for? How to use it in the structure of this framework? Then they addresses these three overarching principles, transparency, accountability and fairness and what specific actions you need to take. That addresses these principles. Then one by one they describe what transparency is and how to score that accountability, how to score that fairness. Then all these principles, again, what specific actions you need to take. And yeah, it is a very nice one. How do you understand what public benefit is? So how to score that? What specific actions you need to take? So yeah, I found it very, very useful. So you can have a look in your spare time. So thank you for your responses coming back to the legal frameworks. In the context of data sharing, I think it would be easier to talk you through about the legal frameworks governing research data. If I take a broader classification of research data by health research authority, it's easier to explain in that way. Although it is by health research authority, but I think it's applicable to all types of data. So according to the HRA, health research authority, data or information is broadly classified into three main categories. Information that relates to identified or identifiable individuals. Information that no longer relates to identified or identifiable individuals with some referred to as anonymous data and synthetic data. I go through each of these briefly and the legal frameworks governing. So the first type is health and care information that relates to identified or identifiable individuals. But before that, just a quick intro to the personal information or data. You can identify an individual through personal information about that person and people can be directly identified or indirectly identified. Examples of direct identifiers are name, address, postcode, telephone number, voice, picture. And some of the examples of indirect identifiers are occupation, geography, unique or exceptional values which we in data terms we call outliers, which when combined can identify a person. So personal data also includes special category data that needs more protection because it is sensitive. As I said, the UK GDPR defines special category data as personal data revealing racial or ethnic origin, political opinion, religious or philosophical beliefs, trade union memberships or genetic data, biometric data, data concerning health and sexual orientation. And most health researchers use special categories of personal data, which includes biometric data, genetic data and so on. And if personal information about people is collected or used in research data, protection regulation applies. So there are two main legal frameworks governing the use of research data or health data that relates to identified or identifiable individuals. And these two frameworks are the common law or duty of government. And these two frameworks are the common law or duty of government. In the UK, there is a duty of confidentiality that is based in common law. And that occurs where confidential information comes to the knowledge of a person in circumventing the use of research data or health data that relates to identified or identifiable individuals. In these two frameworks are the common law or duty of confidentiality and data protection legislation. So there are two factors where confidential information comes to the knowledge of a person in circumstances where it would be unfair if it were then to be disclosed to others. There are some exceptions when you can disclose information. For example, if participant consents to onward sharing of their personal data, then sharing does not breach duty of confidentiality. And under this common law, you will need to obtain an explicit consent if confidential information is used for a research project. And this explicit consent is a very clear and specific statement. It can be given in writing verbally or through another form of communication, such as sign language. And sometimes public interest can override duty of confidentiality. And occasionally there are instances when you may need to give up data such as on a court order. So the best practice is to avoid very specific promises in consents. As researchers, we must adhere to data protection requirements when managing or sharing personal data. So if personal information about people is collected or used in research, then the data protection regulation applies. Data protection legislations that are most widely applicable to the research are Data Protection Act and GDPR, which is EU GDPR, which is now called the UK GDPR. EU GDPR is the EU White Data Protection Regulation that was introduced in 2018, and it replaced the UK Data Protection Act at that time, which was being used until then. However, since the UK left EU, it is now called the UK GDPR. Currently, UK GDPR and EU GDPR, they both are aligned. They place the same legal obligations on researchers, but in the future they may diverge. It will therefore be important for researchers to ensure that they gain local support from their university DPO when their research project will span across the EU. So basically, if the researchers based in the UK collects personal data about people anywhere in the world or a researcher outside the UK collects personal data on UK citizens, then Data Protection Act and the UK GDPR applies. However, if the researchers are undertaking research projects which span across the EU, then EU GDPR also to be considered. So this is the basic rule at the moment. UK GDPR specifies the rights a data subject has when their personal data are processed. That's why it's very important to consider UK GDPR if you are to collect personal information for your projects. And according to this, individuals have the right to be informed about the collection and use of their personal data. They have a right to access the information you hold and they can request a change in the information. Ask for a ratio object or ask to restrict processing. They can also object in terms of data portability or transfers to outside the UK and any sort of decision making. They can do that. And which of these rights will be relevant to processing personal data for your research project will depend on the nature of the project. And the chosen processing ground in which country the research is taking place is another important aspect to consider. But GDPR has given these rights to the participants. And everyone responsible for using personal data has to follow certain strict rules called data protection principles. And the researchers must make sure the information is used fairly, lawfully and transparently. And it should always be used for specified explicit purposes. It should be used in a way that is adequate, relevant and limited to only what is necessary. And information should be accurate and where necessary, kept up to date and not kept longer than it is necessary. So most of all, it should be handled in a way that ensures appropriate security, including protection against unlawful or unauthorized processing, access, laws, destruction or any sort of damage. So these are the principles that the researchers should ensure they are there for the week. Under the UK GDPR, there are six possible in crowns for processing personal data and one of these must be present. And if you are to process personal data, these are consent, public interest, legitimate interest, protection of vital interest, legal obligation or a performance of a contract. But in the context of research, the first three crowns which are consent, public task or legitimate interest are the most applicable crowns for the processing of personal data. I'm not sure whether any one of you are familiar with these crowns or what crowns you are using for your products. So I just thought to add a question on a mentee, just a quick question if you can let me know which legal basis you are using. Either you are using or you are from, you know that in the UK, which legal basis advisability to use as an academic consent. That's interesting. So I think it depends the type of data you are working with. If you are working with the health data, I will go through this in the coming slides. Yeah, if it is health data, then yes, consent and public task. So majority of you have that consent so far. So some responses in the chat as well, consent. When I was doing my PhD, I also thought my PhD was on health research. Yeah, so I considered that consent is the only base that we need to use to collect personal data. So, okay, thank you. Let's go back. So, yeah, some of you might surprise if you are not from health research background. Those who have asked for consent as a legal base, which is advisable to use in the UK and they are from health, that's fine. Otherwise, Information Commissioner's Office advised that for almost all research conducted in the UK organizations should rely on either public tasks. For public bodies such as NHS, universities, UKRI or legitimate interest for non-public bodies such as charities and commercial companies. So they advised to use public task for public bodies and legitimate interest base for non-public bodies and you see that it's not consent. So that might be surprising for some of you. However, those holding and using health information, which is a special category of personal data in the GDPR, and it also require a further condition in addition to the public task. So, in academia, this is usually to support scientific and historical research. We use it as an additional basis in academia, which is called scientific and historical research. But in the health research, you can, you have to use an explicit consent. So for health researchers is consent plus public task and for academia, public task plus scientific and historical research. So these are the two basis or mainly ICO recommendation is to use public task. And most, almost all the universities in the UK, they use public task as the legal base to process personal data. So, but for the health research, you also need to complete a data protection impact assessment for any type of processing, which is likely to be high risk. So you must therefore be aware of the risk of processing the special category data. So there, there is a misconception that data protection laws such as GDPR prohibits data sharing, however, it does not prevent data sharing as long as you approach it in a sensible and appropriate way. GDPR is useful for research because it legalizes much of the current good practice in search placing people at the center. It offers enhanced rights to individuals whose data is being processed. And in the context of research, GDPR has the potential to further benefit research and archiving, helping to improve trust and confidence between the public and universities and between researchers and their participants. So this section until now was about the data that can be identified or identifiable. So the second type that I spoke earlier was about the data that no longer relates to identified or identifiable individuals. So this is a data that has been anonymized or pseudonymized. Personal data that has undergone effective anonymization is not, however, regarded as personal data. And therefore it is not subject to the UK GDPR. This is because the data has been modified and transferred or otherwise made available to another organizations that such that it no longer relates to an identified or identifiable individual. So there are several anonymization techniques that can be used to do that. For example, aggregating, suppression, rounding, reduction, addition of oil and so on. But it is beyond the scope of today's session to talk. However, I have added links at the bottom of the slide for you to have a look later. And as I said, my colleague will be running a workshop on anonymization in the coming week. So you can join that if you need more information. So data that is treated in this way is no longer considered confidential. And generally speaking, does not fall within data protection laws. It is important to note that even when health data is anonymized, it may still be possible to find ways of identifying your individual personal information when combined, how combined different pieces of information. So however, it would likely require special circumstances or efforts. And this effort may involve using other sources of information to narrow down the number of individuals that the data may be relating to. But there is some debate about this. On the other hand, pseudonymization is a security enhancing process that replaces or removes information in a data set that directly identifies an individual. And it is typically applied before information is shared with a third party. For example, it could involve replacing an NHS number, a name or an address with a unique number or code. With the effect that identifying an individual directly from that data is not possible by the recipient without additional information such as a key that would enable matching the pseudonym to direct identifiers in the data set or any other means to re-identify the data. So personal data that has undergone pseudonymization but could still be attributed to an identifier individual by the use of the data alone or in combination with the other data likely to be available is legally presumed to remain personal data under the UK GDPR. While personal data that has undergone pseudonymization, but that is no longer attributable to an identified individual is not considered personal data. For example, if an organization pseudonymizes data and holds the key, that data remains personal data to that organization. If the same organization shares the pseudonymized data with another organization such as us, they deposit the data with us, but they does not share the key with us. It should not be assumed that the data is personal to us. So GDPR doesn't apply on that. For them it is under GDPR for us without the key it is not. So the determining factor is not whether or not the data is pseudonymized, but whether or not it can be used on its own or in conjunction with other available data using reasonable means to identify an individual. So the third type I mentioned earlier was the synthetic data. It is the information that is artificially created rather than generated by real world events. It can simulate synthetic populations that resemble the characteristics as well as diversity of actual people. And it can also be generated to be statistically consistent with the real data set, which it may then replace or augment. So as synthetic data is neither personal nor confidential, it is not subject to data protection legislation or common law or duty of confidentiality. So the third section is about control of consent in research. I'm sure you are all familiar with what informed consent is. However, when it comes to data sharing, then consent is used for two purposes to fulfill ethical obligations and to be legally compliant. We all are familiar with what consent is when which is used for research participation. And it is considered as one of the founding principles of research ethics where it is sought before participation in any research activity and for all participants. And it usually involves providing information regarding study purpose, risk, benefits, voluntary participation, how they can withdraw and so on. However, as stated earlier, consent can be used as one of the legal basis of processing personal data under the UK GDPR. If a researcher collects, manages and shares personal data, then consent of the data subject can be used as a legal base. As I said, to process this personal information. But as we see that in the UK, it is rarely used as a legal base, but around the world, there are many countries that use it as a legal base. So, but even though it is not mandatory under the UK GDPR, but you need to obtain an explicit consent under common law or duty of confidentiality when you have to disclose or share confidential information for research purposes. For example, under Human Dissue Act and for clinical trial purposes, you have to obtain that. And ethically, you should obtain consent informing the participants if you are to share this data for future use, not legally, but ethically you should. So, therefore, consent plays a vital role to be ethically or legally if you are using it as a legal base to obtain it when it comes to being transparent, fair and maintaining confidentiality. Consent can be gained in written or ordered form and the format of the consent depends on the kind of search, however, it is important that whatever format is used, written or verbal, it should be documented. And you need to document how it has been gained, what information has been provided and what they have, what the participants have agreed to, what information they agreed to at that moment. So, consent form plays a vital role in data sharing when you are to archive it or deposit it for future use. And it is very important that you design the consent form keeping in mind these three important sections. If you can to share your data, the first section should be about taking part in the study and it includes some basics such as participants have read and understood the information. They have been given the opportunity to ask questions, they understand that they can withdraw anytime. And the second section is all about how the information that is being collected will be used. For example, how the data will be stored for how long, how the confidentiality will be maintained. And the final section should be around providing information about future uses of the data such as publications, archiving data and so on. And this final section in the consent form is really important if you plan to share your data for future use by other researchers. As I said earlier, I'm running a full workshop on consent issues in data sharing on 30th of November, I think. So you can have more information in that workshop. And we have a model consent form on our website. I think I have added it on the last resource slide as well. You can see that how you divide the consent form in three key areas and what each area should include in the consent form. So that's quite useful. So when you start a research project that involves collecting information from people, for example, via survey or interview, focus group or whatever way, then these questions can help you to comply with data protection legislation in practice. The first consideration should be whether the project needs to collect information that would be defined as personal data. If not, then do not collect it. If the research does not collect personal data, then data protection legislation will not apply. If personal data are being collected, the researcher needs to identify who will be the data controller for the collection, storage and handling of the data. This is unlikely to be the researcher themselves. And in most instances will be the researchers, universities or institutes where they are working. So if the research involved collaborations of different partners, it will be important to identify whether they will be joint controllers of the data or data processors. It will be crucial to ensure data sharing agreements are in place and where necessarily a processing or processor controller agreement should also be in place. The data controller is the person who determines the purpose for which and the way in which personal data is processed. By contrast, a data processor is anyone who processes personal data on behalf of the data controller. For example, if you deposit data with us, you are the controller and we are the processor who process data on your behalf. So an assessment will need to be made about the most appropriate processing ground to use for each research projects. And you are familiar by now that there are three grounds that appear most applicable for research, consent, public task or legitimate interest. And if you are using consent as the processing ground, it is crucial that this is distinguished from consent for other ethical and legal purposes. And that participants can withdraw their consent for processing personal data. This is different from the right to withdraw from the research. So you need to make it explicit in your forms. So if public task is used as the processing ground, you must ensure that your university or institute is classified as a public authority. So that's another important point. In the UK, universities are the public authorities. So I'm talking about outside the UK. So and also that research will be in the public interest. So if you are using legitimate interest as a processing ground, a legitimate interest assessment should be undertaken. This will need to identify the legitimate interest being pursued, demonstrating that personal data processed is necessary to achieve this. And this is being balanced with the rights and freedoms of the participants. So the information that needs communicating will be influenced by which processing ground is chosen. Broadly, participants should be informed about how any personal data collected about them will be used, stored, processed, transferred. The data controller is and their contact details, the legal ground and purpose of the processing, any recipients of the personal data, period of retention and their rights and so on. So remember, despite all the info I have gone through, bear in mind that much research data, even sensitive data, can be shared ethically and legally if researchers employ certain strategies. For example, offering protection of identities through anonymization or a de-identification using processing ground for personal data and finally regulating access where needed. So you can deposit any data by using strategies. The last one I said was you can regulate access to the data if it is sensitive. So I have added on this slide what I meant by regulating access. By regulating access, I meant that facilitating data sharing especially when it is not possible to anonymize data or to obtain consent for data sharing. So in that case, you can restrict user access. For example, here at the UKDS, we facilitated three levels of access for data. Open access for data that contain no personal information, safeguarded access for data that contain no personal information, but the data owner considers a risk of disclosure resulting from the linkage to other data or by combining several pieces of information. So it is available under end user license and users need to register to access data. Users also need to agree to certain conditions such as not to disclose any identifying information and while the third one controlled access is for the data that may be disclosive. Control data are only available to users who have been trained and accredited and their data usage has been approved by the relevant data access committee and access to this data is through a virtual or physical secure environment. So this is the final section which is about what needs to be considered if you are planning to use secondary data sources. Most important issues are the rights inherent in secondary data. So two most relevant types of rights applicable to the secondary data sources are copyrights and database rights. I'll talk you through to the copyright which is the most common one due to time constraint and I have added a link at the bottom for other rights for you to have a look. So copyright or IP rights are assigned automatically to the creator or the researcher who owns the data. When data are shared or archived the original owner retains the right data archive cannot archive data unless all right holders are identified and give permission for their data to be shared. So copyright applies as soon as the data is created you are the copyright owner of the data that you share for the future use by other researchers. And in the context of primary data if you plan to share it for future use you need to consider how you want your data to be used be used by other researchers or students you can specify this by licensing the data to match the intended uses. Various types of licenses for sharing data have been developed by the data archives. As I showed you earlier the licenses we use a data service. You can get a service open access they've got it and controlled ones and and use the license. In the UK copyright arises automatically once a work is created and to enjoy copyright protection the work must be original. That is to say it must be your own book not copied from someone else there is no copyright in ideas or facts only in the way those ideas are expressed such as diagrams and tables. More information if you need more information and are interested in copyright and data use as I said I will be running a workshop next month. And if you're interested in copyright in publishing then there is another workshop in November by my colleague. So if you are using secondary sources then best practices to assess who the copyright holder of the data set is are you allowed to use them. And in what way are you allowed to archive and publish the data in a data repository. Most of the time we encounter problems when researchers are allowed to use data as the data is under open license or they register to use it. But what they do not realize is that it is accessible to them for their personal use but they need permission from the data owner for sharing it or archiving it. So you may need to seek further permission to distribute material you do not own. If permission is not granted you need to remove copyright variables or material before publishing or sharing it. So to be here on this slide I have added a link to our web pages on copyright. I have also added a useful template variable information log for data sets being deposited that includes secondary data sources. Researchers are advised to prepare a variable information log describing these resources. This log not only allows others to understand and use data correctly but also ensures that respositories can check the appropriate terms and conditions applicable to the onward sharing. So you can see here that I'm not sure whether it's clear or not but it include the variable name source how it was collected brief description and any restriction noted on its further use. So it's useful for the secondary data users. So best practices to always investigate which laws apply to your data including cross country collaborative working as early as possible almost at the designing stage of your project. Do not collect or keep personal or sensitive data if not essential to your research but can always seek advice from the research office or data centers like us and make sure that your participants know how this data will be used. All research data are personal data. Just remember that research data is not personal data and GDPR does not apply if it is anonymized data. Not all research data is personal. I'm not sure whether we have enough time for you quick questions or not. Yeah, I think so. On the Mentimeter. Quick quiz if you are. What do you think just it will just recap of what you have heard. I know it's a lot of content but just quick quiz. What do you think pseudonymized data is not subject to the UK GDPR. Is it true or it depends. Majority of states are false. Some say it depends. And someone says it's true. Yeah, I think it's them. It depends as well as you can say that it's false as long as the key to identify the data is held by someone else. Then it's not so don't personal data. Then it's not under GDPR. For example, some organization deposited a pseudonymized data with us and we do not hold that key that helps us to identify the individual. Then it is not under the UK GDPR. But for that organization who holds the pseudonymized data as well as the key with the information. To identify that can help to identify the individuals and for that organization. Same did pseudonymized data is subject to the UK GDPR. So it depends whether you hold the key to identification or not. And what do you think with this effectively anonymized data is not subject to the UK GDPR. Yeah, that's correct. If you think you are 100% sure that the data is effectively anonymized and there is no chance of any identification or there isn't any disclosure risk, then that's right. It's not subject to the UK GDPR. A very simple one. Ethical applications should be considered throughout the research. That's that's true. Thank you for your responses. And what do you think if the researcher based in the UK collects data outside the UK UK GDPR does not apply. I think it's false because if you are based in the UK you need to abide by the UK GDPR. And if you are collecting personal data, then the UK GDPR does apply. So it's a false statement. Anywhere in the world it doesn't matter, but if you are based in the UK and you collect personal data, even if it is outside the UK UK GDPR does apply. I think that's the simple one. If there is no personal information in the data, then the data protection legislation does not apply. And then there is another one. If the researcher based in the UK collects personal data from the EU, which of the following applies. Yep, that's correct. EU GDPR and UK GDPR both applies. And this question is about the EU, but if you are collecting data anywhere in the world from the UK, then the current law in that country plus the UK GDPR both applies. So that's that's correct EU as well as the UK. And what do you think? Yeah, I think it it depends is the safe answer. It depends whether you have taken that preventive measures, whether it is ethically and legally possible to share the data or not. So it depends on number of factors what legal ground you are using what information has been provided to the participants in the consent form, whether they have agreed to share the data, whether it is possible to anonymize it, whether it is possible to put it in a controlled access environment. So that confidentiality is not compromised and people are ready to it in number of number of reasons. So it always depends, but it is possible. So what do you think informing participants about the future users of data is an ethical obligation, a legal obligation, or you're not sure. I think it's more of an ethical obligation. Yeah, there is a note. There isn't any specific law that states that if you are collecting personal information and GDPR applies, then yes, it's a legal obligation. But if you are not collecting personal information, or you are anonymizing that data. So anonymized data does not fall under the UK or EU GDPR, then it's an ethical obligation. You should inform them. So it could be, it depends on the project. So it could be an ethical, it could be a legal or it could be both. So this is a statement we encounter every now and then from the data that researchers deposited with us in the consent forms. I think, is this appropriate? If you plan to share that data, or is it, it's a funder requirement to share that data for future users. Yeah, that's false. That's not an appropriate statements because it precludes data sharing. So researchers who plan to use, who plan to deposit data in archives so that other researchers can use it. They should avoid such statements in their consent. Then there is another statement that should be avoided. It also precludes data sharing. So when people come with the data and this sort of consent form statements, the only option they have to go back to the participants ask for retrospective consent, which is not feasible at all most of the time. So, yeah, so these are very, very problematic statements if their funders require them to deposit data for future use. I'll go through these ones in my consent issues workshop. These ones and some more and then the example consent forms as well. So, another statement that we came across is all research data will be destroyed after so and so years appropriate. So, this should be, it depends if you should inform the participants what you are going to do with their information that you have collected. So this should explicitly state if you are informing them about personal data, all the research data in this statement it says all research data. So if you have this sort of statement, you cannot archive it for future use. So if you need to be explicit that some universities, they have a policy of if you are not depositing personal data, it will be kept for five years, ten years. It all depends on the organization or institute's policy and it will be destroyed. So that is fine. You separate the personal data from the research data. So always consider before using such statements and if you are planning to share your data, such statements are very problematic. So we will go through these statements in my consent workshop. I'm not sure why. Again, Steph, can you see my screen, the slides? Yeah. Yeah. All right. Yeah. So these are some of the resources I have mentioned here with the links that are useful to you, including the consent form, example consent forms, information sheet and rights when using secondary data, regulating information and so on. And these are the links to our upcoming training events page, past training events and recordings. And yeah, thank you for attending today's session.


Let's try this problem. It says Titanium dioxide the substance used as pigment in white paint is prepared industrially by reaction of titanium for chloride with oxygen at high temperature So it gives you the reaction there, and then it says how many kilograms of titanium dioxide can be prepared from 5.60 kilograms of titanium for chloride, okay so How do we figure this out? Well, we're going to have to do a number of calculations and remember a number of conversion factors, okay? so one of the conversion factors already we need to know is The conversion between kilograms and grams. Okay, do you remember that one? 1,000 Grams equals one kilogram Okay, so if you don't remember those you're gonna Make sure you don't buy the test tomorrow So five point six zero kilograms of titanium chloride, okay, so What other conversion factors are we going to need to know well let's just go through this problem and see What conversion factors only know so we're eventually looking for the mass the mass titanium Anyway, I have to start with this five point six zero kilograms of Titanium for So let's just convert that to grams so one kilogram of titanium for chloride 1,000 grams So we can cancel out kilogram Okay, so now we're in grams of titanium for chloride, but that's not what we want We want the mass in kilograms of titanium dioxide, okay, so Do we know a conversion factor that will convert grams of titanium for chloride to titanium oxide? Well, it won't you do need the molar mass, but it's not going to convert from Titanium chloride to titanium oxide It's going to convert from grams of titanium for chloride to grams of or to moles of titanium for Okay, so down here. We're going to want something that's grams of titanium for And like you said up here one mole Titanium for core so whatever that is. That's the molar mass, okay, so We've got to figure out. Well, what's the molar mass of titanium for quite so look at your other people three five point four five times plus titanium 47.8 in So that equals 189.68 grams per mole of titanium for the titanium for So we'll put that down here 189.68 It's grams per mole See that So that cancels grams out and now we have moles of titanium for four Okay, is there a mole-to-mole ratio that you can that you can figure out for titanium for chloride to titanium oxide? Do you remember what we used for that one? How to convert moles of titanium for chloride to titanium oxide? We've got to use the reaction equation here. Okay, so the coefficients of the reaction equation tell us How to do that? So how many titanium for chlorides is this this coefficient telling us we have? One, okay, so and how many titanium oxides? So in this case it's one mole to one mole So we're gonna go one mole So that's where you get that conversion factor from the reaction equation that has to be balanced Okay, so cancel cancel Is that what we're looking for moles of titanium oxide? Mass So is that mass? Okay, so how do we get from moles back to mass? How did we go from? mass to moles before So use the molar mass 32 because that's two oxygens plus 47.88 so the titanium oxides molar mass 79.88 grams per mole one mole titanium oxide 79.88 But I wanted the maths and kilograms is that kilograms? So how do we convert grams to kilograms? So how many? There's no reason to guess about this stuff, okay, we've already written all the things down and up here So now all we have to do Okay, so how many sig figs is our final answer going to be? Really? In three because that's the number that was given to us in the problem So 5.6 times 1,000 divided by 1 89.68 times 1 times 79.88 divided by 1,000 and the three sig figs I get 2.36 kilograms So that's how you would do that If you started with 5.60 kilograms and it all went to the product questions on this


If you were presented with convincing evidence that Ayesha was nine and it was enough to convince you that that was the case, would you at that point see the Prophet as doing something awful? Or would you change your view on statutory rape? I mentioned an article that was published. They mentioned that here in the United States, by example, that it's not uncommon for a girl to reach puberty at the age of eight years old. But there's a stipulation in Islam that they have to have reached the age of puberty. That's one thing. They have to also be mentally and emotionally. They have to be mature enough before any type of interaction like that can take place. Based on that, I believe that the Prophet peace people on him at whatever age she was. And I'm not conceding and saying I believe she was any particular age. I don't know. But the fact of the matter is, I believe that the character of the Prophet, I have no reason to think that he would have done anything wrong in regards to that issue. I think he would have waited until she reached the proper age mentally, emotionally, and physically as well.


Our speaker Christian Berger is an engineer of technology and he will talk about fax signalising. Hello and welcome to my presentation to the subject of long-distance copiers of group two, three. It's a subject that was quite controversial throughout the time of the Congress. In the USA there is an anti-faxer organisation who wants to work against long-distance copiers. And I want to show you some examples of fax configuration. Don't be afraid, we are not going to use the long-distance copier. A part of the usage data, fax devices also need to have some technological parameter they have to exchange, so the meter data. The easiest access to this information is on the devices itself. Many devices can print these sent information. Each sequence here is within this fax device itself. In the beginning the receiving fax device sent its ID and some information and then the sending fax sends a lot of data. We send a lot of binary zeros to verify the connection. Then we send information, then we send data and all the information the page is over. The receiving fax acknowledges the reception of the page and the sending says goodbye. The signalising data are modulated according to one type format. We change the zeros and ones to different tones. Then we have a modulation on top of that. We have the stream of top and the bits below. HDL allows us to send data on a synchronous channel. On a synchronous channel we always transmit all the bits at one unit of time, always the same number of bits, whether we have any content or not. In the time when no data needs to be transmitted we send a flag sequence. This sequence is zero, six ones and once more zero. We always repeat it and transmit it repeatedly if there are no usage data. If we have data we need to transmit and they have different zero and one bits. To differentiate them from the flag bits, every five ones we add another bit. It's always zero and allows us to check whether it's a number of ones behind each other or a flag sequence. The beginning there's always a header and a 16-bit checksum. The header contains an address field, eight bits, usually all bits one, a few use facts and a control field. The control field contains about what type of message is transmitted and whether that message is the last message in the sequence. Within the frame all data are sent with their additional bits to ensure not enough too many ones are there. There are no start and stop bits because we have the flags to differentiate between the frames. This example shows the most simple case. We just sent all the data, the receipt is confirmed and the connection is closed. If there are bit errors in this case they lead to image errors. They are sometimes detected in the receiving fax because we do not, if the length of a line is wrong, but we can't request further lines. The received fax can only, if there are too many wrong lines, the connection can be closed. To be able to send fax over bad lines we are able to use ECM. The image data is put into HDLC frames and they have a checksum and at the end the receiving fax can request the sending fax to recent invalid blocks and that is repeated. So long until all pages are received correctly. There are also further information like fax, color fax or voice data. That means it's hard to hide errors in these other methods so it's important that the connection is correct and ECM makes sure that there are no unknown errors. That also means both fax devices need to have the memory in memory and in the 80s that would have been much the expensive. Nowadays in Voice of IP there are additional problems for the fax. So voice of IP protocols like ZIP transport the data using RTP. That means the data is taken into 20 millisecond long chunks and they are put in a UDP package with a header and this package is then transmitted. The receiver receives all these packages and packs them, writes them into a buffer and then returned into audio data, to an audio signal. However what are 20 milliseconds? Quars or oscillators have the issue that they have a different speed. So 20 milliseconds for one receiver might be slightly different than 20 milliseconds at the center side. That means that it's the issue that the data is received and sent at different speeds. That means that it's possible that the waiting buffer is too full or too empty. So additional data needs to be added or removed. That has an illegible effect and you can even optimize it in such a way that the gaps only happen when there is no speaking. However modems and especially with the long distance copier we have a long time where a modem is talking and modems have an issue when there are short losses of information. They need to be synchronized with all the data and if data is lost the modem is not synchronized with the sending modem. That leads to a lot of bit errors which lead in some cases to a loss of the connection. To reduce the issue T83 was developed. The idea behind T83 is that we circumvent the modem. We try to connect the computer of one fax device to the computer of the other fax device. That leads to the circumvention of the modem issues. Another situation is that less data needs to be transmitted. We do not need a full data connection but only need to transmit the used data. In addition we can even add redundant data just in case a package is lost. Wireshark is able to decode T80 data. And here you can see how the signal data is transmitted. Because signal data is with 300 bits per second every single octet is transmitted. That also reduces the latency that might be included because fax is real time fax.  Otherwise it's like any other fax data. We also see the zeros that are connected to verify the connection. We did that implemented because we have T83 gate base that should be implemented to ensure that only one side talks T83 and the other one T30 the old standard. The initial idea was that fax devices in the future are able to speak voice of IP addresses and are able to be connected to the internet. The communication with older fax devices would be used through a digital modem in the devices or through T83 gateways. Unfortunately there are very few internet aware fax devices. So apart from some fax servers there are very few devices that speak IP directly. There are also further fax devices. For example the German weather service sends weather fax through short wave. Also the fax device in the space lab is probably not a group 3 fax. That is my short introduction in the signal information in group 3 long distance copier. I hope you enjoyed it. Use the power of the tether fax. You will see what is possible with these communicative secret weapon. Thank you very much for your attention also from the translation booth from me Franz T. If you have feedback use the hashtag C3Lingo. I hope everybody else learned as much as we did today. Okay back to the questions. Because we don't want to go too far over the 40t to minute. Why are they T83 over VoIP? Why was that specified? Because T83 over SMTP was already specified. Do we want to have real time fax? It means the moment when it scanned the sender prints it already or do we want to have something similar to email where we basically send an image via email. It is the disadvantage that we can't be sure that the fax was received. I do not know whether there is a sender recognition exchange in appropriate manner. However it is not used. A large issue is all the practical implementation because we have a physical fax device that is in some company already and T37 we would need very extensive methods. We would need to save the document before sending it. This is the smaller variant T83. Part of that is what do I do if I have a fax with 300 dpi but the other side just says 200 dpi and we had to calculate the difference. There are fax to mail implementations but they are completely different issues. There are advantages and disadvantages. The next question. What about group 4? What is group 3? Where are the other groups? I have never heard anything about group 1 or 2 fax machines. Group 4 is through ESDN but they are very rare. A group 4 fax wants to be connected to ESDN directly and then we have a transparent 64 bit data channel and would be a lot quicker and would suddenly have a lot of special features like text transmission or arbitrary file transmission. There are digital group 3 faxes, a couple analog fax devices that they still scan the image line by line and then the printer prints it in real time however. We are not talking about pixel or there is no data compression and that is used by the Deutsche Wetterdienst, the German weather service for weather fax. Another question. What is weather fax? Oh yeah, weather fax. The idea is very simple. We have for example ships on the sea and they want to know how the weather is going to be because if they are streaming ahead it is very important. You can call them up but the weather map is much more handy. So the Deutsche Wetterdienst has a short wave sender and it sends the weather maps all over the world and you can get a nice image of how the weather is going to be. Cool. The next question. How can I have a GPG-appropriate fax encryption? How does fax 3 encryption work and how does the key exchange work? That's an interesting question. It's defined in T4. There is a definition I have not looked into it yet because I do not believe that there is a fax device that supports this but hypothetically we have fax encryption. What group of devices? The Fritzbox. Fritzbox itself has many functions. It's also a router but it supports fax group of group 3. I do not know whether it might support fax group 4 but hypothetically we could also send group 4 fax via transparent data through voice of IP however usually it operates like a group 3 fax or as a 38A if you activate 38. When can we use T38? It needs to happen. Is it dependent of the provider or fax device or router? That depends on a lot of specific locations. Ideally T38 is from one end to the other end and we have a voice of IP connection between those two and in addition we need to be codec transparent. That means if one device requests T38 that needs to be transparently connected to the second device and that needs to be answered that it is transmitted appropriately. There are service providers that do not offer this and there is an asterisk in between and that does not transmit the request. You can then turn T38 back to normal voice data but there is always some loss and that leads to faxes arriving with a reduced probability. So hypothetically it should work if you have two Fritz boxes at a German telecom and the T38 connection should reach through. Among provider it is even more questionable. Perhaps there are other connections where T38 definitely does not work. And then there are two more questions. First of all where can I find the T4? T4 is available on a home page on a website but I don't know the website. If you look IUT-E and then T.4 you should find the specification or search for T.30 and you will find the fax standard and there is a list with all the T standards and you just click on them and get the PDF. And then are there details to T38 on the Fritz box? You know some details about it. It's a question what details are interesting about it. I happen to know that the Fritz box actually don't support one specific modem standard. It's a bug in the Fritz box and it's already reported and so far it just wasn't fixed. And it's V17 with 4,000 bits per second. It's a rare standard but the Fritz box does not support this standard therefore transmission to this data standards are not possible. But I don't know further details. It works quite well with the Fritz box. The Fritz box is a German router manufacturer AVM is the name of the modem. Thank you very much. Perhaps you led to one or the other person being more interested into faxing. Thank you for having me here.


Hello, Complexity Weekend, September 23 to 25, 2022, cohort. This video is going to be a cohort participation overview. It's going to cover all the details about how you participate in the pre-weekend and how you participate in the weekend itself. First, just some notes on this document that we'll be going through. This is the CODA document that's being used as our single source of truth for the weekend. It's an updateable document format, and just a few quick tips on CODA before we go through the material. First, the login for CODA, which will enable you to edit certain pages, is the same email address that is getting all the other communication emails and calendar events from us. Second, if you go up in the top right, you can switch between the dark and the light mode. So this is what the light mode looks like, and you can switch into the dark mode if you'd like. And third, if you use control and plus and minus or control and scroll, you can change the size of the font. You can also hide the sidebar if you want, and these features help make CODA really usable, and it's an awesome platform. Hopefully we'll see some of its cool features as we go through today. Also, just note that this is a document in progress and a complex system, as all systems are. So it might look slightly different, and it's going to be incorporating all your feedback as we go through the process together. So I'm starting on the welcome and how to participate page. The top part of this page provides some opportunities for you to provide feedback. You can email us at complexityweekend.gmail.com. You can click on this link to utilize an anonymous feedback form. Or you can use the comment feature in CODA, which is accomplished by selecting text and then hitting the comment button. Then the comment's visible and we'll make sure to address it. Here's how you participate in complexity weekend. During September, you'll participate in the pre-weekend program, which we'll go to soon. And during September 23 to 25, during the weekend, you'll participate in the weekend program of activities itself. And for all pre-weekend and weekend activities, it's absolutely join and leave when and how works for you. We aim to provide programs for both the pre-weekend and the weekend that are accessible to all time zones. So please join when works and don't worry about it when you can't join. It's not expected or required of anyone. Here, you'll see registration information. This is some text that you can copy and send to a friend. And this is how you register. If you're seeing this video, you've probably already registered. But the way to register is to go to the complexity weekend website and then sign in. And on the user portal, the first question asks if you'd like to participate in the weekend. Just select yes and you'll be auto registered to participate. And a little bit lower on the page, on the first page is a directory that helps navigate amongst these different pages. So let's go through those pages. This page here is about complexity weekend. At the top of the page, there are some different links that you might want to follow, like joining our mailing list where we announce updates and opportunities, checking out our YouTube page where you can see different videos and live streams from the past, going to the events calendar or supporting complexity weekend financially. And this page also has some overview information on complexity weekend. Additionally, on the top page, learn more about complexity weekend overall here. That will link you to the public complexity weekend page. And on this page, there are more links from complexity weekend. There's information on events. And then under about and more information, you'll see the values which you can scroll through. These were generated collectively as a community over the past year or so. You'll also see participation guidelines, committees, which you can participate in, information on stepping up to organize or facilitate and information on teams. But this video is mainly about the September weekend single source of truth or SSOT. Here on the people tab, you'll see a list of all the participants and their first name and eventually their complexity weekend username here in this table. We'll collapse that menu over there. And now let's look at how do you participate in the pre-weekend program. Whenever you see a link, it's clickable and that'll take you right to this page, the pre-weekend program. So this page covers the pre-weekend program. The pre-weekend consists of you scrolling through the single source of truth in your own time and setting aside the time in your calendar for some of the pre-weekend events as well as the weekend events. The aim of the pre-weekend is to build your excitement for the weekend itself to give you a taste of what complexity weekend activities are like and to provide many, many opportunities of different kinds for onboarding. So please feel free to join as many or as few of these pre-weekend events as you'd like. Also during the pre-weekend, check out the facilitator introduction videos. This is going to take you to a YouTube playlist where you'll find a bunch of facilitator introductions. The facilitators are going to be doing facilitated sessions during the weekend and they're also around as participants just like you. So check out their videos, get to know them and they're also exciting to hear from. This table provides different pre-weekend events. You'll see that all dates and times are represented in UTC. That might mean that you'll have to convert time zones. And so the easiest way to get these events on your own calendar in your own time zone is to click one of these two links, either a Google calendar or an iCal link. These links, if you haven't already been added, will help you get all these events for the cohort on your own calendar. Otherwise, you'll probably have to convert from UTC. And there are various types of events and those types of events are described here. There's a people events where we'll have a short group conversation and then a bunch of one-on-one dyadic conversations. We'll then have facilitation training as another kind of event earlier in the pre-weekend where Monica Kang and other facilitators will be talking about facilitation at complexity weekend, what it is, why we place such an emphasis on peer facilitation, and what facilitation means and, hint, they're facilitating your participation. They're not speakers or lecturers or here to give a talk. This is going to be a really engaging interactive experience that the facilitators are there to catalyze. During tech office hours, we will be able to address any technological questions that you're having, any questions about using CODA, this tool that I'm in right now, or about gather, the spatial video chat platform that we use. And welcome to complexity events. We'll be having really accessible and engaging discussions around complexity and sharing people's journeys and perspectives on complexity and talking a little bit about how we begin to learn and apply complexity together. In the purpose of complexity weekend session, Sean, one of the facilitators and a co-founder, will be working through some writing as a collaborative exercise that will be about complexity weekend's purpose. And during the team's sessions in the pre-weekend, those sessions will specifically be addressing the team's process at complexity weekend and how teams are formed and what teams can be, how teams are scaffolded during and after the weekend. So that's the pre-weekend. And also there's a calendar view. You'll find that on almost every day, and we can add more if people have requests on almost every day at different time zones, there'll be something to join into. So please just join in. Go to your calendar event and join the location link in the calendar event. So that's the pre-weekend from whenever you're listening to this video until September 23, 2022. Please join pre-weekend events. Let's go back to the top page. How do we participate in the weekend itself? So all the events during the weekend itself will also be on that same calendar event. So we will have a representation of the program here in a table so you can scan through and so that you can search for different kinds of events like you're interested in the live streams. So here's where you'll find the ability to search and determine what's happening on different days and times UTC. You'll also see the same information on your calendar and more information will be coming closer to the weekend with the exact schedule. But suffice to say, whenever you show up 24 hours a day, there will be interesting sessions and people there for you to connect with and think about teams with. The last two pages that we'll go through here are Exploring Complexity and Exploring Teams. Exploring Complexity will link to another COTA document that exists across cohorts and that is going to be about exploring various topics and methods related to complexity and complexity science. And then in Exploring Teams, you'll see more detail about how teams form at complexity weekend, about the form that you'll fill out to seed a team. This is the team seed form. And there's more information on this page on forming teams. But that's for another session, for possibly another video. This video, hopefully it is enough to say that during September, please participate in the pre-weekend program, join the synchronous events, and watch the videos in the pre-weekend playlist and also set aside time in your calendar, whatever works for you so that you'll be fully able to show up in the weekend program itself. So, thanks a lot. We're looking forward to your participation and your feedback on anywhere that we can improve the documents and the participant experience. And we'll see you soon. Thank you.


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