This paper proposes an optimized scheduling algorithm for social network big data. The algorithm considers both the amount of data communication between tasks and the amount of data processing required by each task when determining the optimal schedule. This ensures that tasks with high priority are completed first while minimizing the total execution time. The experimental results demonstrate that the proposed algorithm can quickly optimize the scheduling of social network data and effectively solve the problem of strong data collision. This article was authored by Weina Fu, Shwailu, and Gautam Srivastava.


Did you have a female role model while going up? Um, yes, but Roma probably my mum, just because she kept herself really active and fit. So I'd say that's probably my only role model. My female role model is Hannah Miley, who's also a swimmer, and I found that she represents someone who shows that you can do anything you want to do as long as you put your mind to it. See where definitely Miss Sharp and then who I could actually see on the TV. My role model was Simone Biles. What do you think, for itself, young girls from trying out when you're sport? I think one of the main reasons is stigma from the media, as often it represents unrealistic beauty standards that a lot of young girls especially feel like they need to meet. Boys. So I would say probably the biggest thing would be embarrassment in front of boys. Boys. Because, like, sport can make your body look different to others and some girls struggle with body image. I think pressure, maybe a little bit of gender, maybe boy or girls, and I think media. Boys. It's to do with confidence, and a lot of females really struggle with confidence in a new environment, especially sport, when there's males around. Boys. Do you think there's enough opportunity and access for young girls to participate in sport? Yes, I think there is, but I do think there's a big enough drive for it. Well, there is quite a lot of opportunities, just not as many as boys. No, there definitely needs to be more opportunities and more encouragement. In some sports, yes, but in most sports, no. There's been more opportunities now, but growing up, not really. No, but I think we're getting there. Sport for females is growing, but it's nowhere now where it should be. I think there's a lot more than there used to be, but there's still like inequalities in sport between women and men because the 1500, the 1500 front crawl was unusually added in the Olympics for women. I think definitely more so now than years before. However, I still feel that boy sport is still widely more encouraged and it's encouraged for them to do it than it is for girls. Have you had any struggles with being in women in sport? Growing up with women in sport, my main struggle has been my period as sometimes it can make me feel amazing while other times it can make me feel really tired. Struggles would be that I would never be allowed to play with the boys. Some struggles, I think it's just hard to kind of keep up with the image of being sexually in gyms, you've got to be strong. Men seem to be the dominant cause when it comes to weightlifting and women are meant to be a certain way, a certain type, a certain body type. The boys told me I wasn't getting enough. Yes, so when I was growing up and when I was in the swimming club all of the coaches were male, so understanding the female body for them was quite difficult and the lack of knowledge that was accessible to them was limited. Yeah, I was told I wasn't good enough cause I was a girl. Why do you think by the age of 14 girls are dropping out of sport two times faster than boys? I think that leads to opportunities available, I don't think there's enough drive to keep going to push on. They just don't see it as being cool and a lot of females don't see it as an important thing in their life. It's more about looking good and not looking sweaty and running around and doing whatever in sport is my... Cause there's not enough influence for us. I think as a girl growing up it can be really hard for us as we have to deal with things like our period and unrealistic beauty standards again which are things boys don't have to deal with but also the encouragement girls just aren't encouraged to do it as much as boys are. There's not enough support for girls as a girl though. I think it's a variety of reasons but media, coaches and the lack of opportunities for single sex clubs is the main ones. What advice would you give to a young girl who's thinking what to do in sport? Just do it because you'll enjoy it and take everything you can forward. I think you won't know unless you try and I think once you throw yourself just into something, give it all you've got. Don't do it for any further back, just throw yourself in, launch in and just do what you enjoy. Take any opportunities that you can get. Try it out because you never know, you might like it.  Don't listen to what other people have to say, just do it.  Don't give up when things get hard because you'll regret it and keep your bum. Go for it. To try as many different sports as you can. Keep trying different things then you will find something that interests you be it a team game or a racket sport or an aquatic in the water or an aesthetic. There's definitely something out there for everybody and I would encourage all young girls to get this idea out their head that they are not as good as boys because I could run rings around the vast majority of boys when I was at high school and I think that they need to be confident about their bodies, their image and just try it. You've got to try it because I am utterly convinced that there's something for everybody and being such an important part of my life I will never give it up.


So today, we have Dimitris Piaracos from the Matinar Research Center from Greece, that is the service manager of the Open Aerospace Service, that I would like to thank Derevelivity to be here today to present the service. So Dimitris, go for it. Thanks, Andrei. Okay, let me share my screen. Okay, can you share my screen? Okay, so I can start. Good morning. Thanks, Andrei, for the introduction. And I'd like to thank you all for joining this series of OpenAir webinars and this usage count seven as in particular. A few more details about me. I have a Bachelor of Physics and an MSc in PhD in computer science and since 2014. I work in OpenAir project as a member of a technical team. And as Dere mentioned, I'm the developer and the administrator or product manager of the OpenAir usage counts service. The usage count service is the service developed in OpenAir in order to analyze the usage activity in commas providers participating in OpenAir and build user statistics. User statistics provide that kind of alternative way to measure the impact of the research and complement traditional scholarly impact indicators. But I will dive into more details during this presentation. So another view of this presentation. First, we will present this introduction to the concept of user statistics, why they are important, as well as what are the available standards for acquiring and exchanging the user statistics. Then we will present the usage count service operation in terms of architecture and engagement with the service. Some initial lab words that show how the service has been deployed. An interesting part of, at least for me, for this presentation, and I hope for you also, will be the future developments. We'll discuss and present the updates in the user statistics concepts after the employment of some form of a new standard. And finally, we will proceed with a demo, I hope without surprises, that we will try to show how the service outcomes have been deployed and how they could be consumed by various interfaces, either inside OpenAir or from conder providers in particular. So first of all, user statistics. What are user statistics and why do we bother collecting, building and working with them? User statistics are based on the processing of usage events. And usage events are triggered by accessing the digital objects in content providers, for example, repositories, journals, and crisis. So digital objects are articles, data sets, thesis books, etc. And once triggered, a user event could be either a metadata view of the digital object, for example, a visit of the metadata page of an article, or a full text download. User statistics, why are we using them? Why are we exploiting them? User statistics are important not only to content providers, but also to a variety of stakeholders, like publishers, aggregators, or funders. For many content providers, user statistics are a required element of their regular and typical reporting to funding and accreditation agencies. User statistics can play an important role in driving a bibliographic institution, internal marketing, and the development of the provider's website. For example, for publishers, the number of full text requests for a given journal is a strong indicator of the impact of the journal. In terms of marketing, monitoring usage over time is a good way of determining the effectiveness of various content, and marketing or campaigning strategies that may be implemented. Finally, aggregators, like publishers with larger services, they require user statistics. They want user statistics not only to assist with collection management, but also to help with the overall management of their services. For example, again, monitoring full text retrieval over time helps with capacity planning for their infrastructures and allows the services to plan ahead for growth or even peaks of their services. More or less user statistics is a logical choice as another impact measure that could supplement other impact factors like citation counts. Don't forget that this is that readership information can be easily and somehow routinely collected. Another aspect that bibliometric indicators do not show the usage of published work by non-authors, for example, students, academics or non-academic users who do not usually publish, but may read scholarly publications. User statistics for academic publications may therefore give help to give a better understanding of the user patterns of documents, and can be most recent than other bibliometric indicators. This is a very important aspect of user statistics as a concept. On the data provider level, user statistics can serve repository managers or content or hosting institutions as a tool to evaluate the success of their publication platform. On the individual item level, on the other hand, this tool can demonstrate popular publications to authors and readers. In addition to other traditional measures like citation counts or alternative metrics, for example, mentions, recommendations, posts in social media, it can inform funding authorities in research evaluation processes. Finally, user statistics on the item level can reflect the relevance of a particular research output of research topics, of data sources over the course of time, and up to the present, so they can be an important indicator to analyze the trends for these items. So we discussed the importance of user statistics, but how about standards? Is there a way to have a common language to collect, exchange, and most importantly, compare user statistics among content providers? And here where the countercode of practice enters the scene. Counter, which stands for Counting Online Usage of Network Electronic Resources, is a non-profit organization which is supported by a global community of library, publisher, and vendor members. And all this contributes to the development of a set of directives that consist of the countercode of practice through working groups and outreach. So countercode of practice is some, more or less, the international standard used by librarians, publishers, and other code that provide them for reporting usage events for electronic resources in standardized ways, and I would like also for collecting and processing the usage events. So it's not only for publishing, but also for countercode of practice, provides the instructions, the directive for processing also the usage events that are collected. So counters that arise usage reports allow providers to compare usage across different publisher platforms, assess user activity, inform with new and new purchasing decisions, justify budget spends to the stakeholders, derive cost per user for content, and inform faculty power users about, or power users about the value and use of current content provider or library resources. There is a variety of services offering usage statistics. Iris, of course, is the national service for the UK, make that account that focuses on data sets, knowledge and lots, Elsevier for publishers, the referential that covers the South America, operas that mostly focuses on books and monographs, RAM, and N plus. So how about our service, the usage count service, this is the use statistics service of for open air research graph and explain this concept in the next slides. First of all, open air. Open air is a European project funded by the European Commission since 2008, and has led the shift to open scholarship in Europe and help alignment with the rest of the world. So open air more or less bridges the words where science occurs and science is published. In one hand, open air is a community driven organization on heart, which accomplishes a participatory infrastructure in European Union member states and associated countries. And this is an infrastructure is accompanied by a service driven approach which aims to support, accelerate and monitor open science. So open air offers services for any kind of for all stakeholders, researchers, scientists, corner providers, funders, institutions, etc. So one of the services that users come serves that we will be discussing this presentation. The main structure of open air information is the open air research graph comprised of interleaked scientific products with access rights information linked to funding information and sets communities. Open air graph provides a form of a kind of a model for the presentation of the formation and open air uses it to represent objects which are in the context of open air are called reset products and businesses products are presented in the scholarly communication domain and they also includes the relationships that exist among them. Among them. So the users counts service inside open air infrastructure users count service is one of the pillar services of open air and simply counts the usage of the graph entities. In other words, the usage of the research products across the network of open air content providers. So in one hand, we have the content providers that produce the content is like it's 200 repositories aggregators that that archives software repositories. This content is is enhanced by other functionalities of open air which operate on research products, for example, the duplication or mining, and then the users count service exploit all these enhanced information to provide a more holistic approach to users statistics and this will be discussed later. So how we do it and how the service operates. We have two different approaches for beating user statistics. The first approach is based on the push or what we call a push workflow, which is depicted in the upper part of the graph. And this approach is based on the on the matomo analytics platform. Following this approach, an institution repository registered in open air providers portal, which is the main entry for participating in the open air infrastructure. So after the registration, a server side tracking software is offered for this for the content provider in the form of either a plug in for for this space platform or patches for the ePrince platform. We are also offering a generic matomo or a generic tracker software, which is based on matomo and that covers all the other platform that are available. So all the plugins and patches to enter generic matomo tracker tracker are exploiting the matomo HTTP API. I'd like to mention that we do not use matomos native tracker, which is based on JavaScript, in order to avoid what we call in missing a direct request. So we don't want to miss a direct request. For example, if a request for a PDF in a content provider is coming by Google Scholar, matomo natives JavaScript tracker will not count while our server side software will properly recognize the request and track it accordingly. So usage activity is tracked and logged at matomo platform in real time. IP anonymization is also offered as an option to respect users' privacy. So keep in mind that IP anonymization is offered again at the server side. So if it is enabled, all IPs are transferred anonymized to matomo. We do not have the IPs anonymized inside matomo, but they are arrived anonymized if they are if this option is enabled. Also countercode of practice robust list is also used in when we are processing the usage of activity in order to remove non-legitimate traffic. So information is transferred offline to openers databases for statistical analysis that follows again the countercode of practice directed. And from this user statistic database statistics are deployed in openers portal like provide, explore and the recently open science monitor, or can be collected by API endpoints which are based on SushiLite protocol. So this is the first approach. The second approach we call it follows a pool form of a workflow. This is used for gathering of course all the data statistics reports from aggregation services. This is the case that we use that we have employed for Irish UK. And we are using protocols that are based on SushiLite or other REST API interfaces. We are also covering using this pool workflow. We are also covering open science journals using a dedicated plugin for OJS platforms. Again, statistics are stored to openers database for statistical analysis. They are integrated with statistics count collected from the other, from the push workflow. And then again deployed by openers interfaces, portals or can be retrieved by the SushiLite API. So just to recap, the main services for usage count. We are tracking of usage, row activity using the push workflow or we are collecting counter reports following the pool workflow. We are offering anonymization of IPs. We are enhancing this usage information with metadata duplication which enables accumulation of usage for the same set of outputs. This is the role of the metadata index that I mentioned in the previous slides. Statistics are produced and created using the counter code of practice in order to provide standard based form of use statistics. And then we are finally, as mentioned in the previous slides, we are producing indicators that complement other traditional alternative biometric indicators in order to provide a comprehensive and most importantly, a recent view of the impact of the academic resources. Uses counts is also a part of EOSC. All these features that are provided by usage counts are also available in EOSC where usage counts is a core service offering the account, what is known, the task of accounting for research products. So research products account service is able to aggregate either by push or pull usage indicators for different type of EOSC research products like data sets, articles, books, etc. And research products accounting is provided by the open-air usage account service. As a part of EOSC, user statistics will be collected and made available. Research product user statistics are integrated with EOSC research product catalog. And another important aspect is that enrichment of EOSC research catalog with user statistics indicator will be visible to end users and offered in the dump of the catalog when published in Zenondo. So together with all the metadata information, the EOSC research catalog which will be published in Zenondo will also include the user statistics that have been produced by our service. And usage counts is also a part of the virtual access metrics account system offered by EOSC. So engagement, how can you participate in the service? First you have to visit the provider's dashboard. And you have to register your data certificate.  The next step is you have the option to enable the metrics, the user statistics for selected data source. There are four different steps that need to be performed. Three on our side, on the participant sides and one in our side. On your side, you have to download the tracking code for your repository platform. Either for the space, for the prints, or if you have another platform, you can download the generic track. You have to configure it according to the instructions that are provided in the documentation or you can contact us for support. And finally, you have to deploy the tracking code in your repository platform. On our side, on the open side, we are going to, as soon as the repository enables the service, we are starting monitoring in this the repository in Matoma, we'll show you in demo later how this is realized. So we are continuously monitoring the service and when everything is the usage events that are coming to our platform and we are valid and we are validating the installation of the tracking code and inform the repository manager accordingly if everything is okay according to the recommendations. So for the software, the next step is to to configure the metrics. You have to download the patches for various versions of this space. We are now supporting this space four, five and six and soon we will support this page seven. We are offering any prints like in for version three and again, as mentioned, we have a Python script for all the other cases. So the configuration of the services is very easily, it can be easily done and you have the full support of us if it required. This is how all usage events are collected in area time. This is where Matomo is actually employed. So this is a view only for a usage count service administrator and we use it initially to validate the content provider and then to monitor the provider users activity. As mentioned, the description of the push for workflow, we are transferring these users activity. We are processing it using the counter code of practice. And then we build and store the user statistics in open open statistics database. From there, they are deployed to portals or retrieved by API endpoints, but we are continually monitoring the service. We do not use Matomo for statistics, but only for monitoring. So let's see some service number. We have collected information from more than 200 content providers. The majority of them are institution repositories. We have also covering journals, we have 20 journals, we have data repositories, publication repository aggregators, and we have the scholarly communication infrastructure, which is the open-air portal itself. We are also collecting information from open-air portal. We have already collected up till May 2022, 6 million research products. We have collected user statistics for 6 million research products. We have 247 million views and 732 million downloads. And of course, the number of downloads is greater due to the indirect requests that are covered, that are collected by our tracking software. By the end of this week, we will update the statistics up to June 2022. So you can also see the evolution for the last year of the number of views and downloads that we are collecting. And you can see that we are collecting more than 10 million views and 20 million downloads. As I mentioned, it's until May 2022. Finally, we are offering countercode of practice release for reports, which are supported. We are supporting five reports that you can use to retrieve countercode of practice compliant reports. I will show you a demo later of these kinds of reports and what you can actually get by using these reports. So far, this is the current status of the service. I'd like to move to the future and their future developments and the upcoming updates that will be, I think that will be of great importance for content providers that participate or want to participate in the service. So the upcoming updates, the implementation of countercode of practice new release, the release five. So all the concepts that we have discussed so far are following the countercode of practice release for views, downloads, countercode of practice, reports, etc. The new release somehow changes completely the way that users' events are collected, counted, and published. So I will try to explain what are the new metrics and the reports for this new release of counter. I will provide some examples and also a comparison between the release four, which is currently offered, and the upcoming release five. I will also try to discuss the new concept that they reduce like data types, access methods, etc. So first of all, metric types. We have to forget the traditional views and downloads and move to the new concepts of the new terms of release five, investigation and request. So in release five, every access, every usage event is considered an investigation. So investigation is tracked when a user performs any action in relation to a content item or a title. Either it's a metadata view, abstract view, an HTML full text, a PDF full text, a download, PDF, or an article preview. On the other hand, a request is specifically related to viewing or downloading full content item. It's more or less close to the concept of downloads in the release four version of the counter code of practice. So new metrics are also using the suffix unique and total to further categorize the metric types. So you have the unique item investigations, which count the unique article investigations and requests inside the user session. The total item investigations, which count the total number of times information is related to an article viewed, including all article full content views. The unique item request, which count unique article full content views in a given session regardless of its format. So for example, if a user views an article PDF and the HTML in the same session, this would only count as one. And the total item request, which counts all article full content views across all formats like HTML and PDF. This is more or less equivalent to release four downloads counts as measured in the previous slide. I will try to provide in a scenario, Susan, we have a user named Susan, which is researching the history of portal side you mean or repository. And from a list of search results, she opens three article abstracts. So the counts for the according to the code of practice at least five is three total and investigations and three unique item investigations. So after reading these abstracts, Susan downloads the PDFs for two of these articles. The counts change to five for total item investigations. We have three views and two downloads, three states for unique item investigations. But now we have two total item requests and two unique item requests. And this is a, I'm leaving this example in this slide. So for further references, you can see the changes and how this counter code of practice list five operates. So if we want to compare this four and five release five metrics, we could notice that downloads and total item requests are the same, are almost the same as you could see in the graph. While views and total item investigations are completely different metrics. So views and total item investigation cannot compare to views. So why do we use them? Why do we have this release, these changes in this release? So the counter code of practice list five metric type features. The total item requests are important for providers that more or less have full text content and they report a number of full text downloads or views. The total item investigation provides a big picture perspective of the total number of investigations and unique investigation the request are considered powerful metrics for identifying activities within unique items and titles. And they are considered most accurate for cost per user analysis. Have we discussed the new metrics? Let's move on the other concepts which are reduced in release five data type. It's a pretty self-explanatory that defines the general type of content being accessed or for which usage is being reported or calculated. For example, data type could be an article, a book, a segment, a collection, data base, data set, etc. Release five also introduces the access type concept which describes the nature of access control that was in place when the content item was accessed and the item which appeared in the journal title reporter one. This is a form of counter release five report and allows usage of open access content to be separated from content that requires a license. So we have control, open access delay, open access goal, etc. The access method is an attribute indicating whether the usage related to investigation request was generated either by a human which browses the repository or the library or whatever the content provider form is or by text data mining processes. And this attribute appears as an optional parameter and TDM usage is excluded from the standard general and book report. These are some details for the publication, for the production of the reports. Finally, release five also reduce the concept of the year of publication, which is the year of publication for the content item access. So if content is available in print and online format and the publication days of these two formats differ, the year of publication of the print will be used. And this item which appeared in journal title report as well as the book reports. So in terms of reports, release five has reduced number of reports. We have four master reports, 16 total versus the 24 reports that we have in the counter release four. Many of the special purpose reports that are seldom used are replaced with a small number of flexible generic reports. And all counter release four reports have either be renamed or eliminated in order to use the new version, the new release report options. We have more filters to select dates, content types, metric types, year of publication, license types, and more in various combinations. This is the list of counter release five reports, platform master reports, the platform usage, etc. In the context of open air, this is our initial implementation of the release five reports. We have developed two master reports for platform items, the platform master report which reports summarizing usage activity for the repository by month metric type and item type, and the platform usage and the institutional report, the platform master item report which is a report for items requested by month metric type, item type and repository. And we also developed the platform usage report which is a report summarizing usage activity for a repository by month, broken type, down by metric type. And we have also added a dataset report which is not included officially and has been introduced by make that account initiative for reporting user statistics for dataset explicitly. The report also uses the new metrics that have been introduced in the in the release five is a particular investigation request, but as I mentioned it's not included officially for at least for this current release in the counter code of practice directors. So as an example the filters that are allowed, if we want to get a platform master report, the difference is that we are now there at least four reports, there are no filters in the, if you have used already the release four reports, you can see that you will remember that there are no filters for the metric type which are now offered in the platform master reports. And I'm talking about the total item request or total investigation that could be selected. And this is an example of a platform master report following the counter code of practice release five and for the platform like the University of of Minio. And you can see the data type, the access method, the total item investigations and the request, etc. And finally this is the release five report attributes that could be used in order to generate the reports. Some of the yellow are the most important which have been used and will be offered in our reports. So before proceeding with RECAP, I would like to show you a demo. Can you see my screen again? Yes. You are seeing Matomo. Okay. So, okay. This is the main Matomo platform that we used for monitoring in real time. The repositories. So for example, if I select the the Umino and change, okay. So for today, okay, we can have the events in real time. You can see here that we have a metadata view for this particular item, the title of the item, and also a download. So this is, as I mentioned, this is only used for monitoring purposes or the initial validation of the repository. So every time a repository or a content provider is registered in the service, we are using this interface to check if everything is recorded properly. And later on, we will validate, we are validating the service. So you can see an overview of the reports. We can see this is the raw usage activity, again, as I mentioned. It's in real time. This user scouts opennet.eu is the main portal of the service. When you can see information for the service itself, you can see what is the user scouts service, why opennet user scouts service, what are the benefits for providers and consumers. We can have some features of the service. You can have some form of analytics. For example, you can see the worldwide results. We have more than 200 repositories. This is a number that has been, more than that, of course, it's more than 200 repositories. The views are 248 and 732 million downloads. You can also search for a country. For example, to Spain, you can see the number of the repositories for Spain. Okay, let's wait. And this is not normal. Okay. So we have the number of repositories. The repository is 16. We have collected 45 million views from Spain and 240 million downloads for this particular country. You can also see the monthly events as arrived in Matomo. You can see the monthly views and downloads that I have already presented in the slides. And in the resources, you can get a counter-release file for a report. For example, as I mentioned, we have the article reports, the item report, the general repository, and the book report. I will give an example for this particular report. If I begin, if I enter the date for it, I will check for the whole period, and I will check for an item, use the DOI. I hope I found, yes, this is what I'm looking for.  And the number of requests for January 0, for February, we have four downloads and one view, etc. for March 3, 2, 0, for April, and one download for format. And this is a report that it can be easily retrieved. So in Provide, I mentioned this is the place where you registered, but you can also see the user's events, the user statistics that we have collected in this for your repository. And I will try to log in. I will use the example of my favorite repository of Mino. And you can see the usage counts either in tabular form, either in boxes or in a form of visualization like this in the graph for total views and downloads. From here, you can get the statistics reports, and we have the five reports that are compliant with the countercode of practice list four. So if you check the article report and select, for example, for the first five months of 2022, you will get the reports. I hope there are no issues with our backend services. Okay, so these are the results for the first five months for the Mino repository. You can see for this particular article, you have the zero downloads and views for January, February and March, and we have only one downloaded one view during April. For this particular, we have more information. For this particular article, we have more information. For example, we have one downloaded one view. This is in a tabular format, not in the JSON format that was displayed in the other interface. So we have two options. In provide, we are offering tabular format of these reports, while in the usage counts portal, we are offering the JSON format if you want to retrieve them directly. Usage activities also displayed in OpenAir Explorer. I don't know if you are familiar with this. This is the main interface where you can find, we can search all content that is available in OpenAir Research Graph. Again, I will search for Mino University as a data source. And you can see on the left side that we have the total number of usage statistics that we have produced that we have published. And if you click, you will have the total number of views and downloads for each month. Again, this is a similar with the one that you have seen in the provided taskbook. However, in OpenAir Explorer, this is an interesting outcome. If you set for a publication, for example, for this publication, you can see that this publication has 20 usage events counted for this particular item, either views and downloads. The important thing is that if I click on this button, you will see that we have 19 downloads and one total view. This has been aggregated from different content providers. This is how we exploit the metadata index that are mentioned in our initial one of the first slides. All this information for this particular item has been aggregated and presented in this form.  Finally, we mentioned the reports. So the last interface is Monitor, which is a new portal that is offered for monitoring the research in institutions and funders. Monitor offers a dashboard for various types of organizations like funders, institutions, etc. So if I select an institution, which will be public, for example, that has public information, in particular University of Gettigan, I will move to its institutional dashboard. And here the user statistics are in the form of impact. So you can see that for this particular institution, we have 80,000 publications and we have average downloads of publication and the total downloads. You can see also a number of, let's say, interesting indicators that are based on user statistics that we have collected. For example, the downloads per publication over time or downloads per publication over time based on the year of publication. The downloads per publication over time and by project participation with abstract over time. This is important because it shows the downloads of publication by open access route over time, if it's green, bronze, etc., or by downloads per publication by open access route and the year of download. As you can see, there are a number of indicators that we have built and the user statistics are one of the main parameters of this indicator of these graphs that are used to somehow provide the impact of this, to measure the impact of this institution. We also see the top genus and per publication from repositories. You can check this interface and you can examine it and see what would be offered in this from this form of impact, let's say, for this particular interface. So let me go back to my presentation. So, 40 cap, sorry, open and users count services is an easily configured robust service. These are the key messages that I would like to convey from this presentation. It follows countercode of practice standards, release four and release five in the future. And users count service for provided is a form of an umbrella system similar to the EOS that provides information on the impact of your repository by integrating users data and offering comparable analytics of the repository's content across the open area infrastructure. For research products operates on open areas and graphs and allows aggregated user statistics of the research products from repositories all over the world. So you also gain the advantage of doing aggregated user statistics of your research products. So that's that's all for me. Thank you very much for your attention and for your participation. I hope you have liked this presentation and found it useful. I would like to pass the floor to André for the for the beef in order to guide you through the feedback of this for this presentation using this mental tool. We also have some questions in the chat. Maybe maybe we can start replying to some questions and then we can move to the stop sharing my screen and I will try to try. The first question is it's about what represents the views and downloads and why the views and downloads are different. And Carlo already answered about the difference between the numbers of views and downloads that what are the difference between views and downloads. So someone has replied. Sorry. Sorry. I couldn't understand the question. Yes. Carlo replied about the why we have different numbers of views and downloads. Okay. I mentioned in my presentation the push of the push workflow that the number of views are less than the number of downloads because we are offering what we call them indirect hits. We are counting in direct hits. So I also described an example. So I assume that you have a repository. You have an article which has a full text in its landing page. So if I go, if I visit the repository and I click on this article and I click on the download of the PDF, I will have one view and one download. Is this correct? Okay. But if I search for this article in the Google scholar and I receive a search result and I click on the search result and I will go directly to the repository for downloading the PDF document. This is counted as a download only, not as a metadata view. So that's why we have more views than downloads. Okay. We have a question for Amelie asking if it is possible to show numbers for an aggregator. For example, Narciss. More the question was, can you show it? Because we are not aggregating from Narciss as far as I know. Narciss is a Dutch portal. Yes. We are not collecting useless events from Narciss. If you want to join the service, of course, we can participate. Have you discussed it earlier? Yeah, but I've heard that it could be done, but I thought okay. So I have to ask if it can be done. Yes. Okay. From us, it's no problem. I mean, we can aggregate, we can receive useless events from aggregators. So you have to simply participate on the service. Okay. We have another question from Magdalena. Do you know how Matomo counts the views and downloads? Do they filter bots? That's the first question. Yes. Okay. So if Matomo counts views and downloads, yes, it counts views and downloads. It can differentiate between views and downloads. But as I mentioned, we do not use Matomo for our service. We are simply collecting the events, and then we are processing to count views and downloads using the countercode of practice, a list of bots that is updated continuously. So Matomo is more or less used as a monitoring tool and just to record the usage events. All of these, all of our processes are performed outside Matomo. The other question is, do they use a specific blacklist? I will not want our local statistics to show drastically different numbers than the entries in opener. Do they use a specific blacklist? You mean Matomo? I hope so. Because I mentioned that we are, apart from Matomo, we are using the countercode of practice list of robots in order to exclude non-legitimate traffic. We have another question from Magdalena. If we provide our statistics now and later decide that we no longer want to participate, is there an option to withdraw the data? Of course. Yes, you could ask them and withdraw the data. Yes, I have a big question from T. Romis. How do metrics like these differentiate between popularity and impact importance? And this is related with, for example, the papers regarding COVID-19 that receive a lot of popularity. So you mean that we can, how do metrics like this differentiate between, so somehow we have to count the topics that are included in this, that these articles are about. I mean, this is how it can be differentiated. This is a part of, I think it's of the monitor that the set of indicators that we are producing. So I think it will be, if we include metadata information from the, from open area sets graph, this could be feasible. And we can differentiate this kind of concepts. He also, I hope I have answered your question. He's also asking if we are going to monitor also keywords such to determine such intent and how the paper content satisfies the needs of the person who searches for certain information. Not for now, we are only counting events as views and downloads. We did not set any other kind of information, but yes, in the future we are planning to include the keywords sets. And we have a question from Oliver. I have notices for our user statistics that transfer of 2020 have been changes retrospectively. I have collected them about two months ago. And when I looked into the dashboard today again, all the accounts from 2020 and 2021 were higher than before. How can that happen? Okay. Can you send me an email so I can check? And that can reply to you. Yes, sure. I will send you an email. Sorry, Oliver. I will check it. Okay. Thank you. Thank you for the questions. We also have Maria that raises the hand. Please, Maria, you can open your microphone. Thank you. Thank you, Dimitris. It was a very interesting and informative talk. My question is about what is the situation with the usage coming from the publisher side because they have been obviously recording usage for a long time.  Or can you still sort of take what is published on their platforms and sort of import it anyway? Hmm. This is an interesting question. Well, if they are available in public and they are following some kind of directives, for example, counter-code of practice in particular reports, then we can potentially collect them. But you mean without somehow signing a kind of an MOU or agreement? Yeah. I'm not sure we will be able to do it. It's a business decision and we have to discuss it with... Right. Because obviously this would be... Sorry, everything that is available in any form of counter reports can be collected by our service. Yeah. It would be incredibly powerful if this service was able to really unite all usage figures from everywhere. Do you know at this moment how the publishers are viewing it, whether they're inclined to provide their usage data or not? No. I don't have such an impression. But we are trying to contact as more publicers as possible and make agreements with them so that we could collect them. Because the software is there, I mean, the tracking software is available. So the only thing that is missing is more or less is the participation agreement, etc. So that's where we are trying to conduct the publishers and ask them, okay, do you have your statistics? We can collect them. And then we can be aggregated, which is an important aspect, a powerful aspect of our service. We can aggregate them and you can take them back easily using these counter standards. So I think it's... Yes, I agree. It's a matter of an agreement with the publishers and this will make our service more powerful. Thank you very much. Okay. Thank you for all your questions. I will now share my screen and it will be quick in order to finish our session. We just have some questions to you about the uses of service, their knowledge, and we would like to have your feedback that will be important for us in order to develop the future developments. So the first question is, have you activated users account service? Majority no. We have four answers for no and five for yes. During my answers and the majority didn't activate the users account service. So today with Dimitri's presentation, we know... Now, how to activate the service? You can access Provide dashboard if you have a data source. You can register data source in Provide and then you can also enable the service. And then maybe we could ask our audience if they have already participating, registering the provided portal. Yes, in some cases we have users that already have their data source registered in Provide but not the users account enabled. So please, if some of you already have enabled the service, the users account service but you not ended the configuration in your side. And if you need help, you can also contact us and you can support you in order to conclude this process. So you already have also the Dimitri's email address in the chat if you need to ask some questions about or not to activate the service. So let's proceed to the next question. If are you using counter release for reports or graphs in opener portals? The graphs that Dimitri is also demonstrated today. Some of you are not aware of these reports and some also are using and finds that they're useful. Some are not using or they found that they are not useful. So for those that are not aware of these reports, we hope that you are convinced about their potential and hopefully in the future you will start using it and it's also important for us in order to better disseminate the service in order for more people to know this service. Let's move to the next question. Are counter code of practice release five new metrics useful? So these new metrics that Dimitri presented today, majority says yes. That's very interesting. Some of you need to learn more about. Yes, of course. But it's very relevant that you find that these reports will be relevant for you. Okay, thank you. Let's move to the next question. Would you like to maintain both release four and release five graphs and reports in the opener provided dashboards? Is that only provided in old interfaces? Yeah. We can maintain both releases in the portals at least for some time in order to give you the opportunity to move from one kind of report metrics to another to the most updated and then we can discontinue. So in the year that your feedback is relevant for us because we will decide according to your preference. We have the participants more or less divided, but we have more people saying yes. Okay. We have more questions. Let's move to the another. Are more detailed reports, not master reports, useful? So are more detailed reports useful? Seven, seven, eight, nine people say yes. And more people say that they need to learn more about these detailed reports. Okay. So next question. When accessing the reports, would you like to see a preview of the first 20, 30 registries, for example, and then an option to download the full report? May I explain somehow what this means? We found that when the report is very large, we are having issues with the performance. So what we have examined is to have the report instead of being in a tabular form or the whole report, to somehow compress it and make it available to the one who has requested the report in a zip file. So instead of having the report displayed in the open air provide, for example, a link with a download of the report will be available. So this is the question. If you would like to see a preview of this report, and then you have also the option to download the full report. So there are two options. Either we have a preview and the download the full report, or you simply have the option to download the full report and not having a preview. So this is the question. So it looks like it would be useful to have the first 20, 30 registries. Okay. We are recording that. Okay. Thank you for your feedback. Let's move to the next comment question. Would you like to have access to more detailed graphics in the provided experts such as the downloads per publication over time and by open access routes? So the impact graphics that Dimitri showed in the monitor portal? Yeah. It seems the participants would like to have them. We have to change a lot. Okay. And also the possibility to select which graphics to showcase in dashboard. It's also relevant. Okay. Okay. Thank you for your feedback. And we have one last question, I think. Do you find useful the number of views and downloads displayed in the data search page in Explorer? For example, do you mean your repository example that Dimitri showed in the demonstration? I was expecting the last answer. I mean, this would only be displayed in Provide because somehow these numbers show the performance of the repository. And so maybe some repositories were to keep them somehow for their eyes only on this information. And it's also important to improve the way we are presenting the numbers in the portal. Six participants saying that. Okay. Let me check if we have another question. No. Okay. Many things for your feedback. Let's see if we have some additional questions in the chat. Okay. I don't know, Dimitri, if you want to say some words. No, I just want to thank you for participating. I hope you find it useful, our service. And I'm waiting for registering for the service and supporting you for deploying and see some of your numbers in our service. Okay. Many thanks Dimitri. Thank you very much, André. For this webinar. I think it was...


This is the cubes live coverage from information on demand IBM's event here in Las Vegas. This is where all the actions happening for IBM Iod the hashtag is hashtag IBM Iod I'm John Furrier the founder of Silicon Angle I'm joined my co-host Dave Vellante co-founder of wiki bond dot org This is the cube our flagship program would go out to the events Extract a signal from the noise IBM just delivered their keynotes which we carried live on silicon angle TV Dave Great event here IBM. This is our second IOD last year We heard them bringing that story together around big data, but this year. It's very very clear IBM is rolling out Much more comprehensive solutions with customer testimonials with some with some meat in the bone as we say around big data analytics Cloud mobile and social and to me the highlights so far is the obviously the data analytics is a big part of their strategy But you're seeing that the connection of two major forces at IBM's harnessing around here so far today And that is the big data revolution combined with social business You know cloud and mobile are kind of underpinnings under the hood kind of technologies that everyone is adopting and adopting I'll see mobile is already kind of the horses out of the barn on that one But cloud is certainly on on the agenda for the software to find data center We're seeing converged infrastructure really moving into the direction of the hybrid cloud That's all going on under the hood But really the big story so far Dave is big data analytics from data to decisions and insights with real new ways to do business and IBM honestly has been in this business of computing for many many years so the business of computing is now moving to the business of data and Social business so so what's your take so far of the keynotes and what do you expect it here for the next two days? We'll be live well John I think it's apropos that we're coming off from big data NYC Hadoop world strata conf where we had the cube we Interviewed a lot of guests and very Hadoop focused obviously it was our fourth year doing that show and the reason I say it's Apropos because IBM observed that whole Hadoop movement and last year really was to me the year that IBM put the stake in the ground and particularly Accommodated at IOD last year where IBM what I said had tweeted this out a lot super glued the the analytics Business it's analytics business to the big data mean and IBM has been hard at work trying to create a new Category big data analytics and I think it's caught on IBM's actually their own research Suggest it's not catching on as fast as maybe people thought but I think it is actually anecdotally I think everybody's really focused on the analytics pieces where the value is and I think that's what's different about this conference John last week Of course we heard a lot about key value stores and bringing sequel to do we're gonna hear a lot about that from a technology standpoint But 90% of the content at this conference is about business about business outcomes It's about business value, and we're gonna hear from a lot of not so much Hadoop practitioners as we are practitioners in health care or energy or other industries that are really trying to transform their businesses That's really the big theme here, and I want to just point out that a couple obviously major trends Just this morning in the Wall Street Journal Andy Kessler wrote an op-ed piece called you know around Twitter's IPO And I think that Signifies with Facebook's public offering at LinkedIn actually doing wealth social business is real The discussion really is around how people are using the data and then social obviously is what we're calling and we coined the term the crowd Consumer and that's this new psychographic this new user. That's out there. That's a worker. That's a that's an enterprise worker That's also a consumer and that we will be having some crowd activated innovation ourselves If you go to crowd chat net we'll be having a four hour live crowd chat If you're on LinkedIn or Twitter come join the crowd chat at crowd chat net slash IBM Iod we're gonna have we're gonna be documenting the cube conversations here on the cube where IBM executives and their customers We're talking about how they're using big data social business in cloud and mobile So go to crowd chat net slash IBM Iod and you will you will hear some of the conversations So Dave I think you know to me, you know the digital business model is here to stay Obviously we heard in New York City big data week NYC big data NYC once you turn that data tap on it You just can't turn it off. It's it's coming in from machines. It's coming in from people And I was hosting a panel with the CEO general electric and you know, we are discussing the industrial internet So, you know IBM is gonna be a major supplier to these businesses. This is about empowering not controlling That's a theme. We're gonna hear to hear today. So it's gonna be very exciting Well today you can hear a lot about analytics. We're gonna hear a lot about data science. Tomorrow is the social analytics piece and and Or social analytics for business and John you mentioned you mentioned crowd chat you talk about things like that But why is the hashtag becoming so important? Well, how is it a source of data? I want you to talk about that a little bit Well, I think what we're seeing is this new crowd consumer and we're gonna talk about this on our On our crowd chat is is that the hashtag is now kind of a folksonomy in database world taxonomies drove everything But now this new advent of what we're calling here at SiliconANGLE we want the crowd consumer brings in a new connected Element to the to the business model and that's people and the people-centric model Which IBM talks to in their social business strategy is grounded in analytics But the hashtag is a phenomenon that you're seeing not only on Twitter Facebook Tumblr any social network users are using hashtag to Signify their interest. It's a gesture of sentiment, but also more importantly. It's a gesture of discovery So what Andy Kester pointed out in the in the Wall Street Journal article update is is that this new way of doing business is going to Change how users find information who they connect with how community leaders not just you know Technical communities business communities communities of interest and more importantly how marketers talk to people So to me I see the hashtag as this new way for people to tune into the the conversations and ultimately the content No longer is it going to be controlling spoon spoon fed the content model of the past This is going to be a direct business model of content marketing content distribution to users So I believe that the hashtag will be a fundamental component like the URL was for the web And I see IBM is using it today. So if you go to hashtag IBM IOD you can follow along the conversation So, you know, we have Tim Crawford's already in I team out there is already on the crowd chat Go to crowdchat.net because the hashtag for the conversation is the conversation is the new content conversation is the new web page and IBM recognizes that a lot of innovators like Twitter are recognizing that Facebook hasn't yet grasped that yet I mean if you look at Facebook Dave technically, they just can't store all those hashtags fast enough And I think they might have a little challenge on the big data side there but in general users are tuning in and they're tuning into new ways to get information the paradigm of Google search will still be around but the new ways is more personalization and that is why we're seeing this notion of the persona of one concept come out where where businesses want to talk to To their customers directly not go through a middleman. So again, this is this is one of those Moments where you see these black swans come out of the marketplace from these major waves And we are certainly with social business and big data analytics in a massive wave a new wave And every time you have these wave billion dollar companies are created So John IBM of course has this massive portfolio in its analytics business It's DB to it's DB to that that that runs on Z but also runs on Linux unix and windows The whole big data analytics business that that comprises a numerous assets including things like Cognos and and obviously The old informants assets its infosphere streams products SPSS it's in at this event. You're also there's an information management focus. You're talking about Even the pure systems pieces those massive massive portfolio that IBM brings to bear So what we're going to be doing this week today and tomorrow is really trying to unpack that and understand how customers are applying Technology to create a business capability. So as I said, we're going to hear from a lot of not necessarily Technical practitioners will hear from those. We always get the tech athletes on the queue But we're also going to hear from business practitioners people in health care people in government people in other industries Jake poor way who's the MC of information on-demand IOD 2013 is coming on the cube today at 3 o'clock We got dr. Tim Buckman from Emory University is coming on later on this morning just in a few minutes We've got a number of folks of this morning at the keynotes John You heard Bob LeBlanc and and Bob Picciano talking about IBM's capabilities and Hosting panels of customers. I also heard a lot about cloud IBM made an acquisition earlier this year of software, you know We often joke that that big data gives the cloud something to do you want to put data in the cloud You don't want to necessarily have to move it. You want to analyze it and pull out the nuggets And actually move the code to the data but not move the data all over the place So cloud gives you the ability to very rapidly Spin up instances of compute and storage and be able to analyze data very quickly and get insights on the fly without having to necessarily procure Systems and and storage devices and the like so it gives you an infrastructure play very quickly IBM's acquisition of software really gets IBM much more into that business and they're really pushing the cloud and Big data themes so we're gonna be talking about that today For the next two days as I say today is big analytics day tomorrow social business It's one of the things Dave we're going to explore here IBM is obviously we're not going to go into the weeds too much We can if if we have the guests that want to go there We're happy to go anywhere. We're like a helicopter. We can go high level go go deep But mainly IBM's focused on business is key We do have a great deep dive technical Conversations from the cube last week in New York City and big data NYC you can go to Silicon angle or go to youtube.com So Silicon angle we have all those videos here, but to me what I'm interested in is the business model side of the innovation This new social activated innovation strategy by IBM is pretty compelling So, you know, so to me I want to hear how the business models are changing some of the value change What's going on at the customer base as we had talked with GE's? CEO and chairman Jeff Immelt and his top customers the vice chairman of united oil and gas leaders and Healthcare is that it's not just about the service side of the business It's also about the operation side So one of the things you know, that's always sexy to put in the key notes Is all the graphs of the social data but at the end of the day the nuts and bolts of business value That's generated very quickly is use of data insights for the operational aspects of this new internet And that's that's going to be around the instrumentation of equipment people and really changing the business models because the social business is both the operational side of it and kind of a Continuous innovation or continuous operations, but also as well as a new user experience So we're going to watch out for that today We're going to dig a little bit poke a little bit at that area We want to look at the business model side of it not just the end user experiences So, you know got some great guests here. We have the professor of surgery at Emory University School of Medicine We have director of big data analysts from IBM We have obviously the general manager of big data at IBM and then I'll see tomorrow We'll talk about the social business So it's gonna be very exciting, you know stay with us and go to crowd chat not slash IBM Iod and that all those tweets go to the hashtag all those comments logging with LinkedIn or Twitter Crowd chat is our new crowd activated innovation platform come join the conversation and take advantage of our new crowd mail service Where if you log in you can message folks within the conference here and chat with them and also chat publicly So this is the Cube. I'm John Furrier with Silicon Angle Dave Vellante. We'll be right back with our next guest after the short break


We are starting a monthly series here called TFI Topic of the Month aka T3M. I like short names, acronyms. And the topic for the month of January was cost cutting versus cost efficiency. As you know as we walked into 2023, we saw major cost cutting measures across industries which included better control on cost as well as trimming down teams which swelled during the pandemic. For this series, I'll be sitting down with founders, CEOs and leaders of the industry to better understand what's going on and what organizations can do to ensure cost efficiency. And today we have with us once again, John Murtic, Executive Director of the Open Main Frame Project. John, it's great to have you back on the show. It's great to be here. Thanks. What are you seeing? What kind of trends you are seeing in the market when we talk about cost cutting or companies becoming more cost efficient? I think the one thing is the same thing that we're all seeing here right now is that we're seeing a ton of layoffs over the last couple of months here. And what's sort of interesting is these layoffs in a lot of ways, if you look at the numbers they're actually sort of reducing down to pre-COVID levels to some degree here. So it kind of is a little bit of a course correction, but I think I was even reading in some of the reports from the Google one, which was just a few days ago when we do this recording, that it was basically a lot of overestimating of where's the demands and they kind of just let the hiring kind of continue to grow as they saw just the market demand for talent was kind of scarce. They kind of hired up. And that's just a reality. I think as vendors are looking at this from a course correction point of view, what you often see is people really kind of coming back and saying, well, what are our priorities? What are we good at? What are the things that we need to be focused on? And I even remember talking with companies a long time ago about that. And I always kind of bring back to, well, what's your core competency? Like why do customers value you? What is the one thing that your competitors cannot bring you? And when you start to get into that mindset, then we get into the last of a cutting to grow. But I think as you alluded to, it's efficiency and it's optimization and so on and so forth there. So I think that's an overarching trend you see anytime, a company that's very mature approaches this scenario. And I'm seeing a lot of that here, which long term, I think is a good sign. What does this economic challenges look like for the mainframe ecosystem?  And they have went through these valleys before. They've went through the economic challenges of the 70s. They went through the challenges of the 80s, early 90s, they've had the boom and so forth. So they've went through these cycles and every time they persevere, and why is that? There's such a central point to our society to function. All of that transactional processing from financial institutions to airlines to other transportation to healthcare to government all runs through it. So the need for that hardware is there. The efficiency that hardware can do that particular types of workloads is unparalleled. There's no other infrastructure that can do it at the same cost structure from that. So for companies that have the investment in hardware, and it's a big investment to get into, for them, they're looking at their hardware and they're looking at all their IT infrastructure and saying, well, how can we do better with this? How can we be more efficient? And what's nice is we're kind of at an interesting era as the open source communities around mainframe are growing, especially with a project like Zoey, which was really designed around the fact of how can I make my mainframe data more accessible through the rest of the enterprise? And what it has kicked off is this larger movement here of, well, well, geez, now I can use mainframe as a part of my end-tier architecture for applications. Maybe in some areas, I might actually think this might be a better place for parts of my workload, because we're moving away from those monolithic applications to services, multi-teers, things of that nature. What does that mean for a downturn? It means that a company is able to go back and look and say, I can do these workloads more efficiently here. I have the benefit if I don't want to learn ZOS, I have Z Linux that I can run on there, which is just like any other Linux, and I can shift things around to better optimize what I'm doing. So it fits into that whole thing. A company takes a step back and says, what is our core competencies? What are we here to do? What do we best staff to do? And how can then we use the infrastructure we have to do that appropriately? And I think it ties in perfectly. What kind of challenges when it comes to purely terms of cost that you are seeing there? And then we'll talk a bit about impact on mainframe ecosystem. You did touch upon that, but I just want to specifically talk about cost. I think companies are looking not just at their personnel, but the software and services that they support and what makes sense. Looking at subscriptions or looking at different software they purchase and they figure out, is this a good use across the business for us? Is there other tools that we can use much more efficiently? I would imagine any of the subscription-based software services out there are probably thinking about that as they plan their year out here that they're going to probably see a significant amount. They're going to see more than normal churn as companies are going to try to reduce onto different platforms and not have so much broadness. So I think that's going to be a part of there. I think the other half is the company is going to look back in the IP that they have built internally around software and services. They're going to say, how much of this do we really need to be the only one holding up the ship? That's where I'm anticipating new things coming out in open source because companies are going to realize, let's get a couple other people working on this. This should be a commodity piece here in a couple of years. Let's get ahead of the game and start doing this. A great example is actually one of the other foundations I work with in the Academy Software Foundation. They recently announced a project called Open Review Initiative, which has contributions from Sony, from D-NAG, from Autodesk of their various review and approval tools for motion picture workflows where the goal is, is they're going to contribute their tools into there, but then they're going to pull the best pieces out of all of that and make a canonical tool that the industry will eventually standardize on. That's the sort of things that I would start to see happening in this. I would not be shocked if we start to see this in the mainframe space or we have a couple of the big vendors come together and say, I have this tool, I have this tool, let's open source them and then let's use that as an exercise to figure out what are the best features of both, what are the key pieces of both, and then build something that the industry can build upon. What you're saying is that we'll see kind of an addiction and do it yourself for not invented here syndrome and folks will try to leverage open source in a way because as you rightly said, so we'll see a lot of growth and adoption of open source as well there. You're going to see people that are going to retrench, you're always going to have exception to that, but I think the people that have been through this cycle before know that this is where the opportunity that you can think longer ahead and you have other competitors that are in sort of similar positions. Like on the financial side, you tend to see a lot of mergers and acquisitions happening when the economy is sort of a low point because of a lot of the cost structures these companies that become easier to, you know, cheaper to pick up. It's a similar dynamic here, you know, these companies are retreading, they're all, I don't want to say they're in desperation mode, but they're certainly more actively interested in how to collaborate to be cost efficient and that ends up being an additional driver towards all of this. How is the open mainframe project helping the ecosystem solve this issue, which is, you know, once again, becoming more cost-efficient, optimizer resource, and of course you folks do open source. So it's a very well placed project. There's always the one half of the technical collaboration. We see projects like Zoe, Fei Long, you know, a number of our other ones, which are getting more mature. They're getting more adoption. They're really starting to stride and we're starting to see customers using those and that's a good sign there. The other half is we have projects that are more focused in our educational areas like the COBOL training course and mainframe open education, which are helping around the skills aspect. As these companies know, they're still going to need, you know, even though we're in a non-economy that doesn't take away the training aspect on the flip side, there's also people are going to be looking to re-career and having the training available and being able to use that as a way for people to identify talent is going to be a huge part as well. So I think that's a piece that we're seeing there. I think another and I think our mentorship program kind of flows into there nicely as well. That's going to be something that's just going to continue to grow for us. And I think a third wheel, which is one that we talked about at open mainframe summit and is slowly but surely been kind of iterating in the background is the mainframe is the modernization working group that has been launched. And where I see that coming into help here is not only just of the tactical of helping sort of redefine the market and add a lot of clarity on this, but as companies are looking to be more cost efficient, they're seeing a lot of mixed messages of how they approach their mainframe infrastructure with that and being able to have some true thought leadership based upon research, based upon where the market is, is a huge aspect. And those are really long tail things that will build out over time. But in the short term, they become opportunities to kind of help focus that work in the area of cost cutting or cost optimization because that's frankly, you know, when you hear the term modernization thrown in the mainframe, it's kind of has been considered a little bit of sort of that dirty word of meaning, you know, you're getting rid of something. Right. And the reality is, is it's probably that's, that's kind of like leading things way too far down the road. What it really is, is companies realizing they need to get modern, but they need to figure out with being modern, how do they work efficiently? Because that is part of modernization is efficiency. A downturn like this is just a driver for that. It kind of accelerates things. So I see that as another way these things are going to come together. What can resources are developed from the open mainframe project that can help organizations, companies, other players to kind of tame this, you know, beast that you're looking at right now? We have, like I said, a lot of our technical projects are great times for companies to go back and invest. Both folks that are vendors that are bringing products to market in the mainframe space. This is an opportunity for them to go and and look back and say, hey, is this is this a way that we can bring higher quality products to market at a lower cost by building on top of something or leveraging something like a Zoe, for example. So I think there's going to be one aspect there. Another angle of it is how can we improve sort of our dev ops efficiency as we bring in, you know, as we know, we have a number of legacy tools, you know, cobalt, things like that out there. And there was a great interview I think you did with bank data a few months ago that really tapped into that.  Go back and listen to it. I think it really talked about not just modernizing the tools, but also modernizing how the teams are built and how the training and how your approaches are and all of the things that they were talking about all were things that came from the open mainframe project, cobalt programming course, you know, cobalt checks, Zoe, all of those things. So I think that's going to be another angle of it. And then I think sort of I would see a third in there is looking back at the mentorship half of things. This is an opportunity for, you know, especially at our member companies, but folks are looking to drive stuff in the open source realm to work with the up and coming students. And look at that as sort of a way of bringing new focuses into their workforce. And the mentorship program is a great place for that. John, thank you so much for taking time out today and talk about this topic. And as usual, I would love to have you back on the show. Thank you. Absolutely. Thank you.


Approximately 25 fisherfolk from the Souffre area participated in a consultation headed by the Minister responsible for fisheries honourable Alfred Prosper and the parliamentary representative for Souffre honourable Emma Hippolit to discuss on what challenges and concerns they face and what intervention may be required from the Department of Fisheries. Minister Hippolit has given the assurance that her commitment remains working with the Department of Fisheries to resolve the myriad of issues fisherfolk in the Souffre area face. I gave them a commitment that I will address some of the issues that they've raised but I felt it was formal to give them the respect so that they can meet the Minister responsible for fisheries, let them add their views and their concerns and we sit here and we hide the Minister making some commitments and saying how as a government we will attempt to address the issues impacting fishers in Souffre because in Souffre they've got some specific problems as well as fishers in the entire country. Some of the main issues highlighted by the fishermen include the deterioration of the coral reefs, the high costs of deploying fish aggregating devices, commonly referred to as fads, as well as the illegal use of gillnets within the reserves. Minister Prosper emphasised the importance of involving other sectors impacted by the fishing sector, such as tourism, in finding solutions to issues confronting the marine environment in Souffre. Our fishermen work very hard, they take high risk, they go out to sea and most times they don't make much but yet there is very little coverage in terms of health insurance if they are sick or if they get injured at sea or if they are lost at sea, very little or no benefits are affordable for them. I am also concerned with, based on what was mentioned today, the issue of sale of fish. I was not aware that the issue of moving the sales depot from the centre of Souffre to this area would have impact the fishers and this is something I believe must be addressed as soon as and I am looking forward to my ministry working with the fishermen of Souffre, not just Souffre but the entire country, to see how we can work with them and assist them and to make lives better for them. Minister Prosper also affirmed his commitment to assisting sector agencies such as the Souffre Marine Management Authority, as the Ministry of Agriculture, Fisheries, Food Security and Rural Development works to improve the livelihoods of all those affected by the sector. From the Communications Unit of the Ministry of Agriculture, I am Anicia Antoine reporting.


Speaking with some finance folks, I mentioned the reason why they've not adopted Power BI if they are reporting. Some of them is thinking there's something in finance related calculations that they can't achieve in Power BI. And looking at some of those, I mentioned focusing as one of them. In Excel, it's pretty much straightforward, pretty much easy to do focusing. When you have your data modelled correctly, your calculations are running correctly. That's pretty much direct to achieve. But in Power BI, they've tried to exploit different same options where they would be able to forecast their data into the future. But before we go into that, for some of those that might be watching this video and we are not from a finance background or related studies, forecasting simply implies that we are trying to use our data to look at the future. We are looking into the future to say what is possible in the future. We might have sales. We have sales data running from probably January of the year till July of the year. So, presuming at the moment when July. But looking at that, we want to use our reporting tool to tell us what's possible from July down to December, what is the likely pattern we would observe in our sales. That is what forecasting is about. Forecasting is a way of learning from what pattern already exists within the data and using that to predict, sort of predict what will happen in the future. So, when we come to reporting, one is before you can forecast, you must have some amount of data that has some data attribute. So, if you have data and the data is not tied to any data attribute, obviously, you cannot do it forecast. So, you need to ensure that you have data and the data is tied to some dates. So now, this is Power BI and one of the things we know is that when we want to visualize time-based reports, we need to use a specific chart. You don't just jump into this. You want to visualize something that's related to date and then you select a pie chart. A pie chart will work for that. Or you select something like a map. It doesn't study. So, you want to ensure that you're picking the right visual. One of the visuals that are pretty excellent for visualizing time-based report or doing time-based reporting is your line chart. So, I have a place order for your line chart here already. So, just go onto populist days. I have it clicked on. So, I would have select my year and I will select my revenue. So, I'm visualizing my revenue by year. So, in 2013, we made this amount of revenue in 2014. 2015, that's what we made. And 2016, that's what we made. So, this is typically four years of data. What if we want to now project into the future to say, how much is it possible that we begin to make after 2016? So, what we would do is you have your chart selected like this. Ordinaryly, on your visualization screen, you see that depending on the chart that you have selected, you would say this button here, that's for visuals generally, then you say a format your visual icon. But because this is a line chart and some other related chart, you get to say this third one, which says add folder analysis to your visual. So, I would select that. And now from here, there are a lot of options, excellent options that we can bring in from here. Statistic related options. But the core of this video is not to look at the entire option. So, I just want to focus on the focus bit. And the focus, you see, we have a group for focus right at the bottom. It is turned off by default. So, before you use the first thing you want to do is to turn it on. So, I'm going to turn that on. But still nothing has been seen here. So, I would expand it. So, once I expand on this, you see that some now I have a sort of a projection, a different outlining out of my line chart. So, my line chart, the actual values are blue line and then there is something different going just off with some shadows around it. That is the focus side. And if you look at this chart very well, we'll notice that our data stopped on 2016. That is the actual. So, we now have data for 2016 to 2026. So, that's 10 years of focus already. And what it's saying is, by interpretation, is that what is expected is that our revenue should continue to grow in this pattern. And this has only been learned from what we have in the actual data. And the second thing to note, if I stay on 2018, for instance, you will see that we have the upper bound and the lower bound. The forecast is the actual line in between. But what it's saying is there is every tendency that our revenue figure would resonate between the two bounds. So, it's either it is higher than the forecast value itself, or it's lower than the forecast value. But it's projected that it's going to be within the shaded area that we can see. Sometimes you don't want to have 10 years of focus. 10 years of focus might just be too much of a prediction to make. But especially when you don't have enough data to fit into that and you're not running machine learning models. So, you may sort of want to reduce the number of years. And in a way that might tell on the accuracy of what you're looking at as well. So, the way to manage that under your focus group, you come here to where you have the focus length. So, it says 10. So, if I want to reduce this to 5 years, I'll just put a 5 here. And I'll come to this button and say apply. So, when I say apply, it reduces my forecast to 5 years of focus. And we'll say that we have less data to look at and then we have more space to look at on our line chart. A couple of other things you may want to do to say that, yeah, we have a confidence interval. This is some pretty much a statistical thing. Probably we have some videos that will address some statistical thing that we have on the analysis. But the confidence interval, the confidence level, they all are somewhat around. How confident are we? What level of confidence have we deployed in this our forecast? So, 95% confidence, 99%, 97% what level of confidence is feeding to this and what what does that imply? So, maybe we have something to talk to that in some of our next surveys. But you want to do some formatting on the forecast line, most especially because you are bearing in mind your users. You don't want them to presume that this line is continuous and this still talks about the actual amount you have made in the business. No, you don't want to confuse them. So, one of what is recommended is that your forecast is not actual. So, you want to make it dotted line. And this is from the standard as well. So, I come here to the style and then I just make it maybe a dashed line. So, it's not continuous. Yes, something like this. This is pretty much different from what we've seen from the actual lines. Actual line is continuous, solid. But some of the forecast is not solid and it's not continuous. You may also want to make it a bit more transparent or depending. So, you want to make it lighter or however just to ensure that people, your report users, they are not confused as to what they are saying. So, pretty much simple, pretty much direct how to build forecast into our Pavia report line chart specifically. Thanks a lot. I hope you found this helpful. Let's stay tuned for our next please.


What is up everybody? This is Chris from the rewired soul where we talk about the problem, but focus on the solution. And my channel is a mental health channel.  So if that's something that you're into, please feel free to hit that subscribe button, turn on the notification bells because I make a ton of videos to help you out. But we're back here today to talk about Logan Paul. I know, I know, I know everybody's talking about Logan Paul. I get it, but this this topic keeps coming up and it's like it's bugging me. What are Logan Paul's motives? I see it all over the place. Everybody is questioning his motives like I made my video yesterday and I've been watching. I follow a lot of different YouTube commentators and stuff. Just for my own research, see what's happening in the community, what other people think.  They're humans. We love drama. We love to hate people. That's what we do. We hate forgiving people. We love to hold grudges like, ooh, it just fuels our soul to hold a good grudge against somebody. And just so many commentators out there are talking about how, you know, what are his motives? What are his motives? What are his motives? Like I happen to stumble across this new YouTube commentator. He's actually pretty good, but when he did his Logan Paul video, I was kind of like, I don't know. But anyways, his name is quite, uh, if you're into this stuff, check him out. But anyways, here's a clip from him. But my point still stands and I'm going to keep repeating this till we get to the end of the video because I consistently keep thinking about it as I keep going through this video. I just can't help but question Logan's motives. I want to believe he's changed so bad. Okay, next, then we have another one. I just sometimes I look in my suggested tab and this guy popped up. I've never seen him for, uh, his name is Jack May. Again, really, this is going to do wonders for your public image, man. In fact, can we get a shot of Logan looking rather full lawn? Do you know what I mean? Looking sad Logan. And if you can include it like a gulp to show that you really understand the gravity of the issue now that I'd be perfect, perfect PR. Keep going. Okay. So, so these are just two clips, but there are hundreds, if not thousands of videos on YouTube right now of people questioning Logan's Paul's motives. So what I'm here to do as a mental health channel, I do a lot of videos on psychology as well as mental health, as well as the way our brains work. So I'm going to talk a little bit about evolutionary psychology in this video because I'm whenever I make a video, I'm trying to explain to you all how your brain works. When you understand how your brain works, you could start making better choices with what you do rather than being on this autopilot and pretty much, you know, to be honest, fueling more hatred in our world.  But like I'm I have this crazy idea of the world becoming a better place. So I make videos like this. But anyways, so let's talk about it. What are Logan Paul's motives? What are his motives? Like quite said, he talks about questioning his motives over and over and over again. You will see it just about other one. And to put it very bluntly, who cares? Who cares? Who cares what his motives are? So what you're looking at right now is a screenshot of how many views Logan Paul's videos got. Logan Paul's video has 14 million views in 24 hours. 14 million 14 million people saw a video bringing awareness to mental illness, to suicide, to what you have to do to get help. 14 million people saw this and the most that people are talking about are what are this guy's motives? Like that is one of the biggest problems in society today is even when somebody is trying to, you know, or even when something good happens, we immediately have this negative bias where we immediately look towards the bad. That's just one of the ways our brain works. Now, I question this a lot and there's actually some scientific reasons behind this. Why do people always want to know what the motive is? Why are people always questioning motives? Well, evolutionary psychology does explain this. So evolution, evolutionary psychology is a branch of psychology where they explain how our modern brains work based on things that our brains had to do back in prehistoric days. So in this aspect, asking ourselves, why do people care what somebody else's motives are? And the reason being is, let me paint the picture for you back in the hunter-gatherer days when you had different tribes and things like that. It was important for you to look a certain way and to put off a certain kind of persona to everybody. So let's say, for example, dude over in the tribe next to you, he pulls a fast one over on you. He tricks you, right? You don't know what his motives are, but you give him the benefit of the doubt. Well, if that guy pulled a fast one on you, who knows what the people in your tribe are going to say or the people in the next tribe are going to say?  So based on that, the way our brain has evolved, it still holds on to that. We're always questioning people's motives because of this very primitive instinct that we have. But fast forward to 2018, Logan Paul is not going to destroy you or your tribe based on his motives, but so many people don't understand how their brain works that they go and autopilot and they're like, I need to make a YouTube video questioning Logan Paul's motives. Like if we really take a step back, if we take a step back and we say, how does this affect me? How does this affect me personally? Like the question nobody's asking, the question nobody's going a little bit deeper, just a little bit deeper after asking what are Logan Paul's motives, the question after that is, why does it matter? Why does it matter? Why does it matter what his motives are for this video? Because I mentioned in my last video about Logan Paul's apology, like only time is going to tell. I mentioned it in the video I did my reaction video. Like we don't know. Like we have to see if he changes, if he becomes a better person. But at the end of the day, at the end of the day, currently on January 25th, 2018, 14 million people have seen that video. 14 million people, people who struggle with depression, people who struggle with suicidal thoughts, which is a minority, a minority of the people who watch that saw this and were able to get some kind of help or some some kind of resources. But the majority of people out there, the majority of 14 million people were able to learn a little bit more about the struggle of what people with suicidal thoughts go through, what people with any form of mental illness go through. And in my in my realm of being a mental health advocate, that's a win. That's a win.  But at the end of the day, 14 million people so far, this number still probably going to grow 14 million people so far either got help or learned practical ways to help somebody else. For me, that is definitely a win. All right.  If you like this video, if you agree with me, give it a thumbs up and do me a favor, share this video with some other people too because we need to start asking ourselves why we're questioning so many people's motives. Okay, we're not cavemen anymore. All right. So it's important to kind of understand that. All right. So again, if you like this video, please give it a thumbs up. And again, if you are new here, make sure you click the little round subscribe button right below this little box. I'm always making videos to help you out with your mental health and we just hit 1000 subscribers. So don't you want to join? Don't you want to join up with us? But anyways, click or tap on one of those thumbnails, check out some other videos. I love you and I'll see you next time.