It goes without saying that the role of the library in providing access to digital resources and data, as well as helping to navigate science data sharing and usage, is crucial to students and researchers alike. Data sharing encourages more connection and collaboration between researchers and librarians, which can result in important new findings within the field but also comes with its own challenges which need to be navigated and addressed.
Join this one-hour webinar presented by Springer Nature, Choice, and the ACRL, where our guest speaker Prof Fatos Xhafa from the Technical University of Catalonia (UPC), and Book Series Editor of Lecture Notes on Data Engineering and Communications Technologies will be discussing the following topics:
– Why is scientific data sharing of importance to researchers?
– What are the challenges and opportunities for researchers and libraries?
– Managing data science projects in practice
– Future trends in data sharing
Learn more about the event and speaker: https://www.choice360.org/webinars/academic-library-support-and-services-for-the-research-community-through-scientific-data-sharing/
Register for upcoming Choice-ACRL webinars: https://www.choice360.org/media/webinars/
Timestamps:
00:00: Technical overview and speaker introduction
02:54: Introductory words and webinar outline
05:26: Why is scientific data sharing of importance to researchers?
14:34: What are the challenges and opportunities for researchers and libraries?
30:03: Open data projects in practice
35:11: Future trends in data sharing
41:53: Future trends in open data
46:26: Final words
49:20: Audience Q&A
Captions provided Zoom’s automated AI captioning.
Sabrina Cofer: Okay. Good morning, everyone. My name is Sabrina Cofer, and on behalf of Choice and ACRL, I’d like to welcome you to today’s program, Academic Library Support and Services for the Research Community through Scientific Data Sharing which is sponsored by Springer Nature. This session is one in a series of sponsored webinars from Choice and ACRL that addresses new ideas and developments of interest to the academic library community.
Sabrina Cofer: And I’ll just put a couple links in the chat for where you all can register for upcoming Choice-ACRL webinars and watch previous choice webinar recordings Sabrina Cofer: before we get started I’d like to point out just a few features of the Webinar software.
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Now, I’d like to introduce our speaker for today. Professor Fatos Xhafa
Sabrina Cofer: Fatos Xhafa, PhD in computer science, is full professor at the Technical University of Catalonia, Barcelona, Spain. He has held various tenured and visiting professorship positions. He was a visiting professor at the University of Surrey, UK, Visiting professor at the Birkbeck College, University of London, UK, and a research associate associate at Drexel University, Philadelphia, U.S.A.
Sabrina Cofer: He was a distinguished guest professor at Hubei University of Technology, China, for 3 years and Professor Xhafa has widely published in peer-reviewed International journals, conferences, workshops, book chapters, edited books, and proceedings in the field.
Sabrina Cofer: He has been awarded teaching and research merits by the Spanish Ministry of Science and Education by IEEE conferences and best paper awards. His research interests include IoT and cloud-to-thing, continuum computing, massive data processing and collective intelligence, optimization, security and trustworthy computing and machine learning among others.
Sabrina Cofer: And with that we are ready to get started. So I will hand it over to Professor Xhafa. Fatos Xhafa–BARCELONATECH: All right. Yeah, thank you, Sabrina, for the introduction and for preparing everything for this webinar. Fatos Xhafa–BARCELONATECH: Thank you, Ashley, as well for your help and and assistance.
Fatos Xhafa–BARCELONATECH: so I received Fatos Xhafa–BARCELONATECH: request from actually Springer. Fatos Xhafa–BARCELONATECH: Germany, to hold these Fatos Xhafa–BARCELONATECH: webinar regarding the collaboration of libraries, services, and research community about the scientific data sharing right? So Fatos Xhafa–BARCELONATECH: that invitation obviously was very interesting to me because my background is from computer science.
Fatos Xhafa–BARCELONATECH: And I’m familiar with the scientific research and scientific data sharing. But it was a little bit more challenging, and I wanted to see how this can be done in conjunction and in collaboration with the the library or the people from the library’s community. Right? Fatos Xhafa–BARCELONATECH: So. I have organized
Fatos Xhafa–BARCELONATECH: the Fatos Xhafa–BARCELONATECH: the the presentation of this webinar into 4 parts. Fatos Xhafa–BARCELONATECH: first, I’ll try to give you some reasons. Why is the scientific data sharing of importance to researchers? Then I’ll list some of the
Fatos Xhafa–BARCELONATECH: challenges both research and development challenges and but also some of the opportunities for researchers and libraries. In this context. then, I’ll give bring to your attention some examples of open data science projects from all over the world.
Fatos Xhafa–BARCELONATECH: And at the at the last part, I’d like to discuss some future trends in open data most importantly. Future trends that has to do with artificial intelligence. Chat Gpt, and and Fatos Xhafa–BARCELONATECH: you know this current discussion, which also affects the open science and and open data. Right?
Fatos Xhafa–BARCELONATECH: So at the end I will have. As Sabrina said, a question and and an answer, so please feel free to to to ask your your questions.
Fatos Xhafa–BARCELONATECH: To start with, let me just give you some of the reasons which why the scientific data sharing is importance to researchers. So let me start by saying that
Fatos Xhafa–BARCELONATECH: scientific data sharing has been always very important. For for for their scientific communities, however, with the fast development of Internet Internet technologies.
Fatos Xhafa–BARCELONATECH: Scientific data sharing has become very important and also possible. Because now we can have a collaboration through scientific platforms. And then data sharing is is possible. Right? So some of the reasons why is data sharing important are, for example, that
Fatos Xhafa–BARCELONATECH: a large part of the research, as you know, is empirical research, which means that
Fatos Xhafa–BARCELONATECH: it requires verifiable evidence obviously to to have that empirical research sustained and the claims to be verifiable and and sustained either in a quantitative or in a qualitative studies. It is important to have collection of data.
Fatos Xhafa–BARCELONATECH: So whenever you, you, someone plans to have an empirical research. The one of the things in the checklist of that study should be, what collection of data shall I shall I use for sustaining the claim right? Fatos Xhafa–BARCELONATECH: A second. The reason would be that any Nobel research method that
Fatos Xhafa–BARCELONATECH: claims to to present an improvement beyond the state of the art need to to use data. Fatos Xhafa–BARCELONATECH: and that data should be shared with others so that others can use exactly the same data. To see if how do. The new research methods stand
Fatos Xhafa–BARCELONATECH: with regard to the new state of the art right? Fatos Xhafa–BARCELONATECH: Additionally, as you know, any research methods is never conclusive. So this is an research.
Fatos Xhafa–BARCELONATECH: Methods are continuously under the, you know, scrutinity. They are improved and they are analyzed, and they are reviewed. So in order to find the the. Fatos Xhafa–BARCELONATECH: the strengths or weaknesses of research methods is necessary to use the dataset. For example, a research method could be performed well
Fatos Xhafa–BARCELONATECH: in some data set, but might may perform poorly on other data sets right. So datasets become a key ingredient to evaluating the the strengths and the weaknesses of the research methods.
Fatos Xhafa–BARCELONATECH: This is. These 3 reasons are kind of a general setting. Reasons, however, in the context of more specific research, such as artificial intelligence or machine learning. Fatos Xhafa–BARCELONATECH: datasets are of a paramount importance. Fatos Xhafa–BARCELONATECH: as you know, in artificial intelligence and machine learning. Yeah, data sets are are
Fatos Xhafa–BARCELONATECH: key to to training and to testing these methods. So without datasets artificial intelligence of machine learning methods would be impossible to you know, to to be to be trained and tested, and to work in practice right?
Fatos Xhafa–BARCELONATECH: In some cases. We it is, you know. We would like not only to to see what are common patterns in the data. But we also like to see hidden patterns from the data. Right? So in that case.
Fatos Xhafa–BARCELONATECH: extracting models from the data set is very useful, because it tries to uncover even patterns that are not directly seen from from the data right? And to to Fatos Xhafa–BARCELONATECH: conclude, with this, I mean, there are more many reasons. But with these reasons, as you know, research is an incremental process.
Fatos Xhafa–BARCELONATECH: So Fatos Xhafa–BARCELONATECH: we have research studies that make a snapshot. Now let’s say, of a phenomena.
Fatos Xhafa–BARCELONATECH: But we have research studies that make, you know. Give a perspective on the short term midterm on the long-run, right? And in each phase of this incremental research, which is an actually a never ending process, we need data sets to support. So in the same way that the research methods.
Fatos Xhafa–BARCELONATECH: research technology supporting the research evolves in the same way. Also the data sets and data and methodologies for collecting data preparing data, etc., evolve over time. Right? So there are
Fatos Xhafa–BARCELONATECH: plenty of reasons of why the scientific data sharing has become of such an of importance to to researchers nowadays. Right? So now, obviously, all these reasons
Fatos Xhafa–BARCELONATECH: stand from the perspective of the scientific data sharing right? So now, our main point here is what libraries can do. And how can libraries define their role in this scientific data sharing right?
Fatos Xhafa–BARCELONATECH: So to that. before I enter into that, let let me also mention that whenever we talk to Fatos Xhafa–BARCELONATECH: scientific data sharing, actually, we understand open data. Or we, we understand open science, right? So as you know, open science and open data.
Fatos Xhafa–BARCELONATECH: They are perfectly orchestrated, because whenever we we talk about open science, there is and should be open data. And whenever there is open data that should enable the the open sign right? So there is a commonly understood and and accepted classification or taxonomy of open science into different branches
Fatos Xhafa–BARCELONATECH: from open access, open data, open reproducible research, open science, and and etc. And, as you see, I have marked here one of the branches. Actually, the second is actually the open data.
Fatos Xhafa–BARCELONATECH: So that’s absolutely fundamental to make the open science. And one of the main reasons besides, the reason that, I said, is that when you make the data open that enables others.
Fatos Xhafa–BARCELONATECH: you know, to make to use the same data set either with the same method or with different methods, and to sustain the reproducible research. So if you look at that classification of the opalate in the, in the, in the right branches. Then you will see
Fatos Xhafa–BARCELONATECH: among others, the open big data which means that very large data sets at the scale of the Internet can be nowadays are available for use by scientific community. We need to agree what we understand by an open data definition. Actually, later on in this presentation, I’ll talk about
Fatos Xhafa–BARCELONATECH: the fair principles we that guide the open data definitions. And, of course, as you know, open data journals. Nowadays. Journals from Springer, Elsevier, and major publishing companies do support open data link to to the research journals. Right?
Fatos Xhafa–BARCELONATECH: And not less important. Nowadays we talk, we’ll see more and more initiatives related to open data government, open open government data. Right? So and this is really an excellent use that many governments around the world, and also public institutions are contributing. So
Fatos Xhafa–BARCELONATECH: the the open science is actually a paradigm, a paradigm shift in scientific research. In what sense, in the sense that Fatos Xhafa–BARCELONATECH: the research understood as as a
Fatos Xhafa–BARCELONATECH: long term, collaborative process in different phases. Whenever it is done under the open size, up open science paradigm, it means that every stage of that research is supported by the open science paradigm. Right? So the current, as I, as I’ll explain a little bit later. Cloud ecosystem!
Fatos Xhafa–BARCELONATECH: The digital cloud ecosystem makes possible that these open science can be fully implemented in practice. Fatos Xhafa–BARCELONATECH: So now, once we have seen some of the reasons that why this scientific data sharing is important to
Fatos Xhafa–BARCELONATECH: scientific community and to research overall. Let me discuss, some of the challenges and and also the opportunities for both researchers and the libraries in in this field. Right? So, as I said earlier.
Fatos Xhafa–BARCELONATECH: the open data and open research have have undergone a very fast transition due to this digital cloud ecosystem. So you know, in a very few years we are seeing how?
Fatos Xhafa–BARCELONATECH: You know, the digital cloud ecosystem is embracing everything. Therefore, the open research and and and open data are not an exception. Right? And, on the contrary, actually, the digital cloud ecosystem is an active, very great news for
Fatos Xhafa–BARCELONATECH: the open research and the open data set, because open data because it supports it can support the open science at any stage of the of the research, right? So some of the researches that are listed here is that the very first one is to make the data open
Fatos Xhafa–BARCELONATECH: first, we know that not everybody can collect data. What does that mean means that Fatos Xhafa–BARCELONATECH: collecting data is not a straightforward process. It requires people. It requires technology, it requires money, and it requires time. So
Fatos Xhafa–BARCELONATECH: is, some institutions have more opportunities or possibilities than others. Right? So by making the data open, what we actually do is to make to give the possibility to others that are not able to collect the data, to use that data for their own research. Right? So the the key challenge here is how to make the the data open to the research community.
Fatos Xhafa–BARCELONATECH: One good thing that open data is as simple as
Fatos Xhafa–BARCELONATECH: posting a data set in a web page. But actually, there are many challenges related to the open data. So it’s not that straightforward. what we when we talk about open data. As I’ll discuss a little bit later, we talk about data, open data that comply with a number of quality standards.
Fatos Xhafa–BARCELONATECH: and therefore what we really need is open data is open data that is useful for the research community at large. But the very first point of is how to make that data open and available to the whole community.
Fatos Xhafa–BARCELONATECH: So how can libraries do I believe that this is an opportunity for the libraries which really can help? Because Fatos Xhafa–BARCELONATECH: libraries have always been a place to find information, as we know. So libraries have a lifetime of centuries.
Fatos Xhafa–BARCELONATECH: and and they and and as we know they were the first place where to find any information. Whenever II would like to.
Fatos Xhafa–BARCELONATECH: for example, find an article or a book, the first thing I do is I go to my library digital version of the library of my university, and I and I and I check if I can access that that resource right away. Right? So in the same way that libraries have been able to
Fatos Xhafa–BARCELONATECH: be a place of information over centuries, they can also extend their role to include as part of that information, also the open data collections. Fatos Xhafa–BARCELONATECH: But of course Fatos Xhafa–BARCELONATECH: it’s not as easy as to have a collection of books or a collections of journals, even
Fatos Xhafa–BARCELONATECH: physical or or digital versions. Because you know the transition from the physical versions, let’s say, of Fatos Xhafa–BARCELONATECH: collection of books series. Fatos Xhafa–BARCELONATECH: it has been easy to transit to the digital version.
Fatos Xhafa–BARCELONATECH: But now, if if we have to have the open data collections, we first need to define that concept of the open data collections, and there are plenty of issues behind that. So there are security issues.
Fatos Xhafa–BARCELONATECH: There are privacy issues. And and most importantly, they are authenticity data issues, because, within a large data collection, there could easily be introduced fake data which would obviously undermine the the research activity.
Fatos Xhafa–BARCELONATECH: And of course there should be compliance with ethical responsibilities of data, sharing inclusiveness issues, gender issues, etc. Right? So
Fatos Xhafa–BARCELONATECH: there are issues. There are concerns, of course, but I believe that there is and an opportunity for libraries to help the research community through extending their collections of information to open data collections. Fatos Xhafa–BARCELONATECH: The second, and perhaps from a technical perspective,
Fatos Xhafa–BARCELONATECH: perspective from a technical perspective. The most important challenge is implementing the fair principles. So the fare stands from finability, accessibility, interoperability, review and use of digital assets. Right? Fatos Xhafa–BARCELONATECH: So the research community has come to the understanding that any open data
Fatos Xhafa–BARCELONATECH: obviously is useful when it is implemented to be so, to serve at the long run. Fatos Xhafa–BARCELONATECH: and for an open data to serve at the long run, it should implement the fair principles. Fatos Xhafa–BARCELONATECH: Now,
Fatos Xhafa–BARCELONATECH: from a technical perspective, this is possible because the cloud digital ecosystem makes possible to implement findability. So you can search and find the open datasets. It makes possible accessibility under different accessor roles. It makes possible interoperability, though, as I’ll discuss a little bit later.
Fatos Xhafa–BARCELONATECH: this interpretability issue is perhaps one of the weakest points nowadays, and their use of of the of the open data sets and the digital assets in general. Right? So the question is, what can libraries
Fatos Xhafa–BARCELONATECH: can help? How can libraries help here, or what the opportunity can we identify here for the libraries? Well, as I said before, libraries has a huge experience in organizing physical and digital collections. So Fatos Xhafa–BARCELONATECH: actually, what we need is the experience from the libraries and translate this experience to
Fatos Xhafa–BARCELONATECH: create or or prepare organizational procedures. Sorry for the typo. II meant organizational procedures for the open data collections. So Fatos Xhafa–BARCELONATECH: instead of
Fatos Xhafa–BARCELONATECH: trying to, you know to guess how we should organize the open data collection. Perhaps we can knock at the door at the library of the People, I mean at the libraries and ask their experience on the organization of physical and digital collections, and then apply those procedures to perhaps redefine in some way to the open data collection. Right?
Fatos Xhafa–BARCELONATECH: As you can see, here is Fatos Xhafa–BARCELONATECH: a picture on the right. So actually fair implementing the fair principle is not a just one Fatos Xhafa–BARCELONATECH: shop Fatos Xhafa–BARCELONATECH: procedure. So it’s actually is. A day is a cycle. So we have a never ending cycle. Somehow, because, as I said.
Fatos Xhafa–BARCELONATECH: data open are useful when they are, they can serve at the long run. So we collect, we sense the data we collect, or we collect the data. We have to prepare and curate the data. We may enrich the data later. And we share the data right? And then this cycle is continuously
Fatos Xhafa–BARCELONATECH: implemented because we sense, you know, data from the E health, we data from the industry data from the environment, etc., etc., right? And and this yields to create the creation of this open data collection. Right?
Fatos Xhafa–BARCELONATECH: The third challenge is actually. And this is again, very critical is to ensure the data data quality dimensions. So
Fatos Xhafa–BARCELONATECH: collecting data nowadays. It’s not difficult. I mean, you can have and a number of sensors out there, or you can have a number of cameras, and then it’s easy to collect the data is that data reach
Fatos Xhafa–BARCELONATECH: it depends. Is, does that data? Complies with quality standards? Not necessarily so. Defining the data as a new oil, not only for the businesses, but also for for the research community at large. Fatos Xhafa–BARCELONATECH: Data is useful if it has quality.
Fatos Xhafa–BARCELONATECH: So, and there are at least 5 dimensions that Fatos Xhafa–BARCELONATECH: define if the data really has a quality or not. So that is a timeliness complex. So we don’t have gaps into the data validity. So the data has no errors. Consistency, which means that. The data
Fatos Xhafa–BARCELONATECH: patterns or the data collections is done continuously, continuously, using same procedures, no changes in the midst of the data, collections or data, preparation, etc. And of course the accuracy right? So Fatos Xhafa–BARCELONATECH: this is perhaps one of the most difficult things.
Fatos Xhafa–BARCELONATECH: this can be done, of course, mostly by the technical expertise of the research community. Fatos Xhafa–BARCELONATECH: I don’t think that libraries are Fatos Xhafa–BARCELONATECH: I mean, do have the expertise to to ensure the data quality dimensions because the complex needs validity, consistency, accuracy are more technical.
Fatos Xhafa–BARCELONATECH: But libraries have a huge experience in ensuring the quality standards of digital collections what is otherwise known as data curation. Fatos Xhafa–BARCELONATECH: So if you go to a library, you they can define. For example, this is a high quality collections Fatos Xhafa–BARCELONATECH: of books or of journals, because
Fatos Xhafa–BARCELONATECH: it has been curated Fatos Xhafa–BARCELONATECH: so means that you you don’t see gaps
Fatos Xhafa–BARCELONATECH: you you you see that the whole series of the books or of the journals is complete, and there are annotated information on that book series, or collections of documents, etc. Right? So this data curation expertise, I believe, is very interesting and very also helpful from for the research community
Fatos Xhafa–BARCELONATECH: and the collaboration between both the research community and the libraries can, can, you know, benefit in in making to ensure the the data quality dimension? Right? So
Fatos Xhafa–BARCELONATECH: how can this be done? Obviously, we, we need to promote the multidisciplinary and of course, cross disciplinary teams with librarians and researchers and developers to see how these data curation expertise from the collections in the libraries can be translated into the research community. Right?
Fatos Xhafa–BARCELONATECH: We do have a weak point here, and actually is that there is a lot of time behind all these procedures. and unfortunately, universities or institutions in general do not recognize enough the credits to researchers for
Fatos Xhafa–BARCELONATECH: open openly sharing their data and working as data curators. Right? So we we really need to Fatos Xhafa–BARCELONATECH: insist and promote that this, you know, dedication from both researchers and the libraries in in data sharing and data creation. Right?
Fatos Xhafa–BARCELONATECH: As a fourth challenge. I would like to mention that open data management is really costly. It is complex. Fatos Xhafa–BARCELONATECH: Implementing the fair principles requires expertise. It requires technical technological platforms, continuous support and and money. So it it cannot be done alone. It requires efforts from
Fatos Xhafa–BARCELONATECH: universities, research institutions, institutions, research projects, scientific research community at large. Right? So II have identified here some opportunities where the libraries can can help in this context.
Fatos Xhafa–BARCELONATECH: and to alleviate a little bit the burden of of these complex open data management. First, out, I think libraries are not expected to be a data placeholder. So having an open big data.
Fatos Xhafa–BARCELONATECH: It’s not easy. And so libraries are usually large technological platforms, but they are not expected to be a data placeholder, right? So but they can promote the open data project, for example.
Fatos Xhafa–BARCELONATECH: You may. You may wonder that actually, they are some networks today called the data curation networks. And you can, you can have a look at that link. If you would be interested in that
Fatos Xhafa–BARCELONATECH: where actually is promoted this data curation effort. Right? So I believe, libraries can participate in in data curation networks and can give they their experience right? Of course, they can train data curators.
Fatos Xhafa–BARCELONATECH: They can enable and promote best data, accuration practices, promote open data culture, organize open data events, etc. Right? So the more we work with the community in this direction, the the better will be for the open data projects overall. Right? So.
Fatos Xhafa–BARCELONATECH: having said this, let me bring to your attention some open data projects in in practice. So I have tick here in with with a blue circle. Only those items that correspond to the open data projects. II think we can have this classification open data projects which are linked to research projects
Fatos Xhafa–BARCELONATECH: either past or ongoing. And or we can have a generic open data, right, which are not related to a concrete research project. But they are there and can be used by different research project. Right? So as you see.
Fatos Xhafa–BARCELONATECH: research is fundamentally based, you know, on this open openness concept, right? Like dissemination plans, data management plan which have to be in place before we start any. You know research project, right?
Fatos Xhafa–BARCELONATECH: So we have to have a decision to disseminate and share. And we have to have plans of depositing the research data and give access and promote the free of charge use. Of course, in some cases it’s natural that the access could be restricted.
Fatos Xhafa–BARCELONATECH: especially because of the the delicate nature or the restricted nature of the data, but generally we should promote this culture of the use, free of charge of of the data. Right? Some examples in place, for example, are
Fatos Xhafa–BARCELONATECH: open data from Spanish government and also from the City Hall of Barcelona from European Union, United States, Canada, Australia. So most Western countries do have the open data initiatives. And that’s actually an excellent use. Because scientific research community can benefit from those open data which are completely
Fatos Xhafa–BARCELONATECH: managed and maintained by the the governments. And but they can be used freely by the research communities. And of course, there are many open data by private entities as well right now. If you remember, in the fair principles, there was 1 point that was the in the interoperability. Right? So
Fatos Xhafa–BARCELONATECH: so find ability, accessibility, interoperability reuse and of digital assets and open data, right? So findability is overall well implemented and accessibility as well and reuse as well. But interoperability is still a a weak point in in open data, because,
Fatos Xhafa–BARCELONATECH: different data sets which are maintained by different governmental bodies. They are interoperable at this local scale. But they are not interoperable at the global scale. Right? So this, this would be perhaps one of the next challenges to be addressed by the open data at at large scale. Right? So we can see
Fatos Xhafa–BARCELONATECH: open data from different parts of the world, and it could be, you know, integrated and interoperable. And that, of course, would give the dime the the research community, much more opportunities to to, you know, to use for for their scientific community search right
Fatos Xhafa–BARCELONATECH: now, how can are actually libraries participating? Or can the libraries make the liaison in in? In this need for implementing interoperability, I think there is needed more connection and collaboration between researchers, librarians, private and public institutions. So in in this context, libraries which
Fatos Xhafa–BARCELONATECH: know how to interoperate within one country, for example, within United States, through American Library Association, should translate their experience also to different governmental bodies. As regards the management. Fatos Xhafa–BARCELONATECH: all the open data, right?
Fatos Xhafa–BARCELONATECH: So I’m not, you know, if you are interesting, you get to get examples from open data of the Spanish government in Datos. Gop, yeah. Es.
Fatos Xhafa–BARCELONATECH: examples from open data of Barcelona City. So the I would invite you to have a look at the open data BC. And for Barcelona, which has about more than 600 data sets, and they are really rich and interesting for different kinds of research studies. Of course, the European Union is a champion in terms of
Fatos Xhafa–BARCELONATECH: promoting the open data. Fatos Xhafa–BARCELONATECH: So you you know, you can find lots of examples from both public and and private bodies.
Fatos Xhafa–BARCELONATECH: So now the point is to to make that available and interoperable at larger scale. Right? So before I I’m coming to the last part of of this webinar. I’d like to discuss some of the future trends in the data sharing, and how these can affect the the open data, and how libraries can can be helpful and collaborate with the research community for the open data in this content. Right?
Fatos Xhafa–BARCELONATECH: So one interesting trend. Fatos Xhafa–BARCELONATECH: In in data sharing is that actually sharing and openings are going beyond the specialized communities. So in the recent past, we used to see how open data was used by principally by researchers, right?
Fatos Xhafa–BARCELONATECH: But now we see that these open data sets are also open to citizens at large Fatos Xhafa–BARCELONATECH: for reasons of transparency accessibility.
Fatos Xhafa–BARCELONATECH: but also for participation and engagement. Right? So, for example, in United Kingdom the Metropolitan Police in London has opened as a data set, an open data set which called open crime data and also open maps. Which shows the the citizens
Fatos Xhafa–BARCELONATECH: to to be informed of the nature of the crimes in in the area where they live. Right? So this participation and engagement of the citizens gives yet another another reason to the Fatos Xhafa–BARCELONATECH: public and private institutions to invest more on the open data as a source for not only
Fatos Xhafa–BARCELONATECH: supporting the research, but also for the citizenship participation. Right now. One of the criteria that I mentioned in in before is actually the data codity which is really critical. Now, each time more we see the definition of a concept which is called the data health
Fatos Xhafa–BARCELONATECH: or the data observability. So we really need to ensure that the data is healthy in a sense that it is accurate, it is reliable. Otherwise, if we allow
Fatos Xhafa–BARCELONATECH: in the data set to enter data which is either incomplete, inaccurate, or in reliable, then that would get a catastrophic impact and undermine the the research of scientific community. Right? So data help is a concept.
Fatos Xhafa–BARCELONATECH: Requires to be taken very seriously to ensure the quality of the data in the long rind. Right? So and and for this I think, the libraries can can be helpful to give their experience of how they ensure that the collections of the information or or books, journals, etc. Was really healthy along many years, or even centuries.
Fatos Xhafa–BARCELONATECH: And another trend is to consider. Because now we see each time more data, we also have to consider and more seriously analyze the risks for the open data. And one of these risks is defined as a data downtown downtime, so that the which is the period
Fatos Xhafa–BARCELONATECH: of time when data is incomplete, erroneous having gaps inside, or is an inaccurate right? So there is one.
Fatos Xhafa–BARCELONATECH: Statistics from Gartner. We need not to take it as as literally because need not to be. That much. Gartner is saying that by 2,02580% of organizations seeking to scale digital businesses may fail because they didn’t take a modern approach to data and analytics. Governor, right? So
Fatos Xhafa–BARCELONATECH: even we, I mean 80%. I’m not sure if it has any statistical significance. But anyway, it’s an alerting that actually indeed, digital businesses could fail if they didn’t take a motor approach to to data. Governance right? So which means that
Fatos Xhafa–BARCELONATECH: scientific community has even, it’s not part of, let’s say, not from the perspective of a business, but from a perspective of the research is important to take into account that a modern approach to data openness is really very important. Right? Fatos Xhafa–BARCELONATECH: Yes. Yet another direction
Fatos Xhafa–BARCELONATECH: of these open trends. Well, sorry the trends for the open data is actually to give more incentivation for the open data Fatos Xhafa–BARCELONATECH: incentivation could be money related or could be effort related. Right? So with, if we consider monetization. that’s actually not the direction of the openness, because means that
Fatos Xhafa–BARCELONATECH: the access to the data will not be completely open, might be selective, or might be by paying a set right. But still, in some critical areas which are not covered by open data forms of monetization which not necessarily means money would be useful to generate and manage new data sets right.
Fatos Xhafa–BARCELONATECH: What I would like to stress. Here is the crediting crediting which means to give credit to Fatos Xhafa–BARCELONATECH: researchers and curators and all communities that contribute to implementing the open data. Right? So Fatos Xhafa–BARCELONATECH: the I’ve I’ve posted here. Well, I’m showing here a graph from
Fatos Xhafa–BARCELONATECH: an article from Matter Water Fatos Xhafa–BARCELONATECH: recently, which actually, if you see the the crossed links here, which means that the researchers actually do not receive enough credit for the effort they dedicate to the open data. And actually, this it has to be
Fatos Xhafa–BARCELONATECH: this credit has to be recognized. I am a university professor, and I recognize that as a university professor
Fatos Xhafa–BARCELONATECH: I have never received any, you know acknowledgement about the the time that I have dedicated to either to working or collaborating with the open data in general. Right? So and this has to change, because we need to involve more people, and and this, involving more people, requires more effort and more time. Therefore, that should have to be recognized.
Fatos Xhafa–BARCELONATECH: And lastly, one of the hype, perhaps, and trends. Now is the Chat Gp. Artificial intelligence. Right as you know this, there is a large discussion. Not only in the scientific community, but also in the society at large
Fatos Xhafa–BARCELONATECH: about the impact of the artificial intelligence and child Gp. Everywhere in every field of our lives. So and of course, open data are not an exception of that. Fatos Xhafa–BARCELONATECH: So there are 2 directions or true relations between artificial intelligence and open data. The first is that
Fatos Xhafa–BARCELONATECH: the Chat GPT. And other similar tools use actually open data. As you know, chat GPT. Fatos Xhafa–BARCELONATECH: Needs data to train each model
Fatos Xhafa–BARCELONATECH: right? So the open data actually has become a key to the performance of the chat. GPT. So now, we do not have any constant. You know we do not have any. You know, Fatos Xhafa–BARCELONATECH: real information
Fatos Xhafa–BARCELONATECH: how these open data sets are being used by the Chatgt. Right? So there are obviously legal issues. And and Chat, Gp and similar tools should comply with requirements on transparency and accountability. So what data have they used to train the the algorithms right?
Fatos Xhafa–BARCELONATECH: The other side is that Chajbt which, as you know, is part of the generative artificial intelligence, can be used to generate data sets. Fatos Xhafa–BARCELONATECH: I have to say that to to my knowledge. And as as far as I have read.
Fatos Xhafa–BARCELONATECH: the this data generation is not the strong point of chat. Gbt, right now. Fatos Xhafa–BARCELONATECH: so, nevertheless, in some cases people are reporting reasonable performance when it comes to to the data generation. Right? Now
Fatos Xhafa–BARCELONATECH: the the weakest point here is that the the open data set, the the data sets generated by Chart Gpt could easily contain fake data. They, they are actually realistic data.
Fatos Xhafa–BARCELONATECH: but in in the sense that they are realistically generated. But inside they can. They can have some some patterns or some data which could easily support some wrong hypothesis. On on the scientific hypothesis, right so. And and there has now is a trend on the scientific community that has started to show how some
Fatos Xhafa–BARCELONATECH: data sets generated by Chat Gpt are actually supporting wrong or fake scientific hypotheses. Right? So we have to be very concerned about the research integrity whenever that research is based on chatg data.
Fatos Xhafa–BARCELONATECH: So the question is, is the artificial intelligence or chat gpt a game changer for the open data.
Fatos Xhafa–BARCELONATECH: Well, right now it is not, but most likely it will be sometime soon, because all not only chat gpt, but all large model generations are are progressing at a very fast path. Therefore we’ll see how this can be used also for generating data set right.
Fatos Xhafa–BARCELONATECH: There are lots of concerns, as I said, about security, data, leakage, confidentiality, liability, property, compliance, etc. So, and of course, whenever there are concerns, there are needs. Fatos Xhafa–BARCELONATECH: and there are also needs for regulations. And. Fatos Xhafa–BARCELONATECH: as you know, very recently, European Union has released the Artificial Intelligence Act.
Fatos Xhafa–BARCELONATECH: which actually defines the levels of risk associated with artificial intelligence.
Fatos Xhafa–BARCELONATECH: And of course, we can take at a smaller scale. But these kinds of risks also apply to the data sets and to the open data, right? So now, whenever like, let’s say, we want to release an open data set using artificial intelligence algorithms, we have to look at this, and we have to see. And which of these levels of risk we are so that we can mitigate those risks? Right?
Fatos Xhafa–BARCELONATECH: So to conclude here. Fatos Xhafa–BARCELONATECH: As you know, we are in the area of artificial intelligence and and chat Gp, and similar Fatos Xhafa–BARCELONATECH: tools that are shaping everything. Fatos Xhafa–BARCELONATECH: not only scientifically, but also and in the society at large. So what the rival libraries role can be here.
Fatos Xhafa–BARCELONATECH: I think. The artificial events, and Chat Gpt, in particular, will propel yet another shift to libraries. So the libraries had a digital shift from the physical collections
Fatos Xhafa–BARCELONATECH: to digital collections. Now they have, they are prompted to have a shift towards the knowledge, creation, and dissemination centers so, and as this, as part of this knowledge, creation libraries also can contribute to the open data creation and and and also procedural
Fatos Xhafa–BARCELONATECH: understanding of management of the open data. Right? So of course, there are plenty of concerns. In this context. But I think that libraries
Fatos Xhafa–BARCELONATECH: should find opportunities to work with the different communities and to contribute to the open data right? So absolutely. The implementing and a fair artificial intelligence procedures fair, accountable, inclusive, and respectful. Artificial intelligence is of paramount importance to the Fatos Xhafa–BARCELONATECH: open signs and to the open data center, right?
Fatos Xhafa–BARCELONATECH: So if you are interested in reading more on this and similar topics. I’d like to invite you to look at these lecture notes in data, engineering, and communication technologies, which is published by Springer.
Fatos Xhafa–BARCELONATECH: We have from time to time also, we publish authored books. We publish edit volumes, and we publish Fatos Xhafa–BARCELONATECH: conference proceedings
Fatos Xhafa–BARCELONATECH: so. And and as part of these, you also will find articles which are relating to the open data in this context, right? So I’d like to to thank dr. Dinger.
Fatos Xhafa–BARCELONATECH: From the Springer Heidelberg in Germany for this opportunity, and also the Springer team, Tatiana, Liza, and of course the Sabrina and Ashley, from the choice and the association of College and Research libraries for their help in preparing this webinar. So I think I’ve come to the end of my presentation. Thank you very much for listening. And now, Sabrina, your turn, please.
Sabrina Cofer: Great. Okay, thank you so much, Professor Draffa. Yeah. Like, you said, we have some time for some questions, so I’ll just encourage everyone. If you haven’t put in a question yet feel free to enter that into the QA. Box.
Sabrina Cofer: And before that I’ll just launch a quick poll for everyone that you can fill out as well.
Sabrina Cofer: Okay. So we do have a few questions already. So this first one that came in I think early on in your presentation. Which is what exactly what is exactly meant by data sets. Is it? Is it a collection of data with common characteristics or linked together?
Fatos Xhafa–BARCELONATECH: Yeah, thank you very much. That’s an interesting question. Whenever we talk about data set, it is understood that that data set
Fatos Xhafa–BARCELONATECH: is a part reflects a phenomenon that we are interesting to study, right? So if we’d like to have, let’s say, a data set about the the noise. In in the city. Obviously, that data set means that will be useful to study that phenomenon. Which means that we’ll have sensors
Fatos Xhafa–BARCELONATECH: in in the, in the, in the city, in that area. And through those sensors we can collect the data, and that data can be useful to to study the phenomenon right now, of course, that that data has to be once that data. So if you don’t mind, I could go back to that cycle.
Fatos Xhafa–BARCELONATECH: in implementing the fair. Fatos Xhafa–BARCELONATECH: Just give me a moment, please, because I’m using this back. Fatos Xhafa–BARCELONATECH: so if in this fair implementation. oh, sorry. Fatos Xhafa–BARCELONATECH: Yeah. Oops.
Fatos Xhafa–BARCELONATECH: So here. So if you see here, we have a data cycle. Right? So we have we sense the data we collect, or we collect the data, we. And then once we collect the data that data is not useful, straightforward. So
Fatos Xhafa–BARCELONATECH: for that data set to become useful for supporting the research study of the phenomena, we need to to give a structure to that data. We need to curate the data. Curation is, you know, a general term which means that data must be structures.
Fatos Xhafa–BARCELONATECH: Data must be interrelated data. You know, ma must be curated from possible errors during the data collection, etcetera. Right? So Fatos Xhafa–BARCELONATECH: to
Fatos Xhafa–BARCELONATECH: come to your point, datasets are those that are collected through a process, a data collection process. It could be through sensors, it could be through cameras, it could be through questionnaires, or it could be through could be fetched from the web, etc. Whatever the way it is, once we have the data
Fatos Xhafa–BARCELONATECH: that data has to be structures and has to be created before it is used right? In some cases there is also associated this concept of data enrichment, which is there is a concept of semantic data enrichments. Which means that we complement the data with other data. So that it can be more helpful in the in the research study. Right. For example, if we are
Fatos Xhafa–BARCELONATECH: getting them the the data. About the noise in in the area of the city. We can enrich that data with jail localization of the data or with time stamps, etc., etc. Right? So yes, data sets need to have this prep, you know, processing and curation and also inter linking between as part of that data set.
Sabrina Cofer: Okay? Great. Thank you. Another question here. That just came in. Sabrina Cofer: It’s why is interoperability still a challenge when there are ways of making data global?
Fatos Xhafa–BARCELONATECH: Yeah, that that’s absolutely a brilliant question. And I’m happy that you you have made that point. So so the the first challenge, I would say so. There are 2 different challenges. I think here one first challenge is technical
Fatos Xhafa–BARCELONATECH: and the other one is more. Well, let’s say political. So the the the technical challenge is the scale. So because
Fatos Xhafa–BARCELONATECH: at the European Union, for example, different. Governments have their open datasets. So Spain or within Spain. Different municipalities, like Barcelona, have their own data sets, however, they are not interoperable. So the first, so the technical challenge is a scale. So you would like to move to the scale of European Union
Fatos Xhafa–BARCELONATECH: or to the to the scale of, you know, dozens of of countries, the fact that we have to manage interoperability while every collection is managed, not globally, but locally Fatos Xhafa–BARCELONATECH: so. And that makes the point the the inter viability very difficult, because the City Hall of Barcelona will not
Fatos Xhafa–BARCELONATECH: give permission to other actors to to to host their data. So the data lifecycle is defined in Barcelona. Fatos Xhafa–BARCELONATECH: but that data should be able to be integrated with others, and others may have a different data cycle definition, right? So
Fatos Xhafa–BARCELONATECH: These technicalities are not, you know, unsolvable. They can be solved, and I guess we can move from the country to a regional or a few countries. And then we move to European Union and and to a larger scale. So that’s that’s possible with the cloud digital ecosystem. What I see more difficult here is the political aspect, because
Fatos Xhafa–BARCELONATECH: behind the data, in in many cases there is data which is which Fatos Xhafa–BARCELONATECH: institutions or government, all that bodies would not like to give access to others so they can give access in using it, but not in, in, in manipulating it, or in defining procedures that they should comply right.
Fatos Xhafa–BARCELONATECH: Nevertheless, we are moving from Fatos Xhafa–BARCELONATECH: a state where open data sets were absolutely disgregated Fatos Xhafa–BARCELONATECH: to a stage where data sets become to see interoperability. So I believe in the near future, interoperability will be each time more possible at the larger scale. Sabrina Cofer: Great. Thank you.
Sabrina Cofer: I think we have time for maybe one more and there’s an interesting comment here from sort of the librarian perspective. It says, while it is nice to talk about sharing data don’t forget the metadata. To connect all these data sets together is equally important.
Sabrina Cofer: You need to think about pids orchid grid, doi, etc. If you want to get credit for sharing your data set. Otherwise, it’s just a bunch of numbers that have no context. So
Fatos Xhafa–BARCELONATECH: yes, definitely finding finding ways. I mean to to give credit to researchers and and developers, generally speaking, about the efforts that they have dedicated to the data. So so to put it, simply, data has been used or has been understood so far as
Fatos Xhafa–BARCELONATECH: as an additional means to make research.
Fatos Xhafa–BARCELONATECH: But I believe it’s time now to give to the open data the the class of the first citizen. Right? So open data has a lot of failure. And as such people that work on creating those open data sets should should definitely take and credit about. It could be academical recognition it could be, I don’t know different forms, but there should be, of course, a recognition to to that.
Sabrina Cofer: Okay, great. Let’s see, I think you have time for one more. Sabrina Cofer: we have sort of a broad question here that says, Sabrina Cofer: open science is okay. But how? How do we? How do we achieve an environment for open data?
Fatos Xhafa–BARCELONATECH: Well, I mean? The first, very, the very first point to achieve that environment from the open data is Fatos Xhafa–BARCELONATECH: to to analyze the the procedures that enable the implementation of the fare. Right? Prime simple, right? And let me show you the case of
Fatos Xhafa–BARCELONATECH: you know, one of the examples of the of the open data that II Fatos Xhafa–BARCELONATECH: I mean, yeah. So I mean, from a methodological perspective, it has to go through as shown in this diagram. Do you see this diagram or
Fatos Xhafa–BARCELONATECH: yes? So so as you see, there should be a data management plan. So whenever a research group or an entity, a university, public body, private body, etc., decides to go for an open data. Fatos Xhafa–BARCELONATECH: It has to be a data management plan, right? So it has to have
Fatos Xhafa–BARCELONATECH: criteria you know, criteria on how to decide the dissemination and sharing, you know. In which way will be deposited and made possible the access to that data. Right? So so this is from a conceptual perspective which, of course, need to be translated into a technological implementation or technical implementation. But now the the very, you know. If you look at the
Fatos Xhafa–BARCELONATECH: the open data set of of the city of Barcelona. So what you’ll see is that
Fatos Xhafa–BARCELONATECH: there is now it is, you know, not just putting the the data sets over there. So there is a way which classifies the data according by themes. So, for example, we have data sets about territory. We have but about population, about cities and services, about administration, about economy and businesses. And myself, for example, I have used these data sets here
Fatos Xhafa–BARCELONATECH: for to study optimization and and artificial intelligence algorithms for the that that user data to monitor in real time the the traffic in the city. Right? Fatos Xhafa–BARCELONATECH: So the the good thing is that because there are, there is a data plan behind
Fatos Xhafa–BARCELONATECH: these data sets are continuously, I mean, very frequently updated, right? So there is a team behind that that takes care, you know, in in structuring the data, in classifying the data, in in curating the data, etc. Right? II understand that this is a huge task which small research groups cannot do
Fatos Xhafa–BARCELONATECH: or cannot do at this scale, but the public administrations can do it, of course, and I believe that if different research groups would join together and collaborate. They can also build such possibilities by by using the cloud digital ecosystem.
Sabrina Cofer: Okay, great. Thank you so much. I think we’re about to about out of time. So thank you so much to Professor Joffler for taking the time to speak with us today, and thank you to our attendees for your questions and comments.
Sabrina Cofer: I’d like to remind our viewers that we did record today’s program. So be on the look out for a follow up email from choice. And A/C. Rl, with a link to the recording.
Sabrina Cofer: Also, if you have a few minutes after the presentation to fill out a brief survey, we would really appreciate it. So thanks again to all of you out there for joining us. We hope you learn something new from the session, and hope to see you again in in the near future on another webinar.
Fatos Xhafa–BARCELONATECH: Thank you. Thank you very much. And I take this opportunity to wish everybody Fatos Xhafa–BARCELONATECH: you know happy holidays and and and and and I hope that we’ll be in touch for future opportunities in these fields. Sabrina Cofer: Thank you. Great thanks. Everyone.