A ‘challenge call’ is made public a few months before the conference alongside a deadline for the result papers, which are then evaluated by a jury. Introduced by Prof Paulo Carvalho from Coimbra University in Portugal and Prof Ratko Magjarevic from Zagreb University in Croatia, the challenges have proved quite successful, with the participation of 20–30 groups of young researchers responding to the first call.
A major problem for the organizers, however, has been to find adequate datasets containing well-documented biomedical data, such as respiratory measurements, electroencephalography recordings, electro-cardiac recordings, and the like. While many state that Big Data is widely accessible and available, well-documented and consistent biomedical datasets are difficult to find. This has resulted in the IFMBE having to actually sponsor teams to collect appropriate datasets of biomedical measurements specifically for the ‘scientific challenge’ competitions!
To address such issues, programmes are now being started that encourage universities and research groups in the Biomedical Sciences to make their datasets public while taking adequate precautions to protect the privacy of patients when such datasets are linked to physical persons. IFMBE is currently exploring practical ways to constitute collections of well-documented biomedical datasets that comply with the FAIR principles and that are made publicly available to researchers via a repository. Moreover, it is encouraging member societies at large to take up similar schemes either themselves or via universities.
Universities are inherently multidisciplinary and often hold a wide variety of research datasets. This makes them an ideal place to develop and test systems to manage, host, and access multidisciplinary and heterogeneous research datasets. However, the existence of such datasets and how they are preserved is not always well known. At Kyoto University, a survey was conducted by the Academic Data Innovation Unit* to gain a basic understanding of this information towards the planning of a new research data management system. The survey was sent to all researchers at Kyoto University, more than 3,000 of them, in December 2018 and we collected their responses until the end of January 2019. Although the survey was not mandatory, valid responses were received from 244 researchers ranging across the disciplines in Figure 1. From the results, we see that the largest proportion of datasets are held by the Life Sciences. This may not be the reality, however, since we received an unexpectedly low response from the Technology departments, which form the largest group at Kyoto University.
Figure 1: Responses by discipline
Figure 2 indicates the level of openness for each of the datasets identified by researchers. As can be seen, the majority of datasets are shared within a research group only and are not open to others (or even open at all). The implication is that the principle use case we need to account for on campus when developing a data management system is the sharing of data among members within each research group rather than making the data completely open.
Figure 2: Number of open and closed datasets
Despite the above, we believe that it should be possible for some researchers to make their datasets open to all if they are provided with appropriate technical support. Proper education and training on open data and data management will also assist in this process. In particular, around 20 data repositories—mostly hosted by research institutes within Kyoto University—are of especially high quality, and we would expect that about half of them could potentially become CoreTrustSeal-certified WDS Regular Members.
*The Academic Data Innovation Unit is a virtual organization at Kyoto University and is currently chaired by Prof Shoji Kajita. One of its main tasks is to propose a research data management system to accommodate the needs of all researchers at Kyoto University.
The WDS-ECR Network was set up in September 2017 to promote scientific data stewardship, share best practices, and foster better communication among ECRs. As a co-lead of the Network, alongside Sabrina Delgado Arias (Science Systems and Applications, Inc.) and Ivan Pyshnograiev (Igor Sikorsky Kyiv Polytechnic Institute), I coordinate events, speaker series, and periodic teleconferences, as well as liaise with other ECR communities to share ideas on future data practices.
In 2018, the WDS-SC invited a representative of the ECR Network to take part in their meetings by opening up a one-year rolling seat on the Committee. This initiative facilitates communication with the next generations of data managers and enables WDS to develop activities targeting ECR’s interests. I represented the Network on the WDS-SC from July 2018 to June 2019. Being a member of the WDS-SC was an amazing experience and opportunity.
All SC members are working pro bono to share their ideas on how to best shape the future of data stewardship for better science. This is very exciting! SC members meet each month via teleconference, and then twice a year in person where most of the plans for actions are validated. In order to reach out to different communities, face-to-face meetings of the WDS-SC are often co-located with other WDS events such as regional conferences. I attended two such meetings, one in November 2018 in Cape Town, and another in May 2019 in Beijing. During the very intense two-day meetings, SC members present their ideas and discuss the tasks for WDS to undertake in the following months. I got to meet exceptional data experts from around the world, and took part in the decisions, and strategic actions and activities of WDS.
In particular, I participated in the preparation of a training workshop targeting ECRs that is sponsored by a grant of the European Geosciences Union. I saw how much work is involved in setting up such events, and I am sure it will be very rewarding for PhD students and Post-docs to learn more about Research Data Management. The training workshop is a great opportunity for those attending and crucial for the future of science. Being part of the WDS-SC provided me with the chance to share my inputs when necessary. I really appreciated seeing that my suggestions were valued. I thank all the SC members for their warm welcome and for the trust I was given. I also encourage all early career scientists and researchers who work with data to join the WDS-ECR Network. It might be you representing the ECR Network on the WDS-SC in the future!
Talking of which...Sabrina Delgado Arias will represent the WDS ECR Network on the WDS-SC from July 2019 to June 2020. We wish her all the best!
In this piece, the authors begin to describe intersections of information maintenance and care ethics in ways that are real and meaningful for information maintainers (i.e., those who manage, maintain, and preserve information systems).
Contributors to this document have varied experiences with information maintenance: community organizers and facilitators, archivists, repository managers, project managers, designers, librarians, researchers, grantmakers, educators, and more. The authors invite those in occupations and roles who understand that the relationship is especially valuable between information maintenance and an ethic of care to read, react, share, and engage with this potluck of ideas. Please circulate widely!
The main point of the article is to encourage the broad research community to work towards open and FAIR data and put in place the policies, guidelines, incentives, and funding necessary to support the needed culture and systemic change around how we handle our scientific data.
A Blog post by Ingrid Dillo (WDS Scientific Committee Vice-chair; Deputy Director of WDS Regular Member: DANS, Data Archiving and Networked Services)
In this WDS Blog post, I want to highlight a set of guidelines developed in a community that is not yet very well represented within the membership of the World Data System, but that is getting more and more involved. I am talking about the Humanities. Coming from the Humanities myself, and being active in a broader international data environment, I know from experience that the Humanities data community has a lot to offer other disciplines. Humanists often struggle with very fuzzy, multi-interpretable, scattered, and incomplete data, and so they need to be highly resourceful. For the Digital Humanities, therefore, international collaboration is a sine qua non.
An example of such international collaboration is the PARTHENOS Projectthat comprises 16 European partners, including DANS (a WDS Regular Member). PARTHENOS stands for ‘Pooling Activities, Resources and Tools for Heritage E-research Networking, Optimization and Synergies’. It is inspired by Athena Parthenos, the Greek goddess of wisdom, inspiration, and civilization.
PARTHENOS aims to strengthen the cohesion of research in the broad sector of Linguistic Studies, Humanities, Cultural Heritage, History, Archaeology, and other related fields. This is being achieved through, for example, the definition and support of common standards and the harmonization of policy definitions and implementation.
One of the activities under the umbrella of PARTHENOS concerns the definition of common policies and implementation strategies for Research Data Management (RDM). The ubiquitous FAIR principles were chosen as a framework to structure a set of guidelines and recommendations. The concrete (and freely available) outcome of this activity is the very practical booklet: Guidelines to FAIRify data management and make data reusable.
The booklet offers a series of guidelines to align the efforts of data producers, data archivists, and data users in the Humanities, and thus make research data as reusable as possible. The guidelines are the result of the work of over 50 PARTHENOS project members, who were responsible for investigating commonalities in the implementation of policies and strategies for RDM and who conducted desk research, questionnaires, and interviews with selected experts to gather around 100 current data management policies—including guides for preferred formats, data review policies, and best practices (both formal and tacit).
The booklet also offers recommendations for two important stakeholder groups:
Researchers and research communities,
Research infrastructures and in particular, data repositories.
By focussing on (meta)data and repository quality, a set of twenty guidelines was extracted. For easy reference, the guidelines have been grouped under the four FAIR principles.
The guide starts with an important message: Invest in people and infrastructure. Investing in data infrastructures and trustworthy data repositories, as well as in hiring and educating data experts, is an important prerequisite to be able to implement any data management guideline. This way, we can enable researchers to comply with data management mandates coming from funders and journals.
Please have a look at the set of guidelines and see whether they are reusable in your domain.