The Call for Nominations for the 2019 WDS Data Stewardship Award is now open until 29 July 2019. This annual prize celebrates the exceptional contributions of early career researchers to the improvement of scientific data stewardship through their (1) engagement with the community, (2) academic achievements, and (3) innovations. We are also pleased to announce that the process has been opened ...
The 2019 Fall Meeting of the American Geophysical Union will be held on 9–13 December 2019 in San Francisco, CA. The World Data System of the International Science Council is co-convening the following session, and we would like to encourage your abstract submission by the deadline of Wednesday, 31 July. Session ID: 82801 Session Title: IN003. Advancing Capabilities to Enable Current and ...
Twenty-four (24) seats are now available for a Training Workshop on Research Data Management aimed at early career researchers and scientists (ECRs). Apply for your place here! Sponsored by the European Geosciences Union (EGU) and hosted by World Data System of the International Science Council, the Workshop will take place on 6–8 November 2019 at Institut de Physique du Globe in ...
The WDS Asia–Oceania Conference 2019 will be held on 7–8 May 2019 in Beijing, China; hosted by the Institute of Geographic Sciences and Nature Resources Research, Chinese Academy Of Science. The purpose of the conference is to establish a collaborative network to share information and to do bottom up of data-oriented activities in the Asia-Oceania area. Towards realizing this goal, the ...
Enabling FAIR Data Project Nature Commentary: Make Scientific Data FAIR
We would like to direct you to Nature Commentary published on 5 June 2019 by the Enabling FAIR Data Steering Committee as a result of the work of the project.
– Make Scientific Data FAIR (Nature 570, 27–29; doi: 10.1038/d41586-019-01720-7)
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.
In the same Nature publication is a companion piece on credit for data that might also be of interest:
– Credit Data Generators for Data Reuse (Nature 570, 30–32; doi: 10.1038/d41586-019-01715-4)
FAIRifying Data Management: An example from the Humanities
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 Project that 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.
Influencers needed!... The next generation of data curators
A Blog post by Isabelle Gärtner-Roer (WDS Scientific Committee member) and Alice Fremand (WDS ECR Network Representative)
Data drives so much of our professional life today. From the organization of business meetings (virtual or face-to-face) to the publication of our research results. Data may simplify or complicate our lives, but for sure it is ubiquitous, though often unseen and behind the scenes.
But, what are the future challenges? And who are the future influencers and curators, when thinking about scientific data, its analysis and curation? We take a closer look at "our" WDS future generation, the enthusiastic group that builds the Early Career Researchers and Scientists (ECR) Network. And we take our hat off to our young and outstanding awardees, such as Wouter Beek in 2018. They represent the next generation and are our link to upcoming thrills and challenges in data science and management. They are our inspiration and hope when it comes to data curation for the next generations to come and we hope they raise their voice to become data influencers in the scientific community.
Want to be part of the next generation of data influencers? Want to meet fellow data experts keen to share their experience or want to support an outstanding colleague working with data? Do not hesitate to join and participate in different activities, WDS proposes. The WDS ECR Network is always happy to invite data experts or future data influencers to join their telecons and events. Moreover, the WDS Data Stewardship award is a good opportunity for you to support your colleague to be part of the next generation of data experts: the Call for Nominations is now open.
WDS ECR Network contact: email@example.com
Postnatal nurturing – giving data at risk a better chance of a long and fruitful life
A Blog post by David J. Patterson (WDS Scientific Committee member)
Big data gurus and advocates for a cyberinfrastructure or big data science describe a data-centric future in which massive quantities of digital data will be available for reuse in research, artificial intelligence, making predictions, or engaging in data-driven discovery. In the world of biology, this translates into the expectation is that molecular sequence information will be available from the nucleotide repositories such as GenBank, or that any and all occurrence data can be found at GBIF. It is also presumed that the data will have been vetted and, in all aspects, are trustworthy.
The vision is flawed. An unknown but large fraction of newborn digital data does not make it beyond the maternity ward. If data are to be properly prepared for re-use in the big data world, they must have moved a long way from the hands of its creators and into the custody of data managers, and repositories that will guarantee access to vetted content in perpetuity.
There are hundreds of thousands of sources where digital information is born. The long tail of parents include individual researchers, research teams, research programs, legacy data recovery projects, local, state, national governmental bodies and international initiatives. These parents rarely have the understanding or skillsets to ensure that their newborn will mature appropriately for a rôle in the big data world. For this to happen, data must be handed on to those who specialise in data management and curation. These adoptive parents will shepherd the content through the maturation process that will make it ready for repositories that are designed to make trustworthy data and services available to the public. The challenges to completion of the path are numerous. The first step is simply to make the data visible and accessible. Bad data need to be set aside or put back on the right path. For content to be discoverable, standardized metadata and ontologies need to be added so that the data can be found in the appropriate context. Interoperability requires access through appropriate services and for the data to be clothed with standardized ontologies and metadata. Just as the idiosyncratic swaddling clothes must be set aside, the new descriptors will need to be embellished with increasing detail, and be continually corrected and improved. Provenance metadata will help creators and managers gain credit for their effort, and will open up a pathway through which concerns about the data can be expressed. There will be problems that are specific to particular disciplines. As an example, relationships among taxa in ‘evolutionary trees’ which are created by algorithms become less trustworthy as new information and new algorithms emerge. In the biodiversity sciences, taxa may be mis-identified. Further, with the passage of time, new species are discovered - a process that renders ambiguous taxa identified by earlier less stringent criteria The ecosystem through which the content moves must provide the support that ensures continued fitness for purpose. Confidentiality and ethical concerns vary with subject matter but also have to be addressed.
As data mature, they will move from the hundreds of thousands of parents to a small number of data repositories that are funded using models that guarantee the persistence of their services. As far as is feasible, we expect the managers and repositories to apply the FAIR principles to the content they hold. Then, if the holder of the baton can meet the expectations of the CoreTrustSeal accreditation, the data will have found a secure and persistent home, with data ready for reuse. Fifty or so repositories have gained the CoreTrustSeal certification. But, as we have seen from the recent US governmental shutdown in December 2018 and January 2019, even major and certified data suppliers cannot be relied upon and may blink out unpredictably.
Many components already exist, nor are they joined up. Not only do most data fall by the wayside, much is not fit for a rôle in a data-centric world. The data are too contextualised, descriptors are incomplete or inaccurate. Few, if any, of the big data world providers allow users to correct errors. The consequence is that users of open data have to work with contaminated material. The World Data System is charged by the International Science Council to promote universal and equitable access to scientific data and information and increasing the capacity to generate new knowledge. WDS is especially concerned with the trustworthiness of the data and services. We will move further faster when we acknowledge that the research and discovery paradigm needs to be complemented with an investment in infrastructure and services. That investment will provide the framework and support that is required for data to live long and to prosper.
Credit for child image: Traitlin Burke