“Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning

Authors: Robert Pergl, Rob Hooft, Marek Suchánek, Vojtěch Knaisl, Jan Slifka

The Data Stewardship Wizard is a tool for data management planning that is focused on getting the most value out of data management planning for the project itself rather than on fulfilling obligations.

It is based on FAIR Data Stewardship, in which each data-related decision in a project acts to optimize the Findability, Accessibility, Interoperability and/or Reusability of the data.

The background to this philosophy is that the first reuser of the data is the researcher themselves. The tool encourages the consulting of expertise and experts, can help researchers avoid risks they did not know they would encounter by confronting them with practical experience from others, and can help them discover helpful technologies they did not know existed.

In this paper, we discuss the context and motivation for the tool, we explain its architecture and we present key functions, such as the knowledge model evolvability and migrations, assembling data management plans, metrics and evaluation of data management plans.

URL : “Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning

DOI : http://doi.org/10.5334/dsj-2019-059

Data Management Planning: How Requirements and Solutions are Beginning to Converge

Authors : Sarah Jones, Robert Pergl, Rob Hooft, Tomasz Miksa, Robert Samors, Judit Ungvari, Rowena I. Davis, Tina Lee

Effective stewardship of data is a critical precursor to making data FAIR. The goal of this paper is to bring an overview of current state of the art of data management and data stewardship planning solutions (DMP).

We begin by arguing why data management is an important vehicle supporting adoption and implementation of the FAIR principles, we describe the background, context and historical development, as well as major driving forces, being research initiatives and funders. Then we provide an overview of the current leading DMP tools in the form of a table presenting the key characteristics.

Next, we elaborate on emerging common standards for DMPs, especially the topic of machine-actionable DMPs. As sound DMP is not only a precursor of FAIR data stewardship, but also an integral part of it, we discuss its positioning in the emerging FAIR tools ecosystem. Capacity building and training activities are an important ingredient in the whole effort.

Although not being the primary goal of this paper, we touch also the topic of research workforce support, as tools can be just as much effective as their users are competent to use them properly.

We conclude by discussing the relations of DMP to FAIR principles, as there are other important connections than just being a precursor.

URL : Data Management Planning: How Requirements and Solutions are Beginning to Converge

 

Playing Well on the Data FAIRground: Initiatives and Infrastructure in Research Data Management

Authors : Danielle Descoteaux, Chiara Farinelli, Marina Soares e Silva, Anita de Waard

Over the past five years, Elsevier has focused on implementing FAIR and best practices in data management, from data preservation through reuse. In this paper we describe a series of efforts undertaken in this time to support proper data management practices.

In particular, we discuss our journal data policies and their implementation, the current status and future goals for the research data management platform Mendeley Data, and clear and persistent linkages to individual data sets stored on external data repositories from corresponding published papers through partnership with Scholix.

Early analysis of our data policies implementation confirms significant disparities at the subject level regarding data sharing practices, with most uptake within disciplines of Physical Sciences. Future directions at Elsevier include implementing better discoverability of linked data within an article and incorporating research data usage metrics.

URL : Playing Well on the Data FAIRground: Initiatives and Infrastructure in Research Data Management

DOI : https://doi.org/10.1162/dint_a_00020

Making FAIR Easy with FAIR Tools: From Creolization to Convergence

Authors : Mark Thompson, Kees Burger, Rajaram Kaliyaperumal, Marco Roos, Luiz Olavo Bonino da Silva Santos

Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and, therefore, the importance of good data management and data stewardship, is recognized.

This has led to many communities asking “What is FAIR?” and “How FAIR are we currently?”, questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR metrics.

However, early adopters of the FAIR principles have already run into the next question: “How can we become (more) FAIR?” This question is more difficult to answer, as the principles do not prescribe any specific standard or implementation.

Moreover, there does not yet exist a mature ecosystem of tools, platforms and standards to support human and machine agents to manage, produce, publish and consume FAIR data in a user-friendly and efficient (i.e., “easy”) way. In this paper we will show, however, that there are already many emerging examples of FAIR tools under development.

This paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining, before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.

DOI : https://doi.org/10.1162/dint_a_00031

Public Microbial Resource Centers: Key Hubs for Findable,Accessible, Interoperable, and Reusable (FAIR) Microorganismsand Genetic Materials

Authors : P. Becker, M. Bosschaerts, P. Chaerle, H.-M. Daniel, A. Hellemans, A. Olbrechts, L. Rigouts, A. Wilmotte, M. Hendrickx

In the context of open science, the availability of research materials is essential for knowledge accumulation and to maximize the impact of scientific research. In microbiology, microbial domain biological resource centers (mBRCs) have long-standing experience in preserving and distributing authenticated microbial strains and genetic materials (e.g., recombinant plasmids and DNA libraries) to support new discoveries and follow-on studies.

These culture collections play a central role in the conservation of microbial biodiversity and have expertise in cultivation, characterization, and taxonomy of microorganisms. Information associated with preserved biological resources is recorded in databases and is accessible through online catalogues.

Legal expertise developed by mBRCs guarantees end users the traceability and legality of the acquired material, notably with respect to the Nagoya Protocol. However, awareness of the advantages of depositing biological materials in professional repositories remains low, and the necessity of securing strains and genetic resources for future research must be emphasized.

This review describes the unique position of mBRCs in microbiology and molecular biology through their history, evolving roles, expertise, services, challenges, and international collaborations. It also calls for an increased deposit of strains and genetic resources, a responsibility shared by scientists, funding agencies, and publishers.

Journal policies requesting a deposit during submission of a manuscript represent one of the measures to make more biological materials available to the broader community, hence fully releasing their potential and improving openness and reproducibility in scientific research.

URL : https://orbi.uliege.be/bitstream/2268/240381/1/Applied%20and%20Environmental%20Microbiology-2019-Becker-e01444-19.full-1.pdf

Produire, analyser et partager des données ouvertes en Humanités Numériques : quelques bonnes pratiques

Auteur/Author : Gérald Kembellec

La réponse à des problématiques scientifiques liées aux humanités passe par le traitement numérique de corpus. Les humanités numériques deviennent un sujet d’importance qui regroupe des savoirs et des méthodes issus de diverses disciplines comme l’informatique, les statistiques, la sociologie, la cartographie ou encore la linguistique.

Cet article, s’il est ancré dans les sciences de l’information et de la communication, convoque des méthodes périphériques et se propose comme un vade-mecum de la gestion des données des humanités : la qualification, la collecte, le traitement, l’enrichissement, la documentation et le partage des données des humanités.

Nous mettons ici en avant le concept de « courtoisie du FAIR data » en contexte scientifique : la valorisation des corpus, en particulier par le partage de jeux de données de qualité, documentés et accessibles physiquement et légalement exploitables. Nous insistons également sur l’éthique lors des étapes de traitement et d’exploitation des données de la recherche.

URL : https://halshs.archives-ouvertes.fr/ISKOFRANCE2019/hal-02306958

Evaluating FAIR maturity through a scalable, automated, community-governed framework

Authors : Mark D. Wilkinson, Michel Dumontier, Susanna-Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Mario Prieto, Dominique Batista, Peter McQuilton, Tobias Kuhn, Philippe Rocca-Serra, Mercѐ Crosas, Erik Schultes

Transparent evaluations of FAIRness are increasingly required by a wide range of stakeholders, from scientists to publishers, funding agencies and policy makers. We propose a scalable, automatable framework to evaluate digital resources that encompasses measurable indicators, open source tools, and participation guidelines, which come together to accommodate domain relevant community-defined FAIR assessments.

The components of the framework are: (1) Maturity Indicators – community-authored specifications that delimit a specific automatically-measurable FAIR behavior; (2) Compliance Tests – small Web apps that test digital resources against individual Maturity Indicators; and (3) the Evaluator, a Web application that registers, assembles, and applies community-relevant sets of Compliance Tests against a digital resource, and provides a detailed report about what a machine “sees” when it visits that resource.

We discuss the technical and social considerations of FAIR assessments, and how this translates to our community-driven infrastructure. We then illustrate how the output of the Evaluator tool can serve as a roadmap to assist data stewards to incrementally and realistically improve the FAIRness of their resources.

URL : Evaluating FAIR maturity through a scalable, automated, community-governed framework

DOI : https://doi.org/10.1038/s41597-019-0184-5