Archives des mots-clés : Data Preservation

FAIR Forever? Accountabilities and Responsibilities in the Preservation of Research Data

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Author : Amy Currie, William Kilbride

Digital preservation is a fast-moving and growing community of practice of ubiquitous relevance, but in which capability is unevenly distributed. Within the open science and research data communities, digital preservation has a close alignment to the FAIR principles and is delivered through a complex specialist infrastructure comprising technology, staff and policy.

However, capacity erodes quickly, establishing a need for ongoing examination and review to ensure that skills, technology, and policy remain fit for changing purpose. To address this challenge, the Digital Preservation Coalition (DPC) conducted the FAIR Forever study, commissioned by the European Open Science Cloud (EOSC) Sustainability Working Group and funded by the EOSC Secretariat Project in 2020, to assess the current strengths, weaknesses, opportunities and threats to the preservation of research data across EOSC, and the feasibility of establishing shared approaches, workflows and services that would benefit EOSC stakeholders.

This paper draws from the FAIR Forever study to document and explore its key findings on the identified strengths, weaknesses, opportunities, and threats to the preservation of FAIR data in EOSC, and to the preservation of research data more broadly.

It begins with background of the study and an overview of the methodology employed, which involved a desk-based assessment of the emerging EOSC vision, interviews with representatives of EOSC stakeholders, and focus groups with digital preservation specialists and data managers in research organizations.

It summarizes key findings on the need for clarity on digital preservation in the EOSC vision and for elucidation of roles, responsibilities, and accountabilities to mitigate risks of data loss, reputation, and sustainability. It then outlines the recommendations provided in the final report presented to the EOSC Sustainability Working Group.

To better ensure that research data can be FAIRer for longer, the recommendations of the study are presented with discussion on how they can be extended and applied to various research data stakeholders in and outside of EOSC, and suggest ways to bring together research data curation, management, and preservation communities to better ensure FAIRness now and in the long term.

URL : FAIR Forever? Accountabilities and Responsibilities in the Preservation of Research Data

DOI : https://doi.org/10.2218/ijdc.v16i1.768

Risk Assessment for Scientific Data

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Authors : Matthew S. Mayernik, Kelsey Breseman, Robert R. Downs, Ruth Duerr, Alexis Garretson, Chung-Yi (Sophie) Hou

Ongoing stewardship is required to keep data collections and archives in existence. Scientific data collections may face a range of risk factors that could hinder, constrain, or limit current or future data use.

Identifying such risk factors to data use is a key step in preventing or minimizing data loss. This paper presents an analysis of data risk factors that scientific data collections may face, and a data risk assessment matrix to support data risk assessments to help ameliorate those risks.

The goals of this work are to inform and enable effective data risk assessment by: a) individuals and organizations who manage data collections, and b) individuals and organizations who want to help to reduce the risks associated with data preservation and stewardship.

The data risk assessment framework presented in this paper provides a platform from which risk assessments can begin, and a reference point for discussions of data stewardship resource allocations and priorities.

URL : Risk Assessment for Scientific Data

DOI : http://doi.org/10.5334/dsj-2020-010

Resurfacing Historical Scientific Data: A Case Study Involving Fruit Breeding Data

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Authors : Shannon L. Farrell, Lois G. Hendrickson, Kristen L. Mastel, Katherine Adina Allen, Julia A. Kelly

Objective

The objective of this paper is to illustrate the importance and complexities of working with historical analog data that exists on university campuses. Using a case study of fruit breeding data, we highlight issues and opportunities for librarians to help preserve and increase access to potentially valuable data sets.

Methods

We worked in conjunction with researchers to inventory, describe, and increase access to a large, 100-year-old data set of analog fruit breeding data. This involved creating a spreadsheet to capture metadata about each data set, identifying data sets at risk for loss, and digitizing select items for deposit in our institutional repository.

Results/Discussion

We illustrate that large amounts of data exist within biological and agricultural sciences departments and labs, and how past practices of data collection, record keeping, storage, and management have hindered data reuse.

We demonstrate that librarians have a role in collaborating with researchers and providing direction in how to preserve analog data and make it available for reuse. This work may provide guidance for other science librarians pursing similar projects.

Conclusions

This case study demonstrates how science librarians can build or strengthen their role in managing and providing access to analog data by combining their data management skills with researchers’ needs to recover and reuse data.

URL : Resurfacing Historical Scientific Data: A Case Study Involving Fruit Breeding Data

DOI : https://doi.org/10.7191/jeslib.2019.1171

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

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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

Research data management in the French National Research Center (CNRS)

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Authors : Joachim Schöpfel, Coline Ferrant, Francis Andre, Renaud Fabre

Purpose

The purpose of this paper is to present empirical evidence on the opinion and behaviour of French scientists (senior management level) regarding research data management (RDM).

Design/methodology/approach

The results are part of a nationwide survey on scientific information and documentation with 432 directors of French public research laboratories conducted by the French Research Center CNRS in 2014.

Findings

The paper presents empirical results about data production (types), management (human resources, IT, funding, and standards), data sharing and related needs, and highlights significant disciplinary differences.

Also, it appears that RDM and data sharing is not directly correlated with the commitment to open access. Regarding the FAIR data principles, the paper reveals that 68 per cent of all laboratory directors affirm that their data production and management is compliant with at least one of the FAIR principles.

But only 26 per cent are compliant with at least three principles, and less than 7 per cent are compliant with all four FAIR criteria, with laboratories in nuclear physics, SSH and earth sciences and astronomy being in advance of other disciplines, especially concerning the findability and the availability of their data output.

The paper concludes with comments about research data service development and recommendations for an institutional RDM policy.

Originality/value

For the first time, a nationwide survey was conducted with the senior research management level from all scientific disciplines. Surveys on RDM usually assess individual data behaviours, skills and needs. This survey is different insofar as it addresses institutional and collective data practice.

The respondents did not report on their own data behaviours and attitudes but were asked to provide information about their laboratory. The response rate was high (>30 per cent), and the results provide good insight into the real support and uptake of RDM by senior research managers who provide both models (examples for good practice) and opinion leadership.

URL : https://hal.univ-lille3.fr/hal-01728541/

The State of Assessing Data Stewardship Maturity – An Overview

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Author : Ge Peng

Data stewardship encompasses all activities that preserve and improve the information content, accessibility, and usability of data and metadata. Recent regulations, mandates, policies, and guidelines set forth by the U.S. government, federal other, and funding agencies, scientific societies and scholarly publishers, have levied stewardship requirements on digital scientific data.

This elevated level of requirements has increased the need for a formal approach to stewardship activities that supports compliance verification and reporting. Meeting or verifying compliance with stewardship requirements requires assessing the current state, identifying gaps, and, if necessary, defining a roadmap for improvement.

This, however, touches on standards and best practices in multiple knowledge domains. Therefore, data stewardship practitioners, especially these at data repositories or data service centers or associated with data stewardship programs, can benefit from knowledge of existing maturity assessment models.

This article provides an overview of the current state of assessing stewardship maturity for federally funded digital scientific data. A brief description of existing maturity assessment models and related application(s) is provided.

This helps stewardship practitioners to readily obtain basic information about these models. It allows them to evaluate each model’s suitability for their unique verification and improvement needs.

URL : The State of Assessing Data Stewardship Maturity – An Overview

DOI : http://doi.org/10.5334/dsj-2018-007