Archives des mots-clés : Rob Hooft

Application Profile for Machine-Actionable Data Management Plans

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Authors : Tomasz Miksa, Paul Walk, Peter Neish, Simon Oblasser, Hollydawn Murray, Tom Renner, Marie-Christine Jacquemot-Perbal, João Cardoso, Trond Kvamme, Maria Praetzellis, Marek Suchánek, Rob Hooft, Benjamin Faure, Hanne Moa, Adil Hasan, Sarah Jones

This paper presents the application profile for machine-actionable data management plans that allows information from traditional data management plans to be expressed in a machine-actionable way.

We describe the methodology and research conducted to define the application profile. We also discuss design decisions made during its development and present systems which have adopted it.

The application profile was developed in an open and consensus-driven manner within the DMP Common Standards Working Group of the Research Data Alliance and is its official recommendation.

URL : Application Profile for Machine-Actionable Data Management Plans

DOI : http://doi.org/10.5334/dsj-2021-032

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

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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

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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

Alternative location : https://www.mitpressjournals.org/doi/pdf/10.1162/dint_a_00043