Machine-Actionability and Evolvability in Data Stewardship Planning: Framework, Implementation, and Case Study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F25%3A00385933" target="_blank" >RIV/68407700:21240/25:00385933 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.5334/dsj-2025-025" target="_blank" >https://doi.org/10.5334/dsj-2025-025</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5334/dsj-2025-025" target="_blank" >10.5334/dsj-2025-025</a>

Result language

angličtina

Original language name

Machine-Actionability and Evolvability in Data Stewardship Planning: Framework, Implementation, and Case Study

Original language description

Ensuring the evolvability of data stewardship planning is a critical challenge, particularly in environments where requirements frequently change. Traditional data management plans (DMPs) often lack modularity, adaptability, and machine-actionability, making it difficult to automate their evaluation, update them in response to new policies, or tailor them to specific disciplines. This paper presents a framework for machine-actionable and evolvable data stewardship planning, leveraging Normalized Systems Theory (NST) to improve scalability, flexibility, and reusability. Our approach integrates semantic technologies, ontologies, and linked data principles to enable structured, interoperable DMPs that can be automatically assessed and adapted. We provide a prototype implementation that demonstrates the feasibility of this approach. The key contribution of this paper is a demonstration case study, which evaluates the framework’s effectiveness in real-world scenarios, illustrating how machine-actionability can reduce manual workload, improve guidance for researchers, and support automated assessment processes. The findings highlight the potential of our solution to advance Findable, Accessible, Interoperable, and Reusable (FAIR)-aligned data stewardship practices, making data management planning more dynamic and sustainable.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LM2023055" target="_blank" >LM2023055: Czech National Infrastructure for Biological Data</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Codata Science Journal

ISSN

1683-1470

e-ISSN

1683-1470

Volume of the periodical

24

Issue of the periodical within the volume

24

Country of publishing house

FR - FRANCE

Number of pages

23

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-105016654554