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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/LM2023055" target="_blank" >LM2023055: Česká národní infrastruktura pro biologická data</a><br>

Návaznosti

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

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Codata Science Journal

ISSN

1683-1470

e-ISSN

1683-1470

Svazek periodika

24

Číslo periodika v rámci svazku

24

Stát vydavatele periodika

FR - Francouzská republika

Počet stran výsledku

23

Strana od-do

—

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105016654554