Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00371539" target="_blank" >RIV/68407700:21240/23:00371539 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.5334/dsj-2023-028" target="_blank" >https://doi.org/10.5334/dsj-2023-028</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5334/dsj-2023-028" target="_blank" >10.5334/dsj-2023-028</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans

Popis výsledku v původním jazyce

Most research funders require Data Management Plans (DMPs). The review process can be time consuming, since reviewers read text documents submitted by researchers and provide their feedback. Moreover, it requires specific expert knowledge in data stewardship, which is scarce. Machine-actionable Data Management Plans (maDMPs) and semantic technologies increase the potential for automatic assessment of information contained in DMPs. However, the level of automation and new possibilities are still not well-explored and leveraged. This paper discusses methods for the automation of DMP assessment. It goes beyond generating human-readable reports. It explores how the information contained in maDMPs can be used to provide automated pre-assessment or to fetch further information, allowing reviewers to better judge the content. We map the identified methods to various reviewer goals.

Název v anglickém jazyce

Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans

Popis výsledku anglicky

Most research funders require Data Management Plans (DMPs). The review process can be time consuming, since reviewers read text documents submitted by researchers and provide their feedback. Moreover, it requires specific expert knowledge in data stewardship, which is scarce. Machine-actionable Data Management Plans (maDMPs) and semantic technologies increase the potential for automatic assessment of information contained in DMPs. However, the level of automation and new possibilities are still not well-explored and leveraged. This paper discusses methods for the automation of DMP assessment. It goes beyond generating human-readable reports. It explores how the information contained in maDMPs can be used to provide automated pre-assessment or to fetch further information, allowing reviewers to better judge the content. We map the identified methods to various reviewer goals.

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/8J22AT015" target="_blank" >8J22AT015: Zefektivnění aplikování principů FAIR ve správě výzkumných dat</a><br>

Návaznosti

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

Rok uplatnění

2023

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

22

Číslo periodika v rámci svazku

August

Stát vydavatele periodika

FR - Francouzská republika

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85169843364