Improving FAIRness and developing a data security policy at Flanders Hydraulics

In 2023, Flanders Hydraulics (FH) implemented a Research Data Management (RDM) policy in order to improve the quality, security and availability of it’s research data, with extra emphasis on data governance and the FAIR principles (Findable, Accessible, Interoperable, Reusable). With support of the FOSB-architecture budget, two priorities were defined: improving FAIRness and developing a security policy for data accessibility. In order to increase data findability, FH developed a tailored DMP-template based on the Flemish Standard DMP, updated it’s research process flow and carried out an assessment of the current CRIS-system. Alongside these actions, a training and coaching programme was also established to promote FAIR awareness and behavioural change among researchers. Data Accessibility was improved via introducing VO data classification and an open data decision tree. Steps were taken to increase data Interoperability through ensuring metadata structure and readability in the CRIS system, additionally aiming to improving data flow to FRIS. The security policy includes a detailed ‘as is’ and ‘to be’ analysis, as well as guidelines for data classification and access rights. Processes for access allocation, including periodic reviews, were also developed. Although some aspects of this work are still being implemented, such as the optimisation of user rights and an impact analysis of management measures, important steps were nonetheless taken in the effective implementation of a security policy which is in line with Flemish government guidelines. Our policy aims to drive the creation of efficient and secure data infrastructure within FH.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-22
DOI
https://doi.org/10.5281/zenodo.15729876
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

Improving FAIRness and developing a data security policy at Flanders Hydraulics

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Improving FAIRness and developing a data security policy at Flanders Hydraulics

article en

Abstract

In 2023, Flanders Hydraulics (FH) implemented a Research Data Management (RDM) policy in order to improve the quality, security and availability of it’s research data, with extra emphasis on data governance and the FAIR principles (Findable, Accessible, Interoperable, Reusable). With support of the FOSB-architecture budget, two priorities were defined: improving FAIRness and developing a security policy for data accessibility. In order to increase data findability, FH developed a tailored DMP-template based on the Flemish Standard DMP, updated it’s research process flow and carried out an assessment of the current CRIS-system. Alongside these actions, a training and coaching programme was also established to promote FAIR awareness and behavioural change among researchers. Data Accessibility was improved via introducing VO data classification and an open data decision tree. Steps were taken to increase data Interoperability through ensuring metadata structure and readability in the CRIS system, additionally aiming to improving data flow to FRIS. The security policy includes a detailed ‘as is’ and ‘to be’ analysis, as well as guidelines for data classification and access rights. Processes for access allocation, including periodic reviews, were also developed. Although some aspects of this work are still being implemented, such as the optimisation of user rights and an impact analysis of management measures, important steps were nonetheless taken in the effective implementation of a security policy which is in line with Flemish government guidelines. Our policy aims to drive the creation of efficient and secure data infrastructure within FH.

Zenodo (CERN European Organization for Nuclear Research)
Flanders Hydraulics (BE)
Industry, innovation and infrastructure
Openalex Percentile: Top 43%
Research Data Management Practices
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