FAIREST: A Framework for Assessing Research Repositories

d’Aquin, Mathieu; Kirstein, Fabian; Oliveira, Daniela; Schimmler, Sonja; Urbanek, Sebastian

doi:10.1162/dint_a_00159

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…2022)). We have added I4 as we believe that exporting metadata is a crucial feature in supporting I3, as we are in agreement with the FAIR analysis provided in (D'Aquin et. al.…”

Section: Interoperablesupporting

confidence: 84%

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Enabling FAIR Certification for Micrometeorological Datasets

Roantree,

Savić,

Scriney

et al. 2023

Preprint

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Abstract. The current state of weather-induced agricultural losses, water use for irrigation, the appearance of new invasive species and disease vectors, new environmental zoning of plant diseases and pests, deforestation, increased urbanization, rural-to-urban migration and increased urban energy consumption for cooling and heating, together impose a scientific demand for FAIR micrometeorological data. FAIR data and metadata should be easily discoverable by humans or machines, accessible under specific conditions or restrictions, conform to recognized formats and standards to be combined and exchanged, and licensed according to community norms, allowing users to know what kinds of reuse are permitted. However, the lack of FAIR data costs Europe a minimum of €10.2bn per year or approximately 78 % of the Horizon annual 2020 budget. If data met the FAIR principle, it would improve data discovery and access, enable re-use, enhance understanding, especially across domains, reach as many people as possible, be cited more often, and open new routes to build cooperation. To support owners of micrometeorological data to make their data FAIR, the FAIR Micromet Portal was developed within the CA20108 COST Action to guide owners through FAIR principles, in a step-by-step manner, with the ultimate goal of making large volumes of data FAIR. This paper provides a detailed discussion on how this is achieved by validating micrometeorological data stored on the FAIR Micromet Portal against the full set of FAIR metrics.

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“…2022)). We have added I4 as we believe that exporting metadata is a crucial feature in supporting I3, as we are in agreement with the FAIR analysis provided in (D'Aquin et. al.…”

Section: Interoperablesupporting

confidence: 84%

“…al. 2016), there have been a number of papers which sought to explore and interpret the different metrics (Berman & Crosas 2020); some authors suggested extensions and a tighter interpretation of the thresholds for compliance (D'Aquin et. al.…”

Section: Is My Data Fair?mentioning

confidence: 99%

Enabling FAIR Certification for Micrometeorological Datasets

Roantree,

Savić,

Scriney

et al. 2023

Preprint

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“…Attention should be paid to maintaining the initial purpose of repositories, i.e., providing open access to research results. However, at the same time, repository operators and managers must take more care of the curation of metadata quality, which means, above all, the assessment and improvement of the FAIRness of their infrastructure [33].…”

Section: Discussionmentioning

confidence: 99%

The Transformation of the Green Road to Open Access

et al. 2023

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(1) Background: The 2002 Budapest Open Access Initiative recommended the self-archiving of scientific articles in open repositories, which has been described as the “green road” to open access. Twenty years later, only one part of the researchers deposits their publications in open repositories; moreover, one part of the repositories’ content is not based on self-archived deposits but on mediated nonfaculty contributions. The purpose of the paper is to provide more empirical evidence on this situation and to assess the impact on the future of the green road. (2) Methods: We analyzed the contributions to the French national HAL repository from more than 1000 laboratories affiliated with the ten most important French research universities, with a focus on 2020, representing 14,023 contributor accounts and 164,070 deposits. (3) Results: We identified seven different types of contributor accounts, including deposits from nonfaculty staff and import flows from other platforms. Mediated nonfaculty contributions (deposits by libraries, import of bibliographic records, migration from other platforms, etc.) account for at least 48% of the 2020 deposits. We also identified differences between institutions and disciplines. (4) Conclusions: Our empirical results reveal a transformation of open repositories from self-archiving and direct scientific communication towards research information management. Repositories like HAL are somewhere in the middle of the process. The paper describes data quality as the main issue and major challenge of this transformation.

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“…It should be noted at this point that the original FAIR specification for data was relatively abstract, potentially leading to different interpretations. Some efforts have been made to further clarify the FAIR principles and even suggest ways to strengthen the original description [1]. This was achieved by examining existing open repositories such as EOSC and providing a deeper examination of how to assess some measure of FAIR for repositories.…”

Section: Application Of Fair Metricsmentioning

confidence: 99%

Constructing a Searchable Knowledge Repository for FAIR Climate Data

Roantree¹,

Lalić

Savić

et al. 2023

Preprint

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The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers who's skills include design and building a knowledge repository, and machine learning researchers who provide expertise on data preparation tasks such as gap filling and advise on different machine learning models that can exploit this data. One of the main goals of the CA20108 cost action is to develop a knowledge portal that is fully compliant with the FAIR principles for scientific data management. In the first year, a bespoke knowledge portal was developed to capture metadata for FAIR datasets. Its purpose was to provide detailed metadata descriptions for shareable micro-meteorological (micromet) data using the WMO standard. While storing Network, Site and Sensor metadata locally, the system passes the actual data to Zenodo, receives back the DOI and thus, creates a permanent link between the Knowledge Portal and the storage platform Zenodo. While the user searches the Knowledge portal (metadata), results provide both detailed descriptions and links to data on the Zenodo platform. Our adherence to FAIR principles are documented below: <ul> <li>Findable. Machine-readable metadata is required for automatic discovery of datasets and services. A metadata description is supplied by the data owners for all micro-meteorological data shared on the system which subsequently drives the search engine, using keywords or network, site and sensor search terms.</li> <li>Accessible. When suitable datasets have been identified, access details should be provided. Assuming data is freely accessible, Zenodo DOIs and links are provided for direct data access.</li> <li>Interoperable. Data interoperability means the ability to share and integrate data from different users and sources. This can only happen if a standard (meta)data model is employed to describe data, an important concept which generally requires data engineering skills to deliver. In the knowledge portal presented here, the WMO guide provides the design and structure for metadata.&#160;&#160;&#160;&#160;</li> <li>Reusable. To truly deliver reusability, metadata should be expressed in as detailed a manner as possible. In this way, data can be replicated and integrated according to different scientific requirements. While the Knowledge Portal facilitates very detailed metadata descriptions, not all metadata is compulsory as it was accepted that in some cases, the overhead in providing this information can be very costly.&#160;</li> </ul> Simple analytics are in place to monitor the volume and size of networks in the system. Current metrics include: network count; average size of network (number of sites); dates and size of datasets per network/site; numbers and types of sensors in each site, etc. The current Portal is in Beta version meaning that the system is currently functional but open only to members of the Cost Action who are nominated testers. This status is due to change in Q1/2023 when access will be open to the wider climate science community.&#160;&#160; Current plans include new Tools and Services to assess the quality of data, including the level of gaps and in some cases, machine learning tools will be provided to attempt gap filling for datasets meeting certain requirements. &#160;

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FAIREST: A Framework for Assessing Research Repositories

Cited by 6 publications

References 21 publications

Enabling FAIR Certification for Micrometeorological Datasets

Enabling FAIR Certification for Micrometeorological Datasets

The Transformation of the Green Road to Open Access

Constructing a Searchable Knowledge Repository for FAIR Climate Data

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