Metadata for Research Data: Current Practices and Trends (original) (raw)
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This paper reports a study that examined the metadata standards and formats used by a select number of research data services, namely Datacite, Dataverse Network, Dryad, and FigShare. These services make use of a broad range of metadata practices and elements. The specific objective of the study was to investigate the number and nature of metadata elements, metadata elements specific to research data, compliance with interoperability and preservation standards, the use of controlled vocabularies for subject description and access and the extent of support for unique identifiers as well as the common and different metadata elements across these services. The study found that there was a variety of metadata elements used by the research data services and that the use of controlled vocabularies was common across the services. It was found that preservation and unique identifiers are central components of the studied services. An interesting observation was the extent of research data specific metadata elements, with Dryad making use of a wider range of metadata elements specific to research data than other services.
Metadata for Research Data in Practice
Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare
What data is needed about data? Describing the process to answer this question for the institutional data repository IST DataRep.
Information
This systematic review synthesised existing research papers that explore the available metadata standards to enable researchers to preserve, discover, and reuse research data in repositories. This review provides a broad overview of certain aspects that must be taken into consideration when creating and assessing metadata standards to enhance research data preservation discoverability and reusability strategies. Research papers on metadata standards, research data preservation, discovery and reuse, and repositories published between January 2003 and April 2023 were reviewed from a total of five databases. The review retrieved 1597 papers, and 13 papers were selected in this review. We revealed 13 research articles that explained the creation and application of metadata standards to enhance preservation, discovery, and reuse of research data in repositories. Among them, eight presented the three main types of metadata, descriptive, structural, and administrative, to enable the preser...
Rethinking Metadata Creation and Management in a Data-Driven Research World
2008
Research data collections are tremendously important and thus need good curation. However data collections are significantly different to publication repositories and so we need to ensure that these differences are taken into account when managing research data. We believe that a good way of approaching this problem is to articulate the needs of research data stakeholders-particularly users and creators. Consequently we have described an analysis of these needs and then examined costs in the light of these varying needs-it is important to note that costs are often incurred by different people to the beneficiaries. We finish the paper by showing practically how incurring software costs can provide valuable savings for both data creators and data managers.
Managing metadata for science, technology and innovation studies: The RISIS case
2016
Here, we describe the RISIS-SMS metadata system, developed to support the use of heterogeneous datasets in the field of Science, Technology and Innovation Studies (STIS). These data are partly within the RISIS infrastructure, but often elsewhere. The system has three aims: (i) to help researchers to search for and understand data that will help to answer specific research questions, without having to access or download the data. As datasets often have restricted access, browsing metadata is a key feature of the system: researchers need help identifying the relevant data from different sources for their research, and for which data it is worthwhile asking for access; (ii) to support the enrichment of data By linking the metadata system to the Linked Open Data environment (LOD); (iii) to facilitate application-driven data integration.
Collaborate, automate, prepare, prioritize: Creating metadata for legacy research data
2013
Data curation projects frequently deal with data that were not created for the purposes of longterm preservation and re-use. How can curation of such legacy data be improved by supplying necessary metadata? In this report, we address this and other questions by creating robust metadata for twenty legacy research datasets. We report on the metrics of creating domainspecific metadata and propose a four-prong framework of metadata creation for legacy research data. Our findings indicate that there is a steep learning curve in encoding metadata using the FGDC content standard for digital geospatial metadata. Our project demonstrates that when data curators are handed research data "as is," they may be successful in incorporating such data into a data sharing environment. We found that data curators can be successful in creating descriptive metadata and enhancing discoverability via subject analysis. However, curators must be aware of the limitations in applying structural and administrative metadata for legacy data.
Landscape of Metadata Schemas for Research Data Repositories: FAIRsharing Analysis
Proceedings of 26th International Symposium on Electronic Theses and Dissertations (ETD 2023), 2023
Research data is the recorded information generated while conducting research, writing an article, theses and dissertations, and other research processes. Providing access to research data is a challenge for all stakeholders in the research community. Metadata schemas contain metadata properties describing a research data repository, such as general scope, content, infrastructure, technical, quality, and metadata standards. Several metadata schemas are available for describing the research data repository. However, to facilitate the selection of an appropriate metadata standard for the research repository, the RDA Metadata Standards Directory, re3data.org, and FAIRsharing have compiled a list of metadata schemas in a single platform. FAIRsharing is a curated platform for information and education resources on data and metadata standards, interrelated to databases and data policies. Therefore, researchers preferred FAIRsharing to undertake a study on the assessment of the landscape of metadata schemas indexed by the platform with objectives of identifying the list of metadata schemas, studying their growth and development, distinguishing the disciplinary metadata schemas, identifying the country-wise contributions, organizations, funding and government bodies and institutional contributions in developing and actively maintaining metadata schemas, etc. The result found that FAIRsharing has covered over 1600 metadata schemas covering all the major domains of science and technology, medicine, management, arts & humanities, and social science. It has overwhelming organizations to maintain and fund developing the metadata schemas. The maximum of the metadata schemas is attributed by the Creative Commons attribution, GNU General Public License, Open Data Commons Attributions, etc. Overall, the study found it worthy for data curators, metadata creators, data repository developers, policymakers, research data librarians, etc., to select the appropriate metadata schema for the research data repository.
Research Data Repositories for Open Science: Metadata Schema Analysis
TRENDS & ISSUES IN LIBRARY TECHNOLOGY IFLA , 2023
The open access movement has promoted the development and implementation of diversity in institutional repositories. Repositories are the main channels that enable academics towards free access to different academic publications and research outputs such as articles, books, book chapters and conference proceedings. Currently, there is a need to promote open science through open access to academic publications, as well as research data. Both are used to generate research and subsequently a publication. Openness and unrestricted exchange of research outputs calls for the increased development and implementation of both publication repositories and data repositories. Data repositories are platforms that promote FAIR principles of findable, accessible, interoperable, and reusable datasets and research methods Like publications, data in data repositories must be organized with standards and metadata schemas. Various metadata schemas exist for this purpose, such as: OpenAIRE, Research Data Alliance, and Dublin Core. The aim of this research is to present and analyze metadata schemes that are used to organize research data repositories logically and in a structured way, particularly those linked to academic publications to facilitate their findability, accessibility, reusability, and interoperability. This study also includes massive data sets used to generate research, to facilitate its identification, access, retrieval, interoperability, and usability. Academic communication is in an era of transformation as research societies and communities have highlighted the need to develop and implement unrestricted communication channels to data in the open science environment that is financed with public funds from Higher Education Institutions (HEI) and Research Centers (RC).
Metadata Schema for the Description of Research Data Repositories : version 3.0
2015
Authors: Jessika Rücknagel , Paul Vierkant , Robert Ulrich , Gabriele Kloska , Edeltraud Schnepf , David Fichtmüller , Evelyn Reuter , Angelika Semrau , Maxi Kindling , Heinz Pampel , Michael Witt , Florian Fritze , Stephanie van de Sandt , Jens Klump , HansJürgen Goebelbecker , Michael Skarupianski , Roland Bertelmann , Peter Schirmbacher , Frank Scholze , Claudia Kramer , Claudio Fuchs , Shaked Spier , Agnes Kirchhoff d
S Gesing/J. Krüger (Eds.), Proceedings of the 8th International Workshop on Science Gateways (IWSG 2016). Rome, Italy, June 8-10, 2016. – Nowadays, the daily work of many research communities is characterized by an increasing amount and complexity of data. This makes it increasingly difficult to manage, access and utilize to ultimately gain scientific insights based on it. At the same time, domain scientists want to focus on their science instead of IT. The solution is research data management in order to store data in a structured way to enable easy discovery for future reference. An integral part is the use of metadata. With it, data becomes accessible by its content instead of only its name and location. The use of metadata shall be as automatic and seamless as possible in order to foster a high usability. Here we present the architecture and initial steps of the MASi project with its aim to build a comprehensive research data management service. First, it extends the existing KIT Data Manager framework by a generic programming interface and by a generic graphical web interface. Advanced additional features includes the integration of provenance metadata and persistent identifiers. The MASi service aims at being easily adaptable for arbitrary communities with limited effort. The requirements for the initial use cases within geography, chemistry and digital humanities are elucidated. The MASi research data management service is currently being built up to satisfy these complex and varying requirements in an efficient way.