DataCite Metadata: Getting Connected!

2021

Objective The enormous growth in research data generated today has highlighted the value of data management (RDM) to make research FAIR (Findable, Accessible, Interconnected and Reusable). Appropriate data instructs researchers to use and reuse that data within appropriate citations and attribute it to the author. And Data citation refers to the process of presenting a reference to data in the same way as a bibliographic reference to printed resources is regularly provided by researchers. In this regard, the objective of this paper is to investigate the activities of the Datacite website in managing research data. Methodology The study approached the Datacite website, a non-profit organization that provides analysis with persistent identifiers (DOIs). The research examines the Statistics systems and other critical resources. Registrations by the Collective group and most involved repositories are included in the statistical approaches. The basic resources include top executives, OAI...

The constantly growing amount of Linked Open Data (LOD) datasets constitutes the need for rich metadata descriptions, enabling users to discover, understand and process the available data. This metadata is often created, maintained and stored in diverse data repositories featuring disparate data models that are often unable to provide the metadata necessary to automatically process the datasets described. This paper proposes DataID, a best-practice for LOD dataset descriptions which utilize RDF files hosted together with the datasets, under the same domain. We are describing the data model, which is based on the widely used DCAT and VoID vocabularies, as well as supporting tools to create and publish DataIDs and use cases that show the benefits of providing semantically rich metadata for complex datasets. As a proof of concept, we generated a DataID for the DBpedia dataset, which we will present in the paper.

A key aim of the CLADDIER project is to investigate the cross-linking and citation of resources (in particular data and their associated publications) held in institutional and subjectbased repositories within the research sector. Typically traditional citations are partial in that they are "backward citations", referring to work which influenced the current research, and they only cite other formal publications, ignoring other artefacts which are the output of research, in particular research data. Online repositories storing more dynamic digital objects gives the opportunity to provide a more complete picture of the relationships between them, with backward and forward citations to data and publications being propagated between repositories.

The rapid increase of scientific digital assets in the last years has made clear that digital identifiers are crucial for effectively publishing, accessing and managing digital information in e-science contexts. From persistent keys for access to digital objects in network environments, the concept of persistent identifiers has been more recently extended to identify also physical objects like people, institutions and any type of relevant entity in the e-Science domain, opening the way to the creation of an integrated information space where a network of resources can be resolved, linked, navigated and analyzed, as the Linked Open Data approach envisions for the Web. However, the creation and full exploitation of this valuable network of connections is currently hindered by the fragmentation and lack of coordination of the digital identifier ecosystem. The aim of this paper is to propose an open, distributed and scalable infrastructure for interoperating existing Persistent Identifiers and other digital identifier systems (like Cool URIs) in e-science, overcoming geographical, disciplinary and organizational boundaries. The Digital Identifier interoperability infrastructure is presented as a crosscutting solution of core services enabling interoperability at three different levels: identifier, co-reference and semantic.

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.

2021

The implementation of a Flemish research evaluation parameter highlights the complexity of author affiliation data collection for publications not included in major bibliographic databases. In this paper, we discuss a set of fundamental challenges that were encountered during a first data collection project. More specifically, we will elaborate the multifaceted data retrieval approach, the quest for a sustainable way of data registration and the development of necessary infrastructure and procedures. Although a lot of efforts are being invested in optimizing the exchange of well-structured author affiliation data, we will zoom in on opportunities that might arise to facilitate similar projects in the future.

2013

In this paper, we tackle the challenge of linking scholarly information in multi-disciplinary research infrastructures. There is a trend towards linking publications with research data and other information, but, as it is still emerging, this is handled differently by various initiatives and disciplines. For OpenAIRE, a European cross-disciplinary publication infrastructure, this poses the challenge of supporting these heterogeneous practices. Hence, OpenAIRE wants to contribute to the development of a common approach for discipline-independent linking practices between publications, data, project information and researchers. To this end, we constructed two demonstrators to identify commonalities and differences. The results show the importance of stable and unique identifiers, and support a "by reference" approach of interlinking research results. This approach allows discipline-specific research information to be managed independently in distributed systems and avoids redundant maintenance. Furthermore, it allows these disciplinary systems to manage the specialized structures of their contents themselves.

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.

2009

Aggregations of Web resources are increasingly important in scholarship as it adopts new methods that are data-centric, collaborative, and networked-based. The same notion of aggregations of resources is common to the mashed-up, socially networked information environment of Web 2.0. We present a mechanism to identify and describe aggregations of Web resources that has resulted from the Open Archives Initiative -Object Reuse and Exchange (OAI-ORE) project. The OAI-ORE specifications are based on the principles of the Architecture of the World Wide Web, the Semantic Web, and the Linked Data effort. Therefore, their incorporation into the cyberinfrastructure that supports eScholarship will ensure the integration of the products of scholarly research into the Data Web.

2018