Modular framework for similarity-based dataset discovery using external knowledge

Nečaský, Martin; Škoda, Petr; Bernhauer, David; Klímek, Jakub; Skopal, Tomáš

doi:10.1108/dta-09-2021-0261

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…Everyone recognizes the massive rise of data. In addition, this data needs to be stored for future use without incurring a high cost (Necasky et al , 2022; Sharifpour et al , 2023). On a similar note, research data has also increased significantly as a result of digitalization.…”

Section: Introductionmentioning

confidence: 99%

Global status of dataset repositories at a glance: study based on OpenDOAR

Sofi,

Bhat,

Gulzar

2024

DLP

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Purpose The study aims to shed light on the current state of “Dataset repositories” indexed in Directory of Open Access Repositories (OpenDOAR). Design/methodology/approach From each repository/record information, the Open-Access Policies, Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), year of creation and the number of data sets archived in the repositories were manually searched, documented and analyzed. Findings Developed countries like the United Kingdom and the USA are primarily involved in the development of institutional open-access repositories comprising significant components of OpenDOAR. The most extensively used software is DSpace. Most data set archives are OAI-PMH compliant but do not follow open-access rules. The study also highlights the sites’ embrace of Web 2.0 capabilities and discovers really simple syndication feeds and Atom integration. The use of social media has made its presence known. Furthermore, the study concludes that the number of data sets kept in repositories is insufficient, although the expansion of such repositories has been consistent over the years. Practical implications The work has the potential to benefit both researchers in general and policymakers in particular. Scholars interested in research data, data sharing and data reuse can learn about the present state of repositories that preserve data sets in OpenDOAR. At the same time, policymakers can develop recommendations and policies to assist in the construction and maintenance of repositories for data sets. Originality/value According to the literature, there have been numerous studies on open-access repositories and OpenDOAR internationally, but no research has focused on repositories preserving content-type data sets. As a result, the study attempts to uncover various characteristics of OpenDOAR Data set repositories.

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Section: Introductionmentioning

confidence: 99%

Global status of dataset repositories at a glance: study based on OpenDOAR

Sofi,

Bhat,

Gulzar

2024

DLP

View full text Add to dashboard Cite

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“…Furthermore, there has recently been growing interest in approaches based on dataset similarity rather than simple query matching. It is impractical for users to understand the perfect query words that represent the required datasets in advance [9]. This allows users to avoid constructing appropriate query words and to carry richer semantics [10].…”

Section: Introductionmentioning

confidence: 99%

Metadata-Based Clustering and Selection of Metadata Items for Similar Dataset Discovery and Data Combination Tasks

Sakumoto,

Hayashi,

Sakaji

et al. 2024

IEEE Access

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Data integration, which aims to solve problems and create new services by combining datasets, has attracted considerable attention. The discovery of similar datasets that can be combined is critical. In the literature on similar dataset discovery, it is important to select an appropriate discovery method for each information need, such as the domain. However, conventional studies have evaluated discovery methods in different ways, such as domains, test datasets, and evaluation metrics. This factor prevents the appropriate method selection for each situation. Furthermore, the specific effects of the combination of different methods are not well known despite conventional studies arguing the importance of the combination. This study attempts to understand (1) the similarity indicators that should be employed for each domain and (2) the effects of a combination of different indicators on performance. We evaluated 16 inter-dataset clustering models based on different metadata-based similarity indicators, using unified evaluation metrics and datasets for 15 domains. Our results (1) suggest that similarity indicators should be used for each domain and (2) demonstrate that most of the combinations of different methods can improve clustering performance.INDEX TERMS dataset discovery, dataset similarity, clustering, data exchange platform, metadata

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LODChain: Strengthen the Connectivity of Your RDF Dataset to the Rest LOD Cloud

Mountantonakis

Tzitzikas

2022

The Semantic Web – ISWC 2022

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There is a recent trend for using the novel Artificial Intelligence Chat-GPT chatbox, which provides detailed responses and articulate answers across many domains of knowledge. However, in many cases it returns plausible-sounding but incorrect or inaccurate responses, whereas it does not provide evidence. Therefore, any user has to further search for checking the accuracy of the answer or/and for finding more information about the entities of the response. At the same time there is a high proliferation of RDF Knowledge Graphs (KGs) over any real domain, that offer high quality structured data. For enabling the combination of ChatGPT and RDF KGs, we present a research prototype, called GPT•LODS, which is able to enrich any ChatGPT response with more information from hundreds of RDF KGs. In particular, it identifies and annotates each entity of the response with statistics and hyperlinks to LODsyndesis KG (which contains integrated data from 400 RDF KGs and over 412 million entities). In this way, it is feasible to enrich the content of entities and to perform fact checking and validation for the facts of the response at real time.Demo Video: https://youtu.be/H30bSv9NfUw. Demo URL: https://demos.isl.ics.forth.gr/GPToLODS.

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Modular framework for similarity-based dataset discovery using external knowledge

Cited by 3 publications

References 41 publications

Global status of dataset repositories at a glance: study based on OpenDOAR

Global status of dataset repositories at a glance: study based on OpenDOAR

Metadata-Based Clustering and Selection of Metadata Items for Similar Dataset Discovery and Data Combination Tasks

LODChain: Strengthen the Connectivity of Your RDF Dataset to the Rest LOD Cloud

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