Visualizer of Dataset Similarity Using Knowledge Graph
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10420919" target="_blank" >RIV/00216208:11320/20:10420919 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-60936-8_29" target="_blank" >https://doi.org/10.1007/978-3-030-60936-8_29</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-60936-8_29" target="_blank" >10.1007/978-3-030-60936-8_29</a>
Alternative languages
Result language
angličtina
Original language name
Visualizer of Dataset Similarity Using Knowledge Graph
Original language description
Many institutions choose to make their datasets available as Open Data. Open Data datasets are described by publisher-provided metadata and are registered in catalogs such as the European Data Portal. In spite of that, findability still remain a major issue. One of the main reasons is that metadata is captured in different contexts and with different background knowledge, so that keyword-based search provided by the catalogs is insufficient. A solution is to use an enriched querying that employs a dataset similarity model built on a shared context represented by a knowledge graph. However, the "black-box" dataset similarity may not fit well the user needs. If an explainable similarity model is used, then the issue can be tackled by providing users with a visualisation of the dataset similarity. This paper introduces a web-based tool for dataset similarity visualisation called ODIN (Open Dataset INspector). ODIN visualises knowledge graph-based dataset similarity, offering thus an explanation to the user. To understand the similarity, users can discover additional datasets that match their needs or reformulate the query to better reflect the knowledge graph. Last but not least, the user can analyze and/or design the similarity model itself.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-01641S" target="_blank" >GA19-01641S: Contextual Similarity Search in Open Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Similarity Search and Applications. SISAP 2020.
ISBN
978-3-030-60936-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
371-378
Publisher name
Springer
Place of publication
Cham, Germany
Event location
Copenhagen, Denmark
Event date
Sep 30, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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