Visualizer of Dataset Similarity Using Knowledge Graph

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Visualizer of Dataset Similarity Using Knowledge Graph

Popis výsledku v původním jazyce

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 &quot;black-box&quot; 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.

Název v anglickém jazyce

Visualizer of Dataset Similarity Using Knowledge Graph

Popis výsledku anglicky

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 &quot;black-box&quot; 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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA19-01641S" target="_blank" >GA19-01641S: Kontextové podobnostní vyhledávání v otevřených datech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Similarity Search and Applications. SISAP 2020.

ISBN

978-3-030-60936-8

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

371-378

Název nakladatele

Springer

Místo vydání

Cham, Germany

Místo konání akce

Copenhagen, Denmark

Datum konání akce

30. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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