Towards Easier Visualization of Linked Data for Lay Users

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10363684" target="_blank" >RIV/00216208:11320/17:10363684 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1145/3102254.3102261" target="_blank" >http://dx.doi.org/10.1145/3102254.3102261</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3102254.3102261" target="_blank" >10.1145/3102254.3102261</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards Easier Visualization of Linked Data for Lay Users

Popis výsledku v původním jazyce

There are lots of Linked Open Data (LOD) datasets published today. However, the possibilities of their consumption are very limited and certainly not suitable for lay users. A lay user is often insufficiently shielded from the RDF format, e.g. when facing resource IRIs. Also, he needs to be a domain expert to understand the published datasets as they are published in a form which provides as much information as possible. Typically, a middle man is needed to interpret the data for the lay users and to create an understandable view. However, due to the lack of LOD enabled tools, the data gets converted to a lesser data format such as CSV, XML or JSON and therefore looses its semantics. In this paper, we identify and formalize the current problems related to publishing Linked Data based visualizations and we propose a method of configuring views for lay users. Moreover, we present a tool, LinkedPipes Visualization Assistant (LPVA), which experimentally implements the proposed method. We also evaluate the implementation and present two experiments based on real world data.

Název v anglickém jazyce

Towards Easier Visualization of Linked Data for Lay Users

Popis výsledku anglicky

There are lots of Linked Open Data (LOD) datasets published today. However, the possibilities of their consumption are very limited and certainly not suitable for lay users. A lay user is often insufficiently shielded from the RDF format, e.g. when facing resource IRIs. Also, he needs to be a domain expert to understand the published datasets as they are published in a form which provides as much information as possible. Typically, a middle man is needed to interpret the data for the lay users and to create an understandable view. However, due to the lack of LOD enabled tools, the data gets converted to a lesser data format such as CSV, XML or JSON and therefore looses its semantics. In this paper, we identify and formalize the current problems related to publishing Linked Data based visualizations and we propose a method of configuring views for lay users. Moreover, we present a tool, LinkedPipes Visualization Assistant (LPVA), which experimentally implements the proposed method. We also evaluate the implementation and present two experiments based on real world data.

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/GA16-09713S" target="_blank" >GA16-09713S: Efektivní explorace prostoru propojených dat</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

WIMS &apos;17 Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics

ISBN

978-1-4503-5225-3

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

9

Strana od-do

1-9

Název nakladatele

ACM

Místo vydání

New York, NY, USA

Místo konání akce

Amantea, Italy

Datum konání akce

19. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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