Tesis doctorales: TESEO

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Ministerio de Educación, Cultura y Deporte - Gobierno de España

Título: LINKED DATA WRAPPER CURATION: A PLATFORM PERSPECTIVE
Autor: AZPEITIA LAKUNTZA, IKER AITOR
Universidad: Universidad del País Vasco/Euskal Herriko Unibertsitatea
Departamento: Lenguajes y sistemas informáticos
Fecha de Lectura: 21/12/2017
Programa de doctorado: Programa de Doctorado en Ingeniería Informática por la Universidad del País Vasco/Euskal Herriko Unibertsitatea
Dirección:
- ITURRIOZ SANCHEZ, JUAN IGNACIO (Director)
- Díaz García, Oscar (Director)
Tribunal:
- Illarramendi Echave, Mª Aranzazu (presidente)
- LOPEZ DE IPIÑA GONZALEZ DE ARTAZA, DIEGO (secretario)
- CORCHO GARCIA, OSCAR (vocal)
Descriptores:
- INFORMATICA
Localización: REPOSITORIO INSTITUCIONAL E.H.U./U.P.V.

http://hdl.handle.net/10810/27014

Marcador: https://www.educacion.es/teseo/mostrarRef.do?ref=432387Añadir a favoritos.
Resumen:
Linked Data Wrappers (LDWs) turn Web APIs into RDF end-points, leveraging the LOD cloud with current data. This potential is frequently undervalued, regarding LDWs as mere by-products of larger endeavors, e.g. developing mashup applications. However, LDWs are mainly data-driven, not contaminated by application semantics, hence with an important potential for reuse. If LDWs could be decoupled from their breakout projects, this would increase the chances of LDWs becoming truly RDF end-points. But this vision is still under threat by LDW fragility upon API upgrades, and the risk of unmaintained LDWs. LDW curation might help. Similar to dataset curation, LDW curation aims to clean up datasets but, in this case, the dataset is implicitly described by the LDW definition, and ¿stains¿ are not limited to those related with the dataset quality but also include those related to the underlying API. This requires the existence of LDW Platforms that leverage existing code repositories with additional functionalities that cater for LDW definition, deployment and curation. This dissertation contributes to this vision through: (1) identifying a set of requirements for LDW Platforms; (2) instantiating these requirements in SYQL, a platform built upon Yahoo's YQL; (3) evaluating SYQL through a fully-developed proof of concept; and (4), validating the extent to which this approach facilitates LDW curation.

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