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https://ruomo.lib.uom.gr/handle/7000/903
Title: | Facilitating the exploitation of Linked Open Statistical Data: JSON-QB API requirements and design criteria |
Authors: | Zeginis, Dimitris Kalampokis, Evangelos Bill, Roberts Moynihan, Rick Tambouris, Efthimios Tarabanis, Konstantinos |
Editors: | Capadisli, Sarven Cotton, Franck Dong, Xin Luna Guha, Ramanathan V. Haller, Armin Hitzler, Pascal Kalampokis, Evangelos Kejriwal, Mayank Sivakumar, D. Szekely, Pedro Troncy, Raphaël Witbrock, Michael |
Type: | Conference Paper |
Subjects: | FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | Linked data Statistical data data cube API JSON requirements |
Issue Date: | 2017 |
Volume Title: | Joint Proceedings of the International Workshops on Hybrid Statistical Semantic Understanding and Emerging Semantics, and Semantic Statistics co-located with 16th Extended Semantic Web Conference (ISWC 2017) |
Abstract: | Recently, many organizations have opened up their data for others to reuse. A major part of these data concern statistics such as demographic and social indicators. Linked Data is a promising paradigm for opening data because it facilitates data integration on the Web. Recently, a growing number of organizations adopted linked data paradigm and provided Linked Open Statistical Data (LOSD). These data can be exploited to create added value services and applications that require integrated data from multiple sources. In this paper, we suggest that in order to unleash the full potential of LOSD we need to facilitate the interaction with LOSD and hide most of the complexity. Moreover, we describe the requirements and design criteria of a JSON-QB API hat (i) facilitates the development of LOSD tools through a style of interaction familiar to web developers and (ii) offers a uniform way to access LOSD. A proof of concept implementation of the JSON-QB API demonstrates part of the proposed functionality. |
URI: | http://semstats.org/2017/ceur/ceur-ws/article-11.pdf https://ruomo.lib.uom.gr/handle/7000/903 |
Appears in Collections: | Department of Applied Informatics Department of Business Administration |
Files in This Item:
File | Description | Size | Format | |
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CR87_OGI_SemStats2017.pdf | 343,68 kB | Adobe PDF | View/Open |
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