Towards an Enterprise Entity Hub: Integration of General and Enterprise Knowledge

Kim, Hak Lae; Lee, Jeong-Soo; Yang, Jung-Yeon

doi:10.1007/978-3-319-31676-5_22

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…e complexity of using the tools is reduced it is easier ease-of-use pilot concept to encourage normal people to gain more interest in Semantic Web and the idea of Linked Data RDF graph generated as an output of a given query is illegible due to the amount of connections and lack of organization. Authors of [16] propose an approach to make the graph more reader-friendly by three steps:…”

Section: Application Of Linked Open Statistical Datamentioning

confidence: 99%

Mediating Open Data Consumption - Identifying Story Patterns for Linked Open Statistical Data

Janowski

Ojo

Curry

et al. 2019

Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance

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Statistical data account for a very large proportion of data published on open data platforms. is category of data are which are oen of high quality, value and public interest; are gradually being published as 5-star linked open statistical data or data cubes (LOSD) for easy integration and cross-border comparability.However, publishing open data as linked data (i.e. graph oriented) significantly increases the technical skill requirements for enduser consumption. We address this problem by mediating the exploration and analysis of LOSD published on open data platforms through the use of data stories. Aer providing the requisite background information on LOSD, we identified data story paerns from extant literature and show how these paerns can be employed in analysing LOSD. Subsequently, we provide a case study to illustrate the use of these data story paerns as an end-user domain-specific language to explore and analyse LOSD. We argue that using data stories for exploring and analysing on open data platforms has the potential to significantly increase the adoption and use of (linked) open data.

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Section: Application Of Linked Open Statistical Datamentioning

confidence: 99%