Abstract
An increasingly large number of sets of linked open data (LOD), typically in RDF format, are being pub-lished on the Semantic Web. Those data represent a potentially valuable resource for data analysis, particularly online analytical processing (OLAP), which often employs multidimensional (MD) models for conducting MD data analysis. Conducting MD analysis over LOD, however, is not a straightforward task. Most analysts will lack the technical skills to query LOD sources using an unfamiliar query language over data in a format not traditionally associated with MD data analysis. In this paper, we introduce the concept of the semantic web analysis graph (SWAG), which allows experts familiar with the LOD source to plot interesting courses of analysis for other users. We present a proof-of-concept prototype. The results of a usability study show that SWAGs may serve to build intuitive user interfaces.
Keywords: Business intelligence, business analytics, online analytical processing, guided analytics. Download URL: https://aisel.aisnet.org/amcis2021/data_science_decision_support/data_science_decision_support/9
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 27th Americas Conference on Information Systems (AMCIS 2021), August 9-13, 2021, Montreal, Canada |
| Publisher | AIS Publ. |
| Number of pages | 10 |
| Publication status | Published - Aug 2021 |
Fields of science
- 102 Computer Sciences
- 102010 Database systems
- 102015 Information systems
- 102016 IT security
- 102025 Distributed systems
- 102027 Web engineering
- 102028 Knowledge engineering
- 102030 Semantic technologies
- 102033 Data mining
- 102035 Data science
- 502050 Business informatics
- 503008 E-learning
JKU Focus areas
- Digital Transformation