Paper 67 (In-Use track)

Semantic Data Quality Challenges in Online Marketing and Sales: an Empirical Study

Author(s): Anna Fensel, Zaenal Akbar, Elias Kärle, Christoph Blank, Andreas Gruber, Patrick Pixner

Abstract: The quality of linked data and instance data is currently a severe bottleneck for building applications that place semantic data in use. Many currently ongoing data quality research efforts such as in exploring existing datasets and new data acquisition techniques are surely largely promising. To complement them, we approach the problem from a different angle: with creation, deployment and testing of a typical online application that is basing on the state of the art semantic data (linked data and instance data), and consequently evaluating the data quality shortcomings and their level of severity. We provide a design and feasibility pilot of a solution implementing semantic content and data value chain for online direct marketing and sales. The designed and developed a solution is applicable for the use on the Web, social media and mobile channels. The designed, implemented and evaluated solution is within the tourism sector, and applicable globally. The state of the art challenges in using of semantic data in our solution have been identified and prioritized by 33 experts. The encountered and reported challenges primarily relate to data quality. We discuss the outcomes and potential future solutions that would be also applicable to other sectors.

Keywords: Data quality; Semantic services; Linked Data;; online marketing; online sales; eTourism

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