Semantically Enhanced Quality Assurance in the JURION Business Use Case
The publishing industry is undergoing major changes. These changes are mainly based on technical developments and related habits of information consumption. Wolters Kluwer already engaged in new solutions to meet these challenges and to improve all processes of generating good quality content in the backend on the one hand and to deliver information and software in the frontend that facilitates the customer’s life on the other hand. JURION is an innovative legal information platform developed by Wolters Kluwer Germany (WKD) that merges and interlinks over one million documents of content and data from diverse sources such as national and European legislation and court judgments, extensive internally authored content and local customer data, as well as social media and web data (e.g. DBpedia). In collecting and managing this data, all stages of the Data Lifecycle are present – extraction, storage, authoring, interlinking, enrichment, quality analysis, repair and publication. Ensuring data quality is a key step in the JURION data lifecycle. In this industry paper we present two use cases for verifying quality: (1) integrating quality tools in the existing software infrastructure and (2) improving the data enrichment step by checking the external sources before importing them in JURION. We open-source part of our extensions and provide a screencast with our prototype in action.
KeywordsRDF quality Linked Data Enrichment
This work was supported by grants from the EU’s H2020 Programme ALIGNED (GA 644055). WKD and JURION is a use case partner in the ALIGNED project.
- 1.Auer, S., Bryl, V., Tramp, S. (eds.): Linked Open Data - Creating Knowledge Out of Interlinked Data, vol. 8661, 1st edn. Springer, Heidelberg (2014)Google Scholar
- 2.Kontokostas, D., Brümmer, M., Hellmann, S., Lehmann, J., Ioannidis, L.: NLP data cleansing based on linguistic ontology constraints. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 224–239. Springer, Heidelberg (2014)CrossRefGoogle Scholar
- 3.Kontokostas, D., Westphal, P., Auer, S., Hellmann, S., Lehmann, J., Databugger, R.C.: A test-driven framework for debugging the web of data. In: WWW Companion 2014, pp. 115–118 (2014)Google Scholar