Jeremy Debattista

Jeremy Debattista
Depiction of Jeremy Debattista
Address Work
Room A110a,
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Selected Publications:

  1. Debattista, J., Auer, S., & Lange, C. Luzzu - A Methodology and Framework for Linked Data Quality Assessment. In ACM Journal of Data Information Quality Special Issue on Web Data Quality. Volume 8 Issue 1, Nov 2016, Article 4. Impact Factor (2015): 1.294

  2. Debattista, J., Londoño, S., Lange, C., & Auer, S. (2015). Quality Assessment of Linked Datasets using Probabilistic Approximation. In 12th European Semantic Web Conference Proceedings 2015, 221-236, Springer - One of three nominations for the best paper award. Acceptance Rate: 23% (research papers)

  3. Debattista, J., Lange, C., & Auer, S. (2014). Representing dataset quality metadata using multi-dimensional views. In Proceedings of the 10th International Conference on Semantic Systems - SEM 14. New York, New York, USA: ACM Press. doi:10.1145/2660517.2660525. Acceptance Rate: 27.1% (full papers)

  4. Debattista, J., Lange, C., & Auer, S. (2014). daQ, an Ontology for Dataset Quality Information. Linked Data on the Web (LDOW).

  5. Debattista, J., Lange, C., & Auer, S. (2016). Luzzu - A framework for Linked Data Quality Assessment. IEEE Tenth International Conference on Semantic Computing (ICSC) 2016, 124-131, IEEE. Acceptance Rate: 28.8% (full papers)

  6. Debattista, J., Lange, C., Scerri, S. & Auer, S. (2015). Linked 'Big' Data: Towards a Manifold Increase in Big Data Value and Veracity. IEEE/ACM 2nd International Symposium on Big Data Computing (BDC) 2015, 92-98, ACM. Acceptance Rate: 13% (short papers)

  7. Scerri, S., Debattista, J., Attard, J., & Rivera, I. (2015). A semantic infrastructure for personalisable context-aware environments. AI Mag. Vol 36 No 2. Impact Factor: 1.17

For a full list of my publications please visit Google Scholar (https://scholar.google.de/citations?user=WSq1odUAAAAJ&hl=en) or DBLP (http://dblp.uni-trier.de/pers/hd/d/Debattista:Jeremy)

Current Projects

  • DIACHRONPreserving the Evolving Data Web: Making Open / Linked Data Diachronic
  • LuzzuA Quality Assessment Framework for Linked Open Datasets

Publications

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