9 citations · 63 across the 31 of their papers we have counts for
6 papers · 1 filter
Enhancing Data Space Semantic Interoperability through Machine Learning: a Visionary Perspective
Zeyd Boukhers, Christoph Lange, Oya Beyan
Our vision paper outlines a plan to improve the future of semantic interoperability in data spaces through the application of machine learning. The use of data spaces, where data i…
Mapping Large Scale Research Metadata to Linked Data: A Performance Comparison of HBase, CSV and XML
Sahar Vahdati, Farah Karim, Jyun-Yao Huang +1
OpenAIRE, the Open Access Infrastructure for Research in Europe, comprises a database of all EC FP7 and H2020 funded research projects, including metadata of their results (publica…
Luzzu Quality Metric Language -- A DSL for Linked Data Quality Assessment
Jeremy Debattista, Christoph Lange, Sören Auer
The steadily growing number of linked open datasets brought about a number of reservations amongst data consumers with regard to the datasets' quality. Quality assessment requires…
Quality Assessment of Linked Datasets using Probabilistic Approximation
Jeremy Debattista, Santiago Londoño, Christoph Lange +1
With the increasing application of Linked Open Data, assessing the quality of datasets by computing quality metrics becomes an issue of crucial importance. For large and evolving d…
Luzzu - A Framework for Linked Data Quality Assessment
Jeremy Debattista, Christoph Lange, Sören Auer
With the increasing adoption and growth of the Linked Open Data cloud [9], with RDFa, Microformats and other ways of embedding data into ordinary Web pages, and with initiatives su…
Representing Dataset Quality Metadata using Multi-Dimensional Views
Jeremy Debattista, Christoph Lange, Sören Auer
Data quality is commonly defined as fitness for use. The problem of identifying quality of data is faced by many data consumers. Data publishers often do not have the means to iden…