4th International Workshop on Dataset PROFIling & fEderated Search for Linked Data

Workshop scope

While the Web of Data, and in particular Linked Data, has seen tremendous growth over the past years, take-up, usage and reuse of data is still limited and is often focused on well-known reference datasets. As the Linked Open Data (LOD) Cloud includes data from a variety of domains spread across hundreds of datasets containing billions of entities and facts and is constantly evolving, manual assessment of dataset features is not feasible or sustainable, leading to brief and often outdated dataset metadata. Given the dynamic nature of the LOD Cloud, particular focus should be on the development of scalable automated approaches, which facilitate the frequent assessment and profiling of large-scale datasets to enable the selection of suitable datasets for query federation and, more generally, dataset recommendation for specific applications.

The PROFILES’17 workshop is a continuation of the workshop series successfully started as PROFILES’14 – PROFILES’16 @ ESWC 2014 – ESWC 2016. These workshops aims to gather innovative query and search approaches for large-scale, distributed and heterogeneous linked datasets inline with dedicated approaches to analyse, describe and discover endpoints, as an inherent task of query distribution and dataset recommendation. The PROFILES’17 workshop aims to become a highly interactive research forum for researchers. PROFILES’17 will bring together researchers and practitioners in the fields of Semantic Web and Linked Data, Databases, Semantic Search, Text Mining, NLP as well as Information Retrieval. PROFILES’17 will gather novel works from the fields of semantic query interpretation and federated search for Linked Data, dataset selection and discovery as well as automated profiling of datasets using scalable data assessment and profiling techniques. PROFILES’17 will equally consider both novel scientific methods and techniques for querying, assessment, profiling, discovery of distributed datasets as well as the application perspective, such as the innovative use of tools and methods for providing structured knowledge about distributed datasets, their evolution and fundamentally, means to search and query the Web of Data. We will seek application-oriented, as well as more theoretical papers and position papers.

Previous PROFILES editions: