Call for Papers: Special issue on Benchmarking Linked Data

Call for papers:

Special issue on Benchmarking Linked Data

The provision of high-quality benchmarks and benchmarking results yields the potential of pushing the development of better approaches and solutions. This holds in particular in the Semantic Web and Linked Data domain.

Big Linked Data is gradually getting adopted in the new data economy. Systems are constantly being developed in order to support the booming exchange of data (existing in numerous formats) in the Web and the Enterprise. Hence, ever more complex requirements emerge, pertaining to the efficiency and effectiveness of solutions driven by Linked Data.

From a practical perspective, the cost and effort required for introducing Big Linked Data technology in an enterprise value chain is significant. It is thus of utmost importance to reduce the costs and hurdles required to introduce Big Linked Data processing. A key step towards abolishing the barriers to the adoption and deployment of such data is to provide open benchmarking reports that allow users to assess the fitness of existing solutions for their purposes.

The primary goal of the current special issue is to compile the newest results pertaining to the evaluation and benchmarking of all steps of the Linked Data lifecycle so as to provide a status quo of (1) the means to measure the performance of existing Linked-Data solutions and (2) the performance of current Linked-Data-driven solutions.

Topics of interest

For this special issue, we welcome articles presenting (1) novel benchmarks (including benchmarking results) as well as (2) novel insights pertaining to evaluating any of the steps of the the Linked Data lifecycle. More specifically, we are interested in articles presenting benchmarks across the entire Linked Data life cycle, benchmarks that rely on large datasets and insights obtained from benchmarking Linked Data management processes.

Topics of interest include but are not limited to:

  • Linked Data benchmarks
  • Analysis of existing benchmarks and benchmarking results
  • Validation of previous experimental results
  • Linked Data benchmark evaluation
  • Benchmarking frameworks
  • Benchmarking tools and methodologies for the Linked Data lifecycle such as:
  • Extraction, generation and acquisition (Information Extraction, Knowledge Extraction, CSV2RDF, R2RML, etc.)
  • Storage and querying (triple stores, NoSQL solutions, graph databases, etc.)
  • Link Discovery
  • Classification and Enrichment (machine Learning, clustering, forward and backward chaining, etc.) versioning and curation
  • Knowledge base repair
  • Fact checking, data fairness, data diversity
  • Search, browsing, question answering
  • Linked Data Visualization
  • Linked-Data-driven applications
  • Novel application- and domain-specific benchmarks (e.g., geo-spatial, biomedical)
  • New evaluation measures (Key Performance Indicators - KPIs) for benchmarking
  • Comparisons of KPIs
  • New theoretical frameworks for benchmarks

Submission Instructions

Submission deadline: March 15, 2017 23:59 PM Hawaii-Time (updated!)

Notification of acceptance: May 15, 2017

Camera ready Paper Deadline: September 15, 2017

Submissions shall be made through the Semantic Web journal website at Prospective authors must take notice of the submission guidelines posted at Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the Special Issue on Benchmarking Linked data.

Submissions are possible in the full research papers category. Papers describing application reports, tools and systems are also welcome, provided that the main contribution still remains an advance of the state of the art with respect to the research perspective.

All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.

Guest editors

  • Axel-Cyrille Ngonga Ngomo, Institute for Applied Informatics, Leipzig, Germany
  • Irini Fundulaki, ICS-FORTH, Heraklion, Greece
  • Anastasia Krithara, National Center for Scientific Research “Demokritos”, Athens, Greece

Guest Editorial Board

  • Giorgos Flouris, ICS-FORTH, Greece
  • Olaf Hartig, Hasso Plattner Institute, Germany
  • Anastasios Kementsietsidis, Google Research, USA
  • Manolis Koubarakis, National and Kapodistrian University, Athens, Greece
  • Tom de Nies, iMinds, Belgium
  • Larri Pey, UPC & Sparsity-Technologies, Spain
  • Muhammad Saleem, University of Leipzig, Germany
  • Juan Sequeda, CAPSENTA, USA
  • Mirko Spasic, OpenLink, United Kingdom
  • Milos Jovanovik, OpenLink, United Kingdom
  • Kostas Stefanidis, University of Tampere, Finland
  • Manolis Terrovitis, IMIS – Athena, Greece
  • Ruben Verborgh, iMinds, Belgium
  • Ricardo Usbeck, University of Leipzig, Germany
  • Julia Stoyanovich, Drexel University