1
Knowledge Representation

  1. Higher-order logic programming: An expressive language for representing qualitative preferences
    A. Charalambidis, P. Rondogiannis, and A. Troumpoukis, Science of Computer Programming, vol. 155, 2018.
    DOI: 10.1016/j.scico.2017.09.002    
  2. An extension of SPARQL for expressing qualitative preferences
    A. Troumpoukis, S. Konstantopoulos, and A. Charalambidis, in Proceedings of the 16th International Semantic Web Conference (ISWC 2017), Vienna, 2017.
    Full text   
  3. The Sevod Vocabulary for Dataset Descriptions for Federated Querying
    S. Konstantopoulos, A. Charalambidis, A. Troumpoukis, G. Mouchakis, and V. Karkaletsis, in Proceedings of the 4th International Workshop on Dataset Profiling and Federated Search for Web Data (PROFILES 2017), Vienna, 22 October 2017. Held at ISWC 2017, 2017.
    Full text    Zenodo: 997603    
  4. The POWDER protocol as infrastructure to serving and compressing semantic data
    S. Konstantopoulos, P. Archer, P. Karampiperis, and V. Karkaletsis, International Journal of Metadata, Semantics and Ontologies, vol. 7, 2012.
    DOI: 10.1504/IJMSO.2012.048509    

2
Logic Programming

  1. Approximation Fixpoint Theory and the Well-Founded Semantics of Higher-Order Logic Programs
    A. Charalambidis, P. Rondogiannis, and I. Simeonidou, Theory and Practice of Logic Programming, vol. 18, no. 3-4, 2018.
    DOI: 10.1017/S1471068418000108    
  2. A refinement operator for inducing threaded-variable clauses
    A. Charalambidis and S. Konstantopoulos, in Revised Selected Papers from the 22nd International Conference on Inductive Logic Programming (ILP 2012). Dubrovnik, Croatia, 17–19 September 2012, 2013.

3
Federated Query Processing

  1. Developing a Benchmark Suite for Semantic Web Data from Existing Workflows
    A. Troumpoukis et al., in Proceedings of the Workshop on Benchmarking Linked Data (BLINK), held at ISWC 2016, Kobe, Japan, October 2016, 2016.
    Full text    Zenodo: 159568    
  2. SemaGrow: Optimizing Federated SPARQL Queries
    A. Charalambidis, A. Troumpoukis, and S. Konstantopoulos, in Proceedings of the 11th International Conference on Semantic Systems (SEMANTiCS 2015), Vienna, 15-17 September 2015, 2015.
    DOI: 10.1145/2814864.2814886    

4
Big Data Management and Processing

  1. From Copernicus Big Data to Extreme Earth Analytics
    M. Koubarakis et al., in Proceedings of the 22nd International Conference on Extending Database Technology (EDBT 2019), Lisbon, Portugal, 26-29 March 2019, 2019.
    DOI: 10.5441/002/edbt.2019.88    
  2. The BigDataEurope Platform – Supporting the Variety Dimension of Big Data
    S. Auer et al., in Proceedings of the 17th International Conference on Web Engineering (ICWE 2017), Rome, 5–8 June 2017, 2017.
    DOI: 10.1007/978-3-319-60131-1_3     Full text   
  3. Workload-Aware Self-Tuning Histograms for the Semantic Web
    K. Zamani, A. Charalambidis, S. Konstantopoulos, N. Zoulis, and E. Mavroudi, Transactions on Large Scale Data and Knowledge-Centered Systems, vol. 28, Sep. 2016.
    DOI: 10.1007/978-3-662-53455-7_6     Full text    Zenodo: 159131    

8
Privacy-preserving data processing

  1. A peer-to-peer protocol and system architecture for privacy-preserving statistical analysis
    K. Zamani, A. Charalambidis, S. Konstantopoulos, M. Dagioglou, and V. Karkaletsis, in Proceedings of the Workshop on Privacy Aware Machine Learning for Health Data Science (PAML), held at the 11th International Conference on Availability, Reliability and Security (ARES 2016), Salzburg, Austria, 31 Aug – 2 Sep 2016, 2016.
    DOI: 10.1007/978-3-319-45507-5_16     Zenodo: 61017     SpringerLink    

9
Applications

  1. Big Data Processing and Semantic Web Technologies for Decision Making in Hazardous Substance Dispersion Emergencies
    A. Davvetas et al., in Proceedings of the Demos and Posters Track of the 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, 21–25 October 2017, 2017.

  2. Towards supporting climate scientists and impact assessment analysts with the Big Data Europe platform
    I. Klampanos et al., in Geophysical Research Abstracts vol. 18, Session ESSI3.3 Earth science on Cloud, HPC and Grid, held at EGU General Assembly Conference, Vienna, Austria, 17-22 April 2016, 2016.
    Full text   
  3. Semantic Web technologies and Big Data infrastructures: SPARQL federated querying of heterogeneous Big Data stores
    S. Konstantopoulos, A. Charalambidis, G. Mouchakis, A. Troumpoukis, J. Jakobitsch, and V. Karkaletsis, in Proceedings of the Demos and Posters Track of the 15th International Semantic Web Conference (ISWC 2016), Kobe, Japan, 19-21 October 2016, 2016.
    Full text    Zenodo: 160170    
  4. Dataset descriptions for optimizing federated querying
    A. Charalambidis, S. Konstantopoulos, and V. Karkaletsis, in 24th International World Wide Web Conference Companion Proceedings (WWW 2015), Poster Session, Florence, Italy, 18-22 May 2015, 2015.
    DOI: 10.1145/2740908.2742779     Full text   
  5. Big data technologies for agricultural systems research
    S. Janssen, R. Knapen, Y. van Randen, G. Mouchakis, S. Konstantopoulos, and R. Lokers, in Book of Abstracts of the 21st International Congress on Modelling and Simulation (MODSIM2015), Broadbeach, Queensland, Australia, 29 Nov - 4 Dec 2015, 2015.

  6. A conceptualization of a nuclear or radiological emergency
    S. Konstantopoulos and A. Ikonomopoulos, Nuclear Engineering and Design, vol. 284, Apr. 2015.
    DOI: 10.1016/j.nucengdes.2014.12.016    
  7. Discovering, indexing and interlinking information resources
    F. Celli, J. Keizer, Y. Jaques, S. Konstantopoulos, and D. Vudragović, F1000 Research, vol. 28, Nov. 2015.
    DOI: 10.12688/f1000research.6848.2     Full text   
  8. Designing innovative linked open data and semantic technologies in agro-environmental modelling
    R. Lokers, S. Konstantopoulos, A. Stellato, R. Knapen, and S. Janssen, in Proceedings of the 7th International Congress on Environmental Modelling and Software (iEMSs 2014), San Diego, California, 15-19 June 2014., 2014.