Parallel Session 3.2
- Introduction - Arne Berre/Axel Ngonga
- Designing Big Data Benchmarks - Irini Fundulaki
- LDBC - Peter Boncz
- DataBench - Gabriella Cattaneo/Tomas P. Lobo
- Holistic Benchmarking - Axel Ngonga/Gayane Sedrakyan
- Benchmarking as a service - Pavel Smirnov (AGT)
- The EU Big Data Inducement price challenge - Kimmo Rossi (EC)
- Presentation of solutions of winners of the EU Big Data Inducement Prize
- Summary and Discussion
This session will be organized by TF6 SG7. The goal of the session is to discuss and promote benchmarking (especially for Big Data platforms) with a focus on European stakeholders. The session will hence focus on:
- Unveiling key requirements and results gathered over the last three years of Big Data benchmarking at a European scale.
- Gathering future needs, trends and directions for benchmarking from a European perspective. Interactive presentations (powered by tools such as Mentimeter) will be combined with discussions in an open workshop-like atmosphere. We foresee the following structure (subject to
- Introduction and BDVA reference model.
- European benchmarking efforts and best practices (HOBBIT, DataBench, LDBC, etc.).
- Application areas (societal challenges, IOT, smart cities, smart homes, etc.).
- Future trends.
- Key areas interaction will include the completion of existing models, current practical challenges faced by European stakeholders and current trends (especially in societal challenges). The objectives of the session include:
- Present the current offering of TF6 SG7.
- Monitor current development in benchmarking (especially in Europe).
- Collect real needs from varied stakeholders pertaining to benchmarking that really matters
for their systems.
- Discover new avenues of research/use for benchmarking technologies.
Arne Jørgen Berre
Arne is working with Digital Platforms and Systems Interoperability, with focus on Big Data and processing support for Analytics/AI/Machine Learning. Chief Scientist at SINTEF Digital, Department for Software and Service Innovation, Group for Smart Data. The leader of BDVA (Big Data Value Association) TF6 Technical Priorities, GEMINI Center for Big Data with SINTEF, NTNU and UiO and SINTEF BigLearn on Big Data and Machine Learning.
Axel is a professor for data science at Paderborn University, where he leads the DICE research group. His work focuses on all aspects of processing knowledge and data at scale. He and his team have developed dozens of frameworks for the extraction, integration, querying, analysis, use and benchmarking of knowledge bases and knowledge graphs. Over the last 10 years, Axel has published more than 200 international peer-reviewed publications and received more than 20 awards for his research, including the Next Einstein Fellowship.
My professional experience encompasses: Software development (C/C++/Java/J2EE), Software Development methodologies (DSDM, Rational), Software Architecture (DBMS, CRM systems), Teaching (University), creating successful start-up companies in data management, Project Management (both commercial and scientific), Advising Ph.D. students and M.Sc. students, Technical Writing (both in the publishing industry, as well as in science - see my Scientific Publications website), Scientific Project Acquisition. As a computer scientist, I often serve in program committees of the major international conferences (ACM SIGMOD, VLDB, IEEE ICDE) in my field (database systems) as well as the referee for the major journal publications (ACM TODS, VLDB Journal, IEEE TKDE). I have also organized science workshops in this area (twice the DaMoN workshop at SIGMOD, as well as the DBDBD in .nl/.be). I am a regular speaker on data management topics, both to science and industry audiences. I have a strong specialization in engineering database systems. I have designed and implemented multiple database kernels, both relational and XML, inclusive query processing and transaction management. My unique technical expertise is an insight into the interaction between high-performance data management and computer architecture.
Gabriella Cattaneo is Associate VP of the European Government Consulting (EGC) Competence Centre of IDC EMEA, the European branch of the premier global provider of market intelligence, advisory services, and events for the ICT industries. The EGC Centre provides research and consulting services to governments and policy makers on ICT demand-supply dynamics, ICT socio-economic impacts and policy evaluation. Cattaneo has 20 years experience in socio-economic research and ICT markets quali-quantitative current and forecast analysis. She has a long experience in leading multinational research projects, mainly for DG Information Society and DG Enterprise of the European Commission, including European research programmes evaluation and assessment, in cooperation with main EU research centres and universities. She has been involved in benchmarking e-Government and e-Procurement services in Europe since 2005. She regularly authors policy reports and briefs.
The past 18 years I have been working with European research and innovation programs and projects. I have been dealing with socio-economic challenges such as competitiveness, inclusion, multilingualism and access to information. The science and technology areas I have dealt with include Big Data technologies, language/semantic technologies, artificial intelligence, statistical data processing and modelling, interfaces and interaction. Our future challenges in the "Data Policy and Innovation" unit include: creating a functioning market and re-use infrastructure for Big Data, Open Data, Linked Data, and harnessing and integrating language technologies, analytics and visualisation technologies to generate the best value from data.
Tomas P. Lobo
Big Data and Semantic Web evangelist. My goal is adding my 2 cents on those technologies. Specialities: software architect, Big Data, negotiation, project leader, stream processing, ontology engineering, semantic web.
Irini is Principal Researcher of the Information Systems Laboratory (ISL) of the Institute of Computer Science (ICS), FORTH and the Head of the W3C Greece Office. She is a member of the board of IDIKA S.A., a publicly owned company that delivers IT products and services for the social and health service public sectors in Greece and of GRNET S.A. that provides Internet connectivity, high-quality e-Infrastructures and advanced services to the Greek Educational, Academic and Research community. Her research interests are in the area of Linked Data Management and more specifically, on Models, Storage and Indexing Schemes for RDF data provenance and access control, Scalable RDF Query Processing, and on developing Benchmarks for Linked data tools with a focus on advanced reasoning, link discovery, instance matching and versioning. Currently, she is involved in EU H2020 HOBBIT Project, theGreek Funded Projects “Advanced Research for Biomedicine and Agriculture” and “Personalized Medicine”. She has published a number of scientific articles that have been widely cited and she has served on the Program Committee of numerous international conferences, journals and workshops. She is also one of the authors of the “Linked Data - Storing, Querying and Reasoning” book published by Springer Verlag.
Gayane Sedrakyan obtained PhD in Business Economics at KU Leuven specializing in Information Systems. Gayane's research interests include model-driven engineering (code generation of soft/web applications), process data analytics, (process-oriented) feedback automation, dashboards, visualizations. The results of her PhD were nominated in the context of university-wise educational prize for the innovative feedback at KU Leuven. Prior to her PhD research, she obtained 4 master degrees. Among them are Management Information Systems (KU Leuven, Belgium, 2012), Computer and Information Science (American University of Armenia, 2007) and post-graduate governmental studies (Public Administration Academy, Armenia, 2000). In addition to her research in academia, she also combines professional experiences from the government, banking and software industries. She was involved in program committees for several international conferences and workshops such as AMARETTO 2017 at Models award, and Online Measures for Learning Processes at EARLI SIG 2016, and was a referee for several journals and books such as Expert Systems with Applications (Elsevier), Computers & Education (Elsevier), Transactions on Learning Technologies (IEEE), Learning Analytics (Springer).
Pavel is currently engaged in the HOBBIT project. He has co-organized the DEBS Grand Challenge 2018. Prior to his work at AGT Pavel worked as a Research engineer at eScience Research Institute at ITMO University doing research in field of HPC/cloud and Big Data infrastructure.
In 2014 defended a PhD devoted to a workflow-based applications design via Virtual Simulation Objects concept and technology.
His topics of interest include cloud infrastructure, data streaming, workload scaling, resource scheduling, metrics monitoring, QoS, performance measurements, distributed infrastructures, linked data.