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https://ceur-ws.org/Vol-1810/EuroPro_paper_00.pdf
Big Data Management Challenges and Solutions in the
Context of European Projects – Workshop Introduction
Yannis Ioannidis
“Athena” Research Center and University of Athens, Greece
yannis@{athenarc.gr,di.uoa.gr}
The main objective of this workshop1 has been to share Seven such projects, each one addressing one or more of the
experiences and best practices, discuss challenges and effective above sub-objectives has been accepted to the workshop. Four of
solutions adopted, and investigate opportunities for collaboration them deal with big data challenges for particular kinds of data:
among European projects (funded by various directorates of the
European Commission or other European funding agencies)
• dataCron focuses on spatiotemporal data, either at rest
dealing with big data management. The projects may have ICT as
(static data) or in motion (streams). It takes advantage
their main focus or, equally well, they may have some other
of big heterogeneous data sources to study the
scientific field, industrial application, or societal challenge as their
trajectories of moving objects and predict their future
main focus, in the context of which big data issues come up.
positions.
The workshop aims at bringing together data management and • STREAMLINE deals with data at rest and data in
database researchers and experts, as well as related user groups, motion as well. It studies various techniques to improve
designers, developers, and data practitioners. It acts as a broad performance of big dataflow executions and advance the
forum for the exchange of the latest research results in big data state of the art in specialized functionality, such as
management exploring new concepts, techniques, and tools. interactive visualization and window aggregation.
These showcase how the major big data challenges are being • PROTEUS is the third project that focuses on both
confronted, be they the classical high data volume, great variety, historical data and streams. It works on developing a
high data velocity, lack of veracity (accuracy or reliability), and software architecture to support online machine learning
difficulty in extracting value from data, or new specialized issues predictive analytics and real-time interactive
that possibly arise in specific environments and contexts. visualization on large volumes of such data.
More specifically, within the context of European projects, the • MyHealthMyData focuses on the issue of data privacy.
workshop has the following concrete sub-objectives: In particular, it deals with biomedical information in a
network of hospitals and aims to provide the necessary
technologies, e.g., blockchain, so that anonymised
• Bring together active data management researchers, data patient data may become available for research, while
scientists, and data practitioners from both the private the patients remain in control of the use of their data.
and public sector
• Identify major challenges in big data management
Furthermore, three of these projects deal with more generic,
• Exchange experiences and best practices in big data horizontal issues that may arise in broader contexts.
management
• Consider the ethical aspects and societal impact of big
data technology • SUPERSEDE develops a big data system whose
purpose is to analyse large volumes of heterogeneous,
• Discuss the importance of world-wide initiatives such as
user-generated and system-generated data on the
the Research Data Alliance (http://www.rd-alliance.org)
Quality of Experience that users have with software
• Clarify the relevance of new roles/job descriptions services and applications so that decisions about the
emerging, such as that of `data scientist’ evolution and adaptation of the latter may be supported.
• Initiate a dialogue among seemingly heterogeneous • TOREADOR offers a Big Data Analytics-as-a-Service
European projects that face similar data management environment aiming at helping organizations that lack
challenges and identify potential concrete actions of the proper big data/data science expertise declare their
collaboration between them big data analytics goals and have the appropriate big
• Connect the data management research community with data pipeline be generated for them, ready to use.
the European funding scene • BigDataEurope is somewhat similar in that it aims to
develop an infrastructure offering diverse big data
computational functionality that may be required in any
This uniquely different EDBT/ICDT workshop is a follow-up of a special track one of the seven EC Societal Challenges (Health, Food,
of the same flavor that was organized for the first time in EDBT/ICDT 2014 in Energy, Transport, Climate, Social Sciences, and
Athens, Greece. Security).
2017, Copyright is with the authors. Published in the Workshop Proc. of the
EDBT/ICDT 2017 Joint Conference (March 21, 2017, Venice, Italy) on CEUR-
WS.org (ISSN 1613-0073). Distribution of this paper is permitted under the
terms of the Creative Commons license CC-by-nc-nd 4.0