- Program Overview
- Detailed Program
- Workshop Program
- EDBT Awards
- Guidelines for Presenters
- EDBT/ICDT/Workshop accepted papers
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The following six workshops are all co-located with the EDBT/ICDT 2017 conference in Venice, Italy.
The workshops will be held on Tuesday, March 21, 2017.
Refer to the websites of each workshop for the pertinent call for papers.
DOLAP: 19th International Workshop On Design, Optimization, Languages and Analytical Processing of Big Data
Organizers: Il-Yeol Song (Drexel, USA), Patrick Marcel (University of Tours, France)
Data Warehouse (DW) and Online Analytical Processing (OLAP) technologies are the core of current Decision Support Systems. The widespread deployment of both DWs and OLAP technologies is due to the intuitive representation of data and simple primitives provided to data analysts or managers in support of management decisions. Research in data warehousing and OLAP has produced important technologies for the design, management and use of information systems for decision support.
BI of the future will be significantly different than what the current state-of-the-practice supports. The trend is to move from the current decision support systems that are "data presenting" to more dynamic systems that allow the semi-automation of the decision making process. This means that the systems partially guide their users towards data discovery, intuition and system-aided decision making via intelligent techniques and visualization. In the back stage, the thrust of the big data era, with the requires that new methods, models, techniques, or architecture are needed to cope with the increasing demand in capacity, data type diversity and responsiveness. And of course, this does not necessarily mean to re-invent the wheel, but rather, as recommended by Gartner to companies regarding BD adoption, "Build on existing BI programs - don't abandon or segregate them". We envision DOLAP 2017 as a venue where novel ideas around these new landscapes of business intelligence and big data are fostered and nurtured and new exiting results are produced, in an attempt to build a strong, vibrant community around these areas.
Organizers: Federica Mandreoli (FIM - University of Modena and Reggio Emilia, Italy), Riccardo Martoglia (FIM - University of Modena and Reggio Emilia, Italy), Wilma Penzo, (DISI - University of Bologna, Italy)
The growing scale and importance of graph data in several database application areas has recently driven much research efforts towards the development of data models and technologies for graph-data management.
Life science databases, social networks, Semantic Web data, bibliographical networks, knowledge bases and ontologies, are prominent examples of application domains exhibiting data that is natural to represent in graph-based form. Datasets in these domains are often characterized by heterogeneity, complexity and largeness of contents that make the querying experience a really challenging task.
The overall goal of the GraphQ workshop is to bring people from different fields together, exchange research ideas and results, and encourage discussion about how to efficiently and effectively support graph queries in different application domains. GraphQ seeks at providing the opportunity for inspiration and cross-fertilization for the many research groups working on graph-structured data, with a particular focus on the querying issues.
The workshop will welcome innovative papers from academic and industrial researchers in the fields of information retrieval, relational databases, Semantic Web, streaming data management, pattern matching, biological databases, social networks, human-computer interaction, and other related areas.
Organizers:Devis Bianchini (Università di Brescia, Italy), Valeria De Antonellis (Università di Brescia, Italy), Roberto De Virgilio (Università Roma Tre, Rome, Italy)
The joint application of data management and Semantic Web competencies, through the design of new models, languages and tools, has turned out to be very useful to enable the use of the Web as a huge, interlinked, dynamic repository of linked resources. The contributions and discussions born and developed during six previous editions of the Linked Web Data Management (LWDM) workshop allowed to meet our goal of introducing a data management perspective within the Linked Data world, previously focused on publishing, retrieving, querying, browsing and mashing-up the ever growing amount of linked data in a meaningful way. The maturity gained by the workshop also enabled to introduce in these years new issues related with the main topics: (a) fruitful contributions on the combination of knowledge coming from data management, Semantic Web and Linked Data fields; (b) the study of Linked Data issues within a social perspective of the Web, where also the relationships between users might play a crucial role in finding the right resources in an efficient way; (c) the need of facing the quantity and the heterogeneity of data made available on the Web, also managing with the rapidity which such data are distributed with (Big Data issues). These problems also feature the Linked Data world to access and explore linked resources, thus requiring innovative application of data management tools.
The Seventh International Workshop on Linked Web Data Management (LWDM) aims to stimulate participants to discuss about data management issues related to the Linked Data and the relationships with other Semantic Web technologies, proposing new models, languages and applications that exploit the Web as a huge, interlinked, dynamic repository of linked resources.
Organizers: Dimitris Kotzinos (Université de Cergy-Pontoise, France), Vassilis Christophides (University of Crete & INRIA Paris - Rocquencourt, France), Charalampos Nikolaou (University of Oxford, UK), Yannis Theodoridis (University of Piraeus, Greece)
Big Geo Data represents an important type of the crowd sourced data that are available today at a global scale. This kind of data refers to
locations, i.e., Points of Interest (POIs), and is usually published in social media (e.g., Facebook, Google+) or in specialized platforms
(e.g., Open Street Maps, Yelp). The quality (e.g., precision, accuracy, consistency) of crowd sourced geo data depends on the origin (machine vs. human generated), the level of detail of the extraction techniques, as well as the obfuscation techniques used to protect users’ privacy.
There is clearly a tradeoff between enhancing the quality of published geo data and the privacy risks entailed for the individuals, also known as
geoprivacy, to uncover places visited, trajectories pursuit etc. Understanding the different aspects of geographic/geometric/geospatial
quality involved in crowd-sourced geo data and assessing the privacy risks introduced by enhancing its quality in personal, social, and urban
applications is a challenging topic.
The BIGQP workshop aims to be a premier venue in gathering computer science and geoscience researchers who are contributing to and are interested in both Data Quality and Privacy of Big Geo Data. Hence, it is a unique opportunity to find in a single place up-to-date scientific works on both subjects that have so far only partially been addressed by different research communities such as Data Quality Management, Distributed and Mobile Systems, Internet of Things, and Big Data Privacy.
Organizers: Nicola Ferro (University of Padua, Italy), Francesco Guerra (University of Modena and Reggio Emilia, Italy) Zachary G. Ives (University of Pennsylvania, USA), Gianmaria Silvello (University of Padua, Italy), Martin Theobald (Ulm University, Germany)
Keyword search is the foremost approach for searching information and it has been successfully applied for retrieving non-structured documents such as text and multimedia files. Nonetheless, retrieving information from (unstructured or semi-structured) documents is intrinsically different from querying structured data sources with either an explicit schema, as relational databases or triple stores, or an implicit one, as tables in textual documents and on the Web.
Structured queries are not end-user oriented and far away from a natural expression of users’ information needs by means of keywords, given that their formulation is based on a quite complex syntax and requires some knowledge about the structure of the data to be queried.
The aim of this multidisciplinary workshop is to bring together researchers from Databases, Information Retrieval, Natural Language Processing, Semantic Web, Human-Computer Interaction, and to combine their perspectives and research to address the above-mentioned issues. In particular, we wish to encourage researchers to discuss the opportunities, challenges, results obtained in the development and evaluation of “complete”, “ready-to-market” keyword search applications over structured data. We are in particular interested in proposal dealing with systemic approaches which manage all the phases of the keyword search, from the management of the data, query formulation, interpretation, computation, ranking and visualization of the results, as well as rigorous evaluation methodologies for such systems.
Organizers: Yannis Ioannidis (University of Athens & “Athena” Research Centre, Greece)
The main objective of this workshop is to share experiences and best practices, discuss challenges and effective solutions adopted, and investigate opportunities for collaboration among European projects (various directorates of the European Commission or other European funding agencies) dealing with big data management. The projects may have ICT as their main focus but may equally well have some other scientific field, industrial application, or societal challenge as their main focus, in the context of which big data issues come up.