- EDBT/ICDT 2012
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- Local information
- Venue / Rooms
- Program Overview
- Detailed Program
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- EDBT Camera-Ready
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EDBT/ICDT 2012 Workshops
The following workshops are all co-located with the EDBT/ICDT 2012 conferences in Berlin, Germany. The workshops are all held on Friday, March 30, 2012.
More detailed descriptions and web links will be provided soon.
Joint EDBT/ICDT Ph.D. Workshop 2012
Organizers: Bernhard Volz (University of Bayreuth, Germany), Sascha Müller-Feuerstein (Ansbach University of Applied Sciences, Germany)
The joint EDBT/ICDT Ph.D. Workshop is intended to bring together Ph.D. students working on topics related to the EDBT and the ICDT conference series. The workshop will offer Ph.D. students the opportunity to present, discuss, and receive feedback on their research in a constructive and international atmosphere. The intention of this workshop is to support and inspire Ph.D. students during their ongoing research efforts. Therefore, it is necessary that authors will have neither achieved their Ph.D. degree nor officially submitted their thesis before the Ph.D workshop (March 30, 2012).
The workshop will be accompanied by prominent professors and researchers in the field of database technology and theory. These experienced researchers will participate actively and contribute to the discussions. The best submission will be rewarded with the EDBT/ICDT Ph.D. Workshop Best Submission Award.
Homepage: Joint EDBT/ICDT Ph.D. Workshop 2012
Energy Data Management (EnDM2012)
Organizers: Professor Torben Bach Pedersen, Aalborg University, Denmark (firstname.lastname@example.org) − Professor Wolfgang Lehner, Dresden University of Technology, Germany (email@example.com) − Dr. Gregor Hackenbroich, SAP Research CEC Dresden, Germany (firstname.lastname@example.org)
This workshop focuses on conceptual and system architecture issues related to the management of very large-scale data sets specifically in the context of the challenging energy domain.
The energy sector is one of the most active application domains being forced to re-think the current practice and apply data-management based IT solutions to provide a scalable and sustainable supply and distribution of energy. Challenges range from energy production by seamlessly incorporating renewable energy resources over energy distribution and monitoring to controlling energy consumption. Decisions are based on huge amounts of empirically collected data from smart meters, new energy sources (increasingly RES - renewable energy sources such as wind, solar, hydro, thermal, etc), new distributions mechanisms (Smart Grid), and new types of consumers and devices, e.g., electric cars. Energy is at the top of the worldwide political agenda, ambitious goals for reductions of energy consumption and CO2 emissions have been formulated, and research funding is increasing rapidly.
This workshop focuses on conceptual and system architecture issues related to the management of very large-scale data sets specifically in the context of the energy domain. The overall goal is to bridge the gap between domain experts and data management scientists on the one hand. On the other hand, the workshop’s goal is to create awareness of this upcoming and very challenging application area. For the workshop’s research program, we are seeking contributions that push the envelope towards novel schemes for large-scale data processing with special focus on energy data management.
Data Analytics in the Cloud (DanaC)
Organizers: Tim Kraska (UC Berkeley, USA), Kostas Tzoumas (TU Berlin, Germany)
Steering committee: Michael J. Carey (UC Irvine, USA), Volker Markl (TU Berlin, Germany)
Due to unprecedented data growth, a need for rich data analysis on petabyte-scale data is emerging. To support such analysis, new data-centric programming paradigms and data management systems are being established, popularized by Google's MapReduce framework and its open-source implementation, Hadoop. The new data analysis market raises several research challenges spanning the whole system stack, from storage and network technologies to programming languages.
At the same time, cloud computing is emerging as a cost-effective paradigm for massively scalable, fault-tolerant, and adaptive computation. Cloud computing architectures scale to massive numbers of commodity computers and adapt to changing hardware availability and requirements by dynamically allocating virtualized computing nodes. Cloud computing systems often use a computational model motivated by functional programming, abstracting away the internals of computation. Both enterprise and client data are moving to the cloud for reasons of cost, reliability, and manageability. This migration poses significant challenges on current systems. The economies of scale provided by cloud computing provide opportunities for richer data analysis on even larger data sets. The new data analysis applications and the unprecedented scale is not adequately served by current offerings, including commercial DBMSs and analytics systems, and open-source cloud computing systems.
This workshop will provide a perfect forum to bring together researchers and practitioners interested in big data analytics, cloud computing, and their intersection. The workshop will help to foster future collaborations and the formation of a community that sets the ground of this emerging field.
Linked Web Data Management (LWDM)
Organizers: Devis Bianchini (Università agli studi di Brescia, Italy), Valeria De Antonellis (Università agli studi di Brescia, Italy), Roberto De Virgilio (Università Roma Tre, Italy)
LWDM focuses on data management issues related to Linked Data and the relationships with other Semantic Web technologies that exploit the Web as a huge, interlinked, dynamic repository of linked resources.
In recent years, the Linked Data perspective of the Web focused the attention of research efforts to build, maintain and exploit the Web as a global database, where resources are identified (by means of URIs), semantically described (by means of RDF) and connected through RDF links. Applications like DBpedia have become a reality to extract and to make structured information available on the Web, going beyond the potential of Web 2.0 and enabling people and applications to discover new linked information in an unexpected way, according to an explorative perspective. Around the Linked Data perspective, several applications have been proposed to publish, retrieve, query, browse and mash-up linked data in a meaningful way, to build new, value-added applications that fit domain-specific goals. Nevertheless, the great availability of Linked Data raises data management issues, that must be faced in a dynamic, highly distributed and heterogeneous environment such as the Web.
The Second International Workshop on "Linked Web Data Management" ( LWDM2012 ) aims at stimulating 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.
Privacy and Anonymity in the Information Society (PAIS)
Organizers: Traian Marius Truta (Northern Kentucky University, U.S.A.), Li Xiong (Emory University, U.S.A.), Farshad Fotouhi (Wayne State University, U.S.A.)
Organizations collect vast amounts of information on individuals, and at the same time they have access to ever-increasing levels of computational power. Although this conjunction of information and power provides great benefits to society, it also threatens individual privacy. As a result legislators for many countries try to regulate the use and the disclosure of confidential information. Various privacy regulations (such as USA Health Insurance Portability and Accountability Act, Canadian Standard Association's Model Code for the Protection of Personal Information, Australian Privacy Amendment Act, etc.) have been enacted in many countries all over the world and, following that, data privacy and protecting individuals' anonymity have become a mainstream avenue for research. The Privacy and Anonymity in Information Society (PAIS'12) Workshop will provide an open yet focused platform for researchers and practitioners from computer science and other fields that are interacting with computer science in the privacy area such as statistics, healthcare informatics, and law to discuss and present current research challenges and advances in data privacy and anonymity research.
Business intelligencE and the WEB (BEWEB)
Organizers: Malu Castellanos (HP Laboratories, Palo Alto, USA), Florian Daniel (University of Trento, Italy), Irene Garrigós (University of Alicante, Spain), Jose-Norberto Mazón (University of Alicante, Spain)
Over the last decade, we have been witnessing an increasing use of Business Intelligence (BI) solutions that allow enterprise to query, understand, and analyze business data in order to make better decisions. Traditionally, BI applications allowed business people to acquire useful knowledge from the data of their organization by means of a variety of technologies, such as data warehousing, OLAP or data mining. Yet, in the very recent years, a new trend emerged: BI applications no longer limit their analysis to the data inside a company. Increasingly, they also source their data from the outside and complement company-internal data with value-adding information, i.e., from the Web, (e.g., retail prices of products sold by competitors), in order to provide richer insights into the dynamics of today's business. In parallel to the move of data from the Web into BI applications, BI applications are experiencing a trend from company-internal information systems to the cloud: BI as a service (e.g., hosted BI platforms for small- and medium-size companies) is the target of huge investments and the focus of large research efforts by industry and academia.
The International Workshop on Business intelligencE and the WEB (BEWEB) intends to target the above two moves and creates an international forum for exchanging ideas on how to leverage the huge amount of data that is available on the Web in BI applications, and how to apply Web-related engineering methods and techniques to the design of BI applications, such as BI as a service.