- « Big Data Integration », Divesh Srivastava (AT&T Labs, ACM Fellow, Board of trustees VLDB endowment)
Divesh Srivastava is the head of Database Research at AT&T Labs-Research. He is an ACM fellow, on the board of trustees of the VLDB Endowment, the managing editor of the Proceedings of the VLDB Endowment (PVLDB) and an associate editor of the ACM Transactions on Database Systems (TODS). His research interests and publications span a variety of topics in data management.
Abstract: The Big Data era is upon us: data is being generated, collected and analyzed at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of Big Data. BDI differs from traditional data integration in many dimensions: (i) the number of data sources, even for a single domain, has grown to be in the tens of thousands, (ii) many of the data sources are very dynamic, as a huge amount of newly collected data are continuously made available, (iii) the data sources are extremely heterogeneous in their structure, with considerable variety even for substantially similar entities, and (iv) the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This talk explores the progress that has been made by the data integration community in addressing these novel challenges faced by big data integration, and identifies a range of open problems for the community.
- « Big Data: Hype and Reality », Dr C. Mohan (IBM Almaden Research Center)
Dr. C. Mohan has been an IBM researcher for 32 years in the information management area, impacting numerous IBM and non-IBM products, the research and academic communities, and standards, especially with his invention of the ARIES family of locking and recovery algorithms, and the Presumed Abort commit protocol. This IBM, ACM and IEEE Fellow has also served as the IBM India Chief Scientist. In addition to receiving the ACM SIGMOD Innovation Award, the VLDB 10 Year Best Paper Award and numerous IBM awards, he has been elected to the US and Indian National Academies of Engineering, and has been named an IBM Master Inventor. This distinguished alumnus of IIT Madras received his PhD at the University of Texas at Austin. He is an inventor of 40 patents. He has served on the advisory board of IEEE Spectrum and on the IBM Software Group Architecture Board’s Council. Mohan is a frequent speaker in North America, Western Europe and India, and has given talks in 40 countries. More information can be found in his home page at http://bit.ly/CMohan Abstract: Big Data has become a hot topic in the last few years in both industry and the research community. For the most part, these developments were initially triggered by the requirements of Web 2.0 companies. Both technical and non-technical issues have continued to fuel the rapid pace of developments in the Big Data space. Open source and non-traditional software entities have played key roles in the latter. As it always happens with any emerging technology, there is a fair amount of hype that accompanies the work being done in the name of Big Data. The set of clear-cut distinctions that were made initially between Big Data systems and traditional database management systems are being blurred as the needs of the broader set of (“real world”) users and developers have come into sharper focus in the last couple of years. In this talk, I will survey the developments in Big Data and try to distill reality from the hype!
- « Declarative Modeling for Machine Learning and Data Mining », Luc De Raedt (Katholieke Universiteit Leuven, ECCAI fellow)
Abstract: Today, it remains a challenge to develop applications and software that incorporates data mining. One reason is that the field has focussed on developing high-performance algorithms for solving particular tasks rather than on developing general principles and techniques.
I propose to alleviate these problems by applying the constraint programming methodology to machine learning and data mining and to specify data mining tasks as constraint satisfaction and optimization problems. What is essential is that the user be provided with a way to declaratively specify what the data mining problem is rather than having to outline how that solution needs to be computed. This corresponds to a model + solver- based approach to data mining, in which the user specifies the problem in a high level modeling language and the system automatically transforms such models into a format that can be used by a solver to efficiently generate a solution. This should be much easier for the user than having to implement or adapt an algorithm that computes a particular solution to a specific problem.
I shall illustrate this perspective by presenting our work on developing models as well as modeling languages for several data mining tasks. I shall include our recent results on the MiningZinc language and system, an extension of the MiniZinc framework for constraint programming.
La conférence “BDA – Gestion de Données — Principes, Technologies et Applications” est le rendez-vous incontournable de la communauté de la gestion de données en France.
- « Hints on publication: the story of Ike Antkare », Cyril Labbé, LIG Lab, Université Joseph Fourier (« Comment publier : l’aventure d’Ike Antkare »)
- « The life of a researcher : a personal viewpoint », Serge Abiteboul,INRIA & ENS Cachan, Conseil national du numérique (« Faire sa recherche aujourd’hui : un avis personnel »)
Serge Abiteboul obtained his Ph.D. from the University of Southern California, and a State Doctoral Thesis from the University of Paris-Sud. He has been a researcher at the Institut National de Recherche en Informatique et Automatique since 1982 and is now Distinguished Affiliated Professor at Ecole Normale Supérieure de Cachan . He was a Lecturer at the École Polytechnique and Visiting Professor at Stanford and Oxford University. He has been Chair Professor at Collège de France in 2011-12 and Francqui Chair Professor at Namur University in 2012-2013. He co-founded the company Xyleme in 2000. Serge Abiteboul has received the ACM SIGMOD Innovation Award in 1998, the EADS Award from the French Academy of Sciences in 2007; the Milner Award from the Royal Society in 2013; and a European Research Council Fellowship (2008-2013). He became a member of the French Academy of Sciences in 2008, and a member the Academy of Europe in 2011. He is a member of the Conseil National du Numérique and Chairman of the Scientific Board of the Société d’Informatique de France. His research work focuses mainly on data, information and knowledge management, particularly on the Web. He founded and is an editor of the blog binaire.blogs.lemonde.fr.