{"id":96,"date":"2015-02-27T17:04:30","date_gmt":"2015-02-27T17:04:30","guid":{"rendered":"http:\/\/bda2015.univ-tln.fr\/?page_id=96"},"modified":"2015-09-10T12:39:40","modified_gmt":"2015-09-10T12:39:40","slug":"conferenciers-invites-et-ateliers","status":"publish","type":"page","link":"https:\/\/bda2015.univ-tln.fr\/?page_id=96","title":{"rendered":"Conf\u00e9renciers invit\u00e9s et Tutoriel"},"content":{"rendered":"<h1>Conf\u00e9renciers invit\u00e9s<\/h1>\n<ul>\n<ul>\n<li id=\"keynote2\">\n<h2 class=\"western\" lang=\"fr-FR\">\u00ab\u00a0Web s\u00e9mantique : beaucoup de donn\u00e9es, quelques connaissances et un peu de raisonnement. \u00bb<\/h2>\n<p class=\"western\" lang=\"fr-FR\" style=\"text-align: justify;\">Fran\u00e7ois Goasdou\u00e9 (Universit\u00e9 de Rennes 1, ENSSAT-IRISA) et Marie-Christine Rousset (Universit\u00e9 de Grenoble-Alpes, LIG, et Institut Universitaire de France).<\/p>\n<p class=\"western\" lang=\"fr-FR\" style=\"text-align: justify;\"><strong>Abstract :\u00a0<\/strong>Le Resource Description Framework (RDF), standard du W3C pour le Web S\u00e9mantique, suscite un int\u00e9r\u00eat croissant de la part de la communaut\u00e9 Bases de Donn\u00e9es. Ce mod\u00e8le de donn\u00e9es est en effet particuli\u00e8rement adapt\u00e9 \u00e0 la repr\u00e9sentation de Big Data (donn\u00e9es tr\u00e8s volumineuses, h\u00e9t\u00e9rog\u00e8nes et incompl\u00e8tes) et a d\u00e9j\u00e0 une incarnation phare dans le Linked Data (<a title=\"http:\/\/linkeddata.org\" href=\"http:\/\/linkeddata.org\">http:\/\/linkeddata.org<\/a>).<\/p>\n<p class=\"western\" lang=\"fr-FR\" style=\"text-align: justify;\">RDF est un mod\u00e8le flexible qui permet d\u2019exprimer de mani\u00e8re uniforme, sous forme de triplets, des m\u00e9ta-donn\u00e9es sur des entit\u00e9s r\u00e9f\u00e9renc\u00e9es par des URIs, mais aussi des connaissances sur le sch\u00e9ma des classes et des propri\u00e9t\u00e9s, qui constituent ce qu\u2019on appelle souvent des ontologies.<\/p>\n<p class=\"western\" lang=\"fr-FR\" style=\"text-align: justify;\">La mise en \u0153uvre du Web s\u00e9mantique consiste \u00e0 exploiter ces connaissances par des algorithmes de raisonnement pour compl\u00e9ter par inf\u00e9rence l\u2019ensemble des r\u00e9ponses \u00e0 des requ\u00eates, et aussi pour enrichir et lier les donn\u00e9es de plusieurs sources.<\/p>\n<p class=\"western\" lang=\"fr-FR\" style=\"text-align: justify;\"><a name=\"_GoBack\"><\/a> Dans cet expos\u00e9, nous soulignerons les similitudes et les sp\u00e9cificit\u00e9s du mod\u00e8le RDF par rapport aux mod\u00e8les formels des bases de donn\u00e9es d\u00e9ductives et des bases de donn\u00e9es incompl\u00e8tes. Nous d\u00e9gagerons ensuite les d\u00e9fis d\u00e9coulant de ces sp\u00e9cificit\u00e9s pour mettre en \u0153uvre des techniques efficaces d\u2019interrogation ainsi que de liage de donn\u00e9es et de connaissances. Nous pr\u00e9senterons enfin les principales approches propos\u00e9es dans la litt\u00e9rature r\u00e9cente pour relever certains de ces d\u00e9fis.<\/p>\n<p>Fran\u00e7ois Goasdou\u00e9 est Professeur en Informatique \u00e0 l&rsquo;Universit\u00e9 de \u00a0Rennes 1. Ses travaux de recherche sont men\u00e9s \u00e0 l&rsquo;interface des Bases \u00a0de Donn\u00e9es et de la Repr\u00e9sentation des Connaissances &amp; Raisonnement ; \u00a0ils portent sur la gestion efficace de donn\u00e9es (consistance, \u00a0interrogation, mise-\u00e0-jour, etc) dans le cadre des graphes RDF et des \u00a0bases de connaissances OWL2, et dans des architectures centralis\u00e9es, \u00a0d\u00e9centralis\u00e9es et massivement parall\u00e8les. Ses r\u00e9sultats sont \u00a0r\u00e9guli\u00e8rement publi\u00e9s dans les revues et conf\u00e9rences majeures de Bases \u00a0de donn\u00e9es et d&rsquo;Intelligence Artificielle.<\/p>\n<p>Marie-Christine Rousset is a Professor of Computer Science at the University of Grenoble. Her areas of research are Knowledge Representation, Information Integration, Linked Data and the Semantic Web. She has published around 100 refereed international journal articles and conference papers, and participated in several cooperative industry-university projects. She received a best paper award from AAAI in 1996, and has been nominated ECCAI fellow in 2005. She has served in many program committees of international conferences and workshops and in editorial boards of several journals.<\/p>\n<p><em>Chair : Ioana Manolescu<\/em><\/li>\n<li id=\"keynote3\" style=\"text-align: justify;\">\n<h2>\u00ab Accommoder les\u00a0miettes de donn\u00e9es : Ingr\u00e9dients, Recettes et Astuces \u00bb<\/h2>\n<p>Am\u00e9lie Marian (Rutgers U) et Arnaud Sahuguet (NYU Urban Science)<\/p>\n<p><strong>Abstract<\/strong> :\u00a0Notre existence devient chaque jour de plus en plus digitale. Nos interactions sociales, professionnelles, \u00e9ducatives, financi\u00e8res, sportives, culturelles, etc. sont d\u00e9sormais conduites via des interm\u00e9diaires digitaux. Pour chacune de ces interactions, une trace digitale est cr\u00e9\u00e9e.<br \/>\nCes miettes de donn\u00e9es constituent un r\u00e9servoir de connaissances \u00e9norme et encore mal exploit\u00e9 pour les individus, le secteur priv\u00e9 mais aussi le secteur public. Ces miettes repr\u00e9sentent \u00e0 la fois un immense espoir \u2013 m\u00e9decine personnalis\u00e9e, assistant personnel intelligent, ville intelligente \u2013 mais aussi une terrible crainte \u2013 surveillance \u00e9tatique, fin de la vie priv\u00e9e, hyper-marketing.<br \/>\nDans cet expos\u00e9, nous passerons en revue les diff\u00e9rents types de donn\u00e9es g\u00e9n\u00e9r\u00e9es par nos interaction digitales; les mod\u00e8les de donn\u00e9es et m\u00e9tadonn\u00e9es qui y sont associ\u00e9es; les techniques de stockage et de requ\u00eates associ\u00e9es; ainsi que des exemple d&rsquo;usages pour des produits grand public, des applications li\u00e9es \u00e0 la recherche m\u00e9dicale et des applications citoyennes.<\/p>\n<p><span style=\"line-height: 1.714285714; font-size: 1rem;\"><span style=\"line-height: 1.714285714; font-size: 1rem;\">Am\u00e9lie Marian is an Associate Professor in the Computer Science Department at Rutgers University. Her research interests are in Personal Information Management, Ranked Query Processing, Semi-structured data and Web data Management. Am\u00e9lie received her Ph.D. in Computer Science from Columbia University in 2005. From March 1999 to August 2000, Am\u00e9lie was a member of the VERSO project at INRIA-Rocquencourt. She received B.S. and M.S. degrees from Universit\u00e9 Paris Dauphine, France in 1998 and 1999, respectively. She is the recipient of a Microsoft Live Labs Award (2006), three Google Research Awards (2008, 2010, and 2012) and an NSF CAREER award (2009).<\/span><\/span><\/p>\n<p><span style=\"line-height: 1.714285714; font-size: 1rem;\">Dr Arnaud Sahuguet is a technologist and entrepreneur with a passion to invent, architect and build products that leverage technology to solve meaningful problems and have a large social impact. His goal is to empower people and organizations to be more productive and collaborative through innovation.\u00a0<\/span><span style=\"line-height: 1.714285714; font-size: 1rem;\">Before joining GovLab as Chief Technology Officer, Arnaud spent 8 years at Google as a product manager for speech recognition and Google Maps; he founded and launched \u00a0the OneToday mobile fundraising platform for <\/span><a style=\"line-height: 1.714285714; font-size: 1rem;\" href=\"http:\/\/Google.org\">Google.org<\/a><span style=\"line-height: 1.714285714; font-size: 1rem;\">; he also worked on child protection and civic innovation. Before Google, he spent 5 years at Bell Labs research as member of technical staff working on standardization, identity management and converged services.\u00a0<\/span><span style=\"line-height: 1.714285714; font-size: 1rem;\">Arnaud holds a PhD in Computer Science from Univ. of Pennsylvania, a MSc from Ecole Nationale des Ponts et Chauss\u00e9es and a BSc from Ecole Polytechnique in France.\u00a0<\/span><span style=\"line-height: 1.714285714; font-size: 1rem;\">Full profile at <\/span><a style=\"line-height: 1.714285714; font-size: 1rem;\" href=\"https:\/\/www.linkedin.com\/in\/sahuguet\">https:\/\/www.linkedin.com\/in\/sahuguet<\/p>\n<p><\/a><em>Chair : David Gross-Amblard<\/em><a style=\"line-height: 1.714285714; font-size: 1rem;\" href=\"https:\/\/www.linkedin.com\/in\/sahuguet\"><br \/>\n<\/a><\/li>\n<li id=\"keynote1\" style=\"text-align: justify;\">\n<h2>\u00ab Data integration challenges raised by self-service Business Intelligence\u00a0\u00bb<\/h2>\n<p>Eric Simon, SAP France<\/p>\n<p><strong>Abstract<\/strong> :\u00a0Enterprise Business Intelligence (BI) traditionally provides solutions to business users for managed reporting (ad-hoc query and reporting or pixel-perfect reporting), dashboards and data analysis. BI solutions heavily rely on the IT organization to create the data warehouse and data marts underpinning the BI system, as well as the semantic layers specifically designed over this trusted data foundation to model information used by reports, dashboards and analytic queries. A decade ago, BI has evolved to empower business users to create personalized reports and analytical queries, and let them manipulate and explore information directly, without resorting to IT. Business users and analysts are now demanding access to true \u201cself-service\u201d capabilities beyond data discovery and rich interactive visualization of IT-curated data sources, to include access to sophisticated data integration tools to prepare their data for analysis, and data governance capabilities. This growing demand raises the need for new data-driven and iterative solutions better suited to business users than the traditional \u00ab\u00a0design-test-deploy\u00a0\u00bb paradigm typically adopted by IT organizations. In this paradigm shift, business users \u00ab\u00a0model their data as they go\u00a0\u00bb creating their own analyses, reports and performance indicators. Business users need new powerful data-driven and interactive user interfaces as well as new capabilities to search for data, easily assess the quality of data, semi-automate the curation, profiling, and enrichment of data, and suggest how to expand and combine datasets that are semantically related depending on the user interaction context and profile. This talk will review the requirements of \u00ab\u00a0self-service BI\u00a0\u00bb and explain the technical challenges it raises to provide more data-driven data integration solutions. Some of the recent directions taken by SAP in this field will be outlined and illustrated. Open issues will be presented at the end.<\/p>\n<p><em>Chair : Christine Collet<\/em><\/li>\n<\/ul>\n<\/ul>\n<h1 id=\"tutoriels\">Tutoriels<\/h1>\n<ul>\n<ul>\n<li style=\"text-align: justify;\">\n<h2>\u00ab\u00a0Data cleaning in the big data era\u00a0\u00bb<\/h2>\n<p>Paolo Papotti and Jorge Quian\u00e9-Ruiz,\u00a0Qatar Computing Research Institute (QCRI)<\/p>\n<p><strong>Abstract<\/strong> : In the \u00ab\u00a0big data\u00a0\u00bb era, data is often dirty in nature because of several reasons, such as typos, missing values, and duplicates. The intrinsic problem with dirty data is that it can lead to poor results in analytic tasks. For instance, Experian QAS Inc. reported that poor customer data cost British businesses \u00a38 billion loss of revenue in 2011. Therefore, data cleaning is an unavoidable task to have reliable data for final applications, such as querying and mining. Data cleaning (a.k.a. data preparation) is a popular activity in both industry and in academia. Nevertheless, data cleaning is hard in practice as it requires a great amount of manual work. Several systems have been proposed to achieve the level of automation and scalability required by the volume and variety in big data. They rely on a formal, declarative approach based on first order logic: users provide high-level specifications of their tasks (the \u00ab\u00a0what\u00a0\u00bb); the systems compute optimal solutions without human intervention on the generated code (the \u00ab\u00a0how\u00a0\u00bb). However, despite the positive results in automating the data cleaning task, the volume (scalability) and variety of big data remain two open problems. In this tutorial, we first describe recent results in tackling data cleaning with a declarative approach. We then discuss how this experience has pushed several groups to explore a new approach to the problem to deal with the volume and variety of big data. In particular, we discuss how user defined functions and declarative specifications can coexist in a unified system, ultimately taking the best from both worlds.<\/p>\n<p>Chair : Sihem Amer-Yahia<\/li>\n<\/ul>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Conf\u00e9renciers invit\u00e9s \u00ab\u00a0Web s\u00e9mantique : beaucoup de donn\u00e9es, quelques connaissances et un peu de raisonnement. \u00bb Fran\u00e7ois Goasdou\u00e9 (Universit\u00e9 de Rennes 1, ENSSAT-IRISA) et Marie-Christine Rousset (Universit\u00e9 de Grenoble-Alpes, LIG, et Institut Universitaire de France). Abstract :\u00a0Le Resource Description Framework (RDF), standard du W3C pour le Web S\u00e9mantique, suscite un int\u00e9r\u00eat croissant de la part [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-96","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/pages\/96","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=96"}],"version-history":[{"count":22,"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/pages\/96\/revisions"}],"predecessor-version":[{"id":266,"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=\/wp\/v2\/pages\/96\/revisions\/266"}],"wp:attachment":[{"href":"https:\/\/bda2015.univ-tln.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=96"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}