Important dates
All deadlines are due 11pm GMT
Workshop proposals: December 12th, 2011
Full paper submission: March 19th, 2012
PhD Symposium submission: April 15th, 2012
Tutorials, panel, and demos proposals: May 8th, 2012
Paper notification: May 14th, 2012
Camera-ready paper submission: June 11th, 2012
Author Registration Deadline: June 25th, 2012
Conference: October 15th-18th, 2012
31st International Conference on Conceptual Modeling (ER 2012) - Florence, Italy
Keynote Speakers Print

Mega-Modeling for Scientific Data Processing

 

Stefano Ceri

Dipartimento di Elettronica e Informazione
Politecnico di Milano, Italy

 

 

 

 

 

 

 

 

ABSTRACT

The availability of huge amounts of data ("big data") is changing our attitude towards science, which is moving from specialized to massive experiments and from very focused to very broad research questions. Models of all kinds, from analytic to numeric, from exact to stochastic, from simulative to predictive, from descriptive to ontological, enable massive data analysis and mining, often in real time. Scientific discovery in most cases stems from complex pipelines of data analysis and data mining methods on top of "big" experimental data, confronted and contrasted with state-of-art knowledge. In this setting, I will discuss the concept of mega-modelling as a new holistic abstraction for the acquisition, composition, integration, management, querying and mining of data and patterns, capable of supporting what-if analyses, predictive analytics and scenario explorations.

 

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BIO:Stefano Ceri is professor at the Dipartimento di Elettronica e Informazione (DEI), Politecnico di Milano; he was a visiting professor at the Computer Science Department of Stanford University between 1983 and 1991. He is the Director of Alta Scuola Politecnica (ASP), a school of excellence emphasizing innovation and multidisciplinarity, for master-level students of Politecnico di Milano and Politecnico di Torino. He is author of more than 300 articles on International Journals and Conference Proceedings and of 11 international books, with an H-index 56. He is co-inventor of WebML, a model for the conceptual design of Web applications (US Patent 6,591,271, July 2003), and co-founder in 2001 of Web Models, a spinoff company of Politecnico di Milano which commercializes WebML by means of the product WebRatio. He is the recipient of the ERC IDEAS Grant "Search Computing" (SeCo), a multi-disciplinary project providing the abstractions, foundations, methods, and tools required to give answer to complex search queries. The project spans from Nov. 1, 2008 to Oct. 31, 2013; the major results include a series of three books with Springer-Verlag, numerous articles and demos, and a recently awarded patent.

 

Date: Monday, October 15, 2012
Time: 9:30 - 11:00
Room: Sala Michelangelo
Chair: David Cheung

 

The Spatial Web – A New Data Management Frontier

 

Christian Jensen

Department of Computer Science
Aarhus University, Denmark

 

 

 

 

 

 

 

 

 

ABSTRACT

The sales of mobile devices such as smartphones are skyrocketing, and the web is accessed increasingly by mobile users. Similarly, we are witnessing a proliferation of positioning capabilities. As a result, a spatial, or geographical, web is emerging where content and users are associated with locations that are used in a wide range of location-based services. Studies suggest that each week, several billion web queries have local intent and target so-called spatial web objects, i.e., points of interest with a web presence that have locations as well as textual descriptions.

This development has given prominence to spatial web data management, and it opens a research area full of new and exciting opportunities and challenges. A spatial web query takes a user location and user-supplied keywords as arguments and returns web objects that are spatially and textually relevant to these arguments. Due perhaps to the rich semantics of geographical space and its importance to our daily lives, many different kinds of relevant spatial web queries may be envisioned.

Based on recent and ongoing work by the speaker and his colleagues, the talk offers an account of a quest for spatial web querying functionality that is easy to use, that is relevant to users, and that can be supported efficiently. The talk will illustrate different kinds of functionality and the ideas underlying their definition, and it will describe briefly techniques that are capable of supporting the functionality.

 

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BIO: Christian S. Jensen is a Professor of Computer Science at Aarhus University, Denmark, and he was previously at Aalborg University for two decades. He recently spent a 1-year sabbatical at Google Inc., Mountain View. His research concerns data management and data-intensive systems, and its focus is on temporal and spatio-temporal data management. Christian is an ACM and an IEEE fellow, and he is a member of the Royal Danish Academy of Sciences and Letters and the Danish Academy of Technical Sciences. He has received several national and international awards for his research. He is currently vice-chair of ACM SIGMOD and an editor-in-chief of The VLDB Journal.

 

Date: Tuesday, October 16, 2012
Time: 8:30 - 10:00
Room: Sala Michelangelo
Chair: Sudha Ram

 

 

Of Cubes, DAGs & Hierarchical Joins: A Novel Conceptual Model for Analyzing Social Media Data

 

Umesh Dayal

HP Labs
Palo Alto, CA, US

 

 

 

 

 

 

 

ABSTRACT

With the advent of social media, there is an ever increasing amount of unstructured data that can be analyzed to obtain insights. Two prominent examples are sentiment analysis and the discovery of correlated concepts. A convenient representation of information in such scenarios is in terms of concepts extracted from the unstructured data, and measures, such as sentiment scores, associated with these concepts. Typically, social media analysis reports these concepts and their associated measures. We argue that much richer insights can be obtained through the use of OLAP-style multidimensional analysis. It is fairly straightforward to see how to add traditional dimension hierarchies such as time and geography, and to analyze the data along these dimensions using traditional OLAP operations such as roll-up; for instance, to answer queries of the form “What was the average sentiment for X in Europe during the past month?” However, it is trickier to answer queries of the form “What was the average sentiment for concepts related to X in Europe during the past month?” We introduce a conceptual modeling framework that extends traditional multidimensional models and OLAP operators to address the new set of requirements for data extracted from social media. In this model, we organize data along both traditional dimensions (we call these metadata dimensions) and concept dimensions, which model relationships among concepts using parent-child hierarchies. Specifically: (i) we allow operations on parent-child hierarchies to be treated in a uniform way as we treat operations on traditional dimension hierarchies; (ii) to model the rich relationships that can exist among concepts, we extend the parent-child hierarchies to be rooted level-DAGs rather than simply trees; and (iii) we introduce new equivalence classes that allow us to reason with “similar” concepts in new ways with specific application to approximate joins. We show that our modeling and operator framework facilitates multidimensional analysis to gain further insights from social media data than is possible with existing methods.

 

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BIO: Umeshwar Dayal is an HP Fellow and Director of the Information Analytics Lab at Hewlett-Packard Labs, Palo Alto, California. Umesh has over 30 years of research experience in data and information management. His current research interests are in enterprise-scale information management, live business intelligence, data mining, analytics, and information visualization. Prior to joining HP Labs, he was a senior researcher at DEC's Cambridge Research Lab, Chief Scientist at Xerox Advanced Information Technology and Computer Corporation of America, and on the faculty at the University of Texas-Austin. He received his PhD from Harvard University. He has published over 200 papers and holds over 50 patents. Umesh is an ACM Fellow, and the recipient of the 2010 Edgar F Codd Award from ACM SIGMOD for his contributions to data management. In 2001, Umesh and two co-authors received the VLDB 10-year Best Paper Award for their 1991 paper on a transactional model of long-running activities. He is on the Editorial Board of several international journals, has edited two books, and has chaired and served on the Program Committees of numerous conferences. He is currently a member of the Steering Committees of the IEEE International Conference on Data Engineering, the ER Conference on Conceptual Modeling, and the SPIE International Conference on Visualization and Data Analysis, and has served as a member of the Board of the VLDB Endowment, the Board of the International Foundation for Cooperative Information Systems, and the Steering Committee of the SIAM Data Mining Conference. Umesh can be reached at This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

 

Date: Wednesday, October 17, 2012
Time: 8:30 - 10:00
Room: Sala Michelangelo
Chair: Paolo Atzeni