Photos of the conference are available.
Alon Halevy heads the Structured Data Management Research group at Google. Prior to that, he was a professor of Computer Science at the University of Washington in Seattle, where he founded the database group. In 1999, Dr. Halevy co–founded Nimble Technology, one of the first companies in the Enterprise Information Integration space, and in 2004, Dr. Halevy founded Transformic Inc., a company that created search engines for the deep web, and was acquired by Google. Dr Halevy is a Fellow of the Association for Computing Machinery, received the the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2000, and was a Sloan Fellow (1999–2000). He received his Ph.D in Computer Science from Stanford University in 1993.
Best-Effort Modeling of Structured Data on the Web
The World-Wide Web provides access to millions of data table with high-quality content, either in HTML tables, lists or other structured formats. These tables contain data about virtually every domain of interest to mankind. Creating a conceptual model, in the traditional sense, for such a collection of data is impractical because of the breadth of the data, the fact that domains overlap in complex ways, and that modeling assumptions differ depending on the level of detail and cultural context.
I will describe several projects at Google whose goal is to leverage this collection of data and to make it easier to create and share new data sets. In each case, I will explain the challenges arising from the lack of a conceptual model. In the WebTables Project we collected over 100 million high-quality HTML tables, developed search over this collection. We used information from text on the Web to recover some of the semantics of these tables. In Google Fusion Tables, we make it easy for data owners to upload and manipulate their data, create visualizations and discover other data sets that may be relevant to them, all this without requiring them to a priori create a model of their data.
Stefano Spaccapietra is Emeritus professor at the Swiss Federal Institute of Technology (EPFL), Switzerland, where he headed the database laboratory. He has been in academic positions all along his career. He got his PhD from the University of Paris VI, in 1978, where he first had his master in Computer Science in 1969. At that time, he has been teaching file systems, later turned into teaching database systems. He moved to the University of Burgundy, Dijon, in 1983 to take a professor position at the Institute of Technology. He left Dijon for EPFL in 1988.
Prof. Spaccapietra is a Fellow of the IEEE and recipient of the IFIP Silver Core Award. He is Editor-in-chief of the Journal of Data Semantics (LNCS subline), Springer. He is member of the editorial boards of the Data and Knowledge Engineering Journal (Elsevier), the Internet and Web Information Systems Journal (Kluwer), the Revue Internationale de Géomatique (Hermes), and the Computing Letters Journal (CoLe), VSP/Brill. He was former Chair of the IFIP Working Group 2.6 "Databases" and of the ER Conferences Steering Committee.
Adding Meaning to your Steps
Mobility has been stated to be one of the three major computer science domains for the current decade. Indeed, the challenge to develop the state of art in this domain is scientifically exciting and the number of foreseeable new applications is huge. This talk addresses one piece of the puzzle: providing a conceptual framework for turning the spatio-temporal traces generated by moving objects (be they humans, animal, or things) into information meaningful for the application at hand. A moving object in this context is an object whose position in geographical space changes over time.
The talk discusses the concepts that may play a role in giving a structure to the raw (e.g. GPS) data in a movement track. Next, it surveys methods to extract further knowledge, providing several examples from different application areas. Finally, it considers privacy concerns that must be covered when monitoring people's tracks.
Carson Woo is Stanley Kwok Professor of Business, Sauder School of Business, University of British Columbia, and an associate member of the Department of Computer Science at the same university. He received his B.Sc., M.Sc., and Ph.D. degrees in Computer Science from the University of Toronto. His research interests include conceptual modeling, systems analysis and design, and requirements engineering. In particular, he is interested in using conceptual models to help management in digesting information and deriving knowledge through documentation, investigation, and planning. Dr. Woo is editor of Information Technology and Systems abstracts journal at the Social Science Research Network (ITS-SSRN) as well as serving on the editorial board of ACM Transactions on Management Information Systems and Requirements Engineering. He was conference co-chair of the 29th International Conference on Conceptual Modeling (ER’2010) and program co-chair of the 14th International Conference on Advanced Information Systems Engineering (CAiSE 2002). He has served as President of Workshop on Information Technology and Systems (WITS), Inc. (2004-2006) and chair of ACM Special Interest Group on Office Information Systems (SIGOIS) 1991-1995.
The Role of Conceptual Modeling in Managing and Changing the Business
Each business evolves and changes over time, due to growth, downsizing, and new generations of consumers. The changes can be so complex that even organizational workers involved in the change might only have their own narrow perspective of the overall picture of the business. This can result in problems such as duplication of work and conflicting messages to customers. For a systems analyst in such an organization, it can be very challenging to gather requirements for conceptual modeling.
This challenge is also an opportunity. Systems analysts are trained to map abstract knowledge into explicit knowledge, because this is needed to develop information systems. The result of this mapping is usually some kind of a diagram or conceptual model. If systems analysts can go one step further and utilize this conceptual model to assist organizational workers in their problem solving, then conceptual modeling will have a dual role: developing IT, and managing the changes occurring in the business.
To illustrate how conceptual models can be used to assist organizational workers in their problem solving, we present examples from our research. We focus on developing approaches to conceptual modeling that are derived from research on management. It is only through using management concepts (rather than IT concepts) that conceptual models can potentially support the organizational worker. To reach this objective, we view business as consisting of organizational actors, who each represent an organizational worker role, and have a goal and a thought process.
We analyzed the goals of organizational actors from both the business and the IT sides, to assess alignments between business strategies and IT requirements. By studying this alignment, we found misalignments between the business's need and the requirements for developing an IT system. The misalignments are most predominant at the middle manager level. The conceptual models we developed for these cases helped middle managers to revise their interpretations of the business’s need, and aligned them with the strategic intent.
In addition, understanding an actor’s thought process is important in understanding the business. In this research, we found that conceptual representations of the rationales of actors provided organizational workers who are domain experts with hidden knowledge about the domain. For example, in creating a conceptual model of retailer and consumer actors, a marketing expert discovered that the objective of the retail actor is not what drives pricing behavior but the actor's reasoning and learning. As another example, when we represented the conceptual model of the actors in a disaster management scenario, senior disaster professionals found that a major resource for them was not technical manuals but everyday sources (e.g., student newspapers and community meetings) that provided information about the “pulse” of the community.
We see a lot of potential in expanding conceptual modeling to support organizational workers. Although these conceptual models might need some intermediate mapping before they can be used for IT development, the organizational worker’s conceptual models should help to evolve requirements needed to develop information systems, which can also open up many avenues for future research.