ER 2006 Industrial Presentations

INDUSTRIAL CO-CHAIRS
Arnie Rosenthal (Mitre Corporation, USA, arnie@mitre.org )
Len Seligman (Mitre Corporation, USA, seligman@mitre.org )
 

• The ADO.NET Entity Framework: Making the Conceptual Level Real
  José A. Blakeley, S. Muralidhar, Anil Nori
  Microsoft Corporation

This paper describes the ADO.NET Entity Framework, a platform for programming against data that raises the level of abstraction from the logical (relational) level to the conceptual (entity) level, and thereby significantly reduces the impedance mismatch for applications and data services such as reporting, analysis, and replication. The conceptual data model is made real by a runtime that implements an extended relational model (the Entity Data Model aka the EDM), that embraces entities and relationships as first class concepts; a query language for the EDM; a comprehensive mapping engine that translates from the conceptual to the logical (relational) level, and a set of model-driven tools that help create entity-object, object-xml, and entity-xml transformers.

• XMeta Repository and Services
  Lee Scheffler
  IBM Corporation

The XMeta repository is an emerging industrial-strength model and instance persistence, management, access, query, update, upgrade and mapping facility based on EMF modelling technology. It is actively used as the foundation of several commercial metadata intensive products within IBM as well as several research efforts involving conceptual modeling. This talk covers both the features of XMeta and its services, and some of its current uses. It is expected that a version of XMeta will be made more widely available in some external form in the future.

• IBM Industry Models: Experience, Management and Challenges
  Pat G O’Sullivan, Dan Wolfson
  IBM Enterprise Master Data Management Solutions

IBM's Industry Models for Banking and Insurance continue to evolve to encompass our accumulated experience with our customers, the changing needs of the industry, and the changing directions in technologies. With over 15 years of use, these models represent a wealth of information about the information models, process models and integration models for these industries. The models are in use today by more than 300 leading Banks and Insurance companies, where they serve in a variety of capacities - from supporting Data Consolidation initiatives and Business Process Re-Design to addressing Risk & Compliance issues such as Anti-Money Laundering, Sarbanes-Oxley, or Basel II. 

• Community Semantics For Ultra-Scale Information Management
  Scott Renner
  The MITRE Corporation

The U.S. Department of Defense (DoD) presents an instance of an ultra-scale information management problem: thousands of information systems, millions of users, billions of dollars for procurement and operations. Military organizations are often viewed as the ultimate in rigid hierarchical control. In fact, authority over users and developers is widely distributed, and centralized control is quite difficult – or even impossible, as many of the DoD core functions involve an extended enterprise that includes completely independent entities, such as allied military forces, for-profit corporations, and non-governmental organizations. For this reason, information management within the DoD must take place in an environment of limited autonomy, one in which influence and negotiation are as necessary as top-down direction and control.
This presentation examines the DoD’s information management problems in the context of its transformation to network-centric warfare The key tenent of NCW holds that “seamless” information sharing leads to increased combat power. We examine several implications of the net-centric transformation and show how each depends upon shared semantic understanding within communities of interest. Opportunities for research and for commercial tool development in the area of conceptual modeling will be apparent as we go along.
 

• Policy Models for Data Sharing
  Ken Smith
  The MITRE Corporation

Data sharing has become an enabler of a diverse and important set of activities in areas such as science, law enforcement, and commerce. Data sharing scenarios frequently involve issues such as personal confidentiality, data misinterpretation, the potential for malicious exploitation of shared data, data with proprietary or first-use value, secret data, and governmental regulation. For these reasons, the need to state and enforce data sharing policy has grown increasingly significant. In this talk, we discuss models for data sharing policy and their key concepts.

• Managing Data in High Throughput Laboratories: An Experience Report from Proteomics
  Thodoros Topaloglou
  University of Toronto
  
  Scientific laboratories are rich in data management challenges. This paper describes an end-to-end information management infrastructure for a high throughput proteomics industrial laboratory. A unique feature of the platform is a data and applications integration framework that is employed for the integration of heterogeneous data, applications and processes across the entire laboratory production workflow. We also define a reference architecture for implementing similar solutions organized according to the laboratory data lifecycle phases. Each phase is modeled by a set of workflows integrating programs and databases in sequences of steps and associated communication and data transfers. We discuss the issues associated with each phase, and describe how these issues were approached in the proteomics implementation.