Shazia Sadiq – författare

The 11 papers promote and disseminate research on theories of concepts underlying conceptual modeling, methods and tools for developing and communicating conceptual models, techniques for transforming conceptual models into effective implementations, and the impact of conceptual modeling techniques on databases, business strategies and information systems. The following workshops are included in this volume: Second Workshop on Conceptual Modeling for NoSQL Data Stores (CoMoNoS); 4th International Workshop on Empirical Methods in Conceptual Modeling (EmpER); and Second International Workshop on Conceptual Modeling for Life Sciences (CMLS).

The 23 full papers included in this volume were carefully reviewed and selected from a total of 151 submissions to the conference. The papers were organized in research tracks on foundations, engineering, and management. 

This book constitutes the thoroughly refereed post-workshop proceedings of eight international workshops held in Ulm, Germany, in conjunction with the 7th International Conference on Business Process Management, BPM 2009, in September 2009. The eight workshops were on Empirical Research in Business Process Management (ER-BPM 2009), Reference Modeling (RefMod 2009), Business Process Design (BPD 2009), Business Process Intelligence (BPI 2009), Collaborative Business Processes (CBP 2009), Process-Oriented Information Systems in Healthcare (ProHealth 2009), Business Process Management and Social Software (BPMS2 2009), Event-Driven Business Process Management (edBPM 2009). The 67 revised full papers presented were carefully reviewed and selected from numerous submissions.

The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results.

With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects.

Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors.

Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.