Shazia Sadiq – författare

This book constitutes the proceedings of the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, which was held online during June 28-July 2, 2021. The papers included in these proceedings focus on intelligent information systems and deal with novel approaches to IS engineering;

This book constitutes the refereed proceedings of three workshops symposia, held at the 40th International Conference on Conceptual Modeling, ER 2021, which were held virtually and in St. John’s, NL, Canada, in October 2021.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).

This book constitutes the refereed proceedings of the 21st International Conference on Business Process Management, BPM 2023, which took place in Utrecht, The Netherlands, in September 2023. The 27 papers included in this book were carefully reviewed and selected from 151 submissions. They were organized in three main research tracks: Foundations, engineering, and management.

This book constitutes the proceedings of the BPM Forum held at the 21st International Conference on Business Process Management, BPM 2023, which took place in Utrecht, The Netherlands, in September 2023.

This book constitutes the proceedings of the 44th International Conference on Conceptual Modeling, ER 2025, which took place in Poitiers, France, during October 20–23, 2025.The 22 full papers included in this book were carefully reviewed and selected from 106 submissions. The ER conference is providing a forum for the presentation, discussion, and debate of innovative and emerging ideas, concepts, and methods. They create an environment that encourages experimentation, interdisciplinary exchange, and the exploration ofnew research frontiers.

This book constitutes the proceedings of the 12th International Conference on Business Process Management, BPM 2014, held in Haifa, Israel, in September 2014. The 21 regular papers and 10 short papers included in this volume were carefully reviewed and selected from 123 submissions. The papers are organized in 9 topical sections on declarative processes, user-centered process approaches, process discovery, integrative BPM, resource and time management in BPM, process analytics, process enabled environments, discovery and monitoring, and industry papers.

This two-volume set LNCS 10827 and LNCS 10828 constitutes the refereed proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018.The 83 full papers, 21 short papers, 6 industry papers, and 8 demo papers were carefully selected from a total of 360 submissions. The papers are organized around the following topics: network embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming data; RDF and knowledge graphs; text and data mining; medical data mining; security and privacy; search and information retrieval; query processing and optimizations; data quality and crowdsourcing; learning models; multimedia data processing; and distributed computing.

This two-volume set LNCS 10827 and LNCS 10828 constitutes the refereed proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018.The 83 full papers, 21 short papers, 6 industry papers, and 8 demo papers were carefully selected from a total of 360 submissions. The papers are organized around the following topics: network embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming data; RDF and knowledge graphs; text and data mining; medical data mining; security and privacy; search and information retrieval; query processing and optimizations; data quality and crowdsourcing; learning models; multimedia data processing; and distributed computing.

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.

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.