Topic
Data management
About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.
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TL;DR: This work will outline the framework approach of data management, discuss its relative merits and provide a working example of its application to data management and analysis.
Abstract: Qualitative methods are invaluable for exploring the complexities of health care and patient experiences in particular. Diverse qualitative methods are available that incorporate different ontological and epistemological perspectives. One method of data management that is gaining in popularity among healthcare researchers is the framework approach. We will outline this approach, discuss its relative merits and provide a working example of its application to data management and analysis.
1,008 citations
TL;DR: This comprehensive reference contains 1,300 illustrated entries, organized alphabetically, providing easy access to important concepts relevant information on all aspects of very large databases, data management, and database systems, including areas of current interest and research results of historical significance.
Abstract: Data have become a highly valued asset for governments, industries and individuals, and the management of these data collections remains a critical technical challenge.. The challenges of managing terabytes and exabytes of data and expanding data management to include other data modalities while maintaining the fundamental tenets of database management (data independence, data integrity, data consistency, etc) are important issues for any organization today. Published as five volumes with over 4000 pages, the Encyclopedia of Database Systems provides easy access to important concepts relevant information on all aspects of very large databases, data management, and database systems, including areas of current interest and research results of historical significance.. This comprehensive reference contains 1,300 illustrated entries, organized alphabetically. Each entry presents basic terminology, concepts, methods and algorithms, key results to date, references to the literature, and cross-references to other entries. Topics for the Encyclopedia including areas of current interest as well as research results of historical significance were selected by a distinguished international advisory board and written by world class experts in the field. Encyclopedia of Database Systems is designed to meet the needs of researchers, professors, graduate and undergraduate students in computer science and engineering. Industry professionals such as database specialists and software developers will also benefit from this reference work.
991 citations
20 Aug 2002
TL;DR: This paper presents Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. and describes the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real-time operation.
Abstract: This paper introduces monitoring applications, which we will show differ substantially from conventional business data processing. The fact that a software system must process and react to continual inputs from many sources (e.g., sensors) rather than from human operators requires one to rethink the fundamental architecture of a DBMS for this application area. In this paper, we present Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. We describe the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real-time operation.
963 citations
Patent•
14 May 1999
TL;DR: In this article, a first set of computer data is acquired that represents a model of an organization of people having fundamental components, such as processes or capabilities, that are represented in the computer data by data items.
Abstract: Management information is processed. A first set of computer data is acquired that represents a model of an organization of people having fundamental components, such as processes or capabilities, that are represented in the first set of computer data by data items. The first set of computer data is associated with a second set of computer data that represents a portfolio of management concepts, such as management goals. A report of management concepts is issued based on the second set of computer data and is sorted by fundamental component.
894 citations
TL;DR: The purpose of this TDQM methodology is to deliver highquality information products (IP) to information consumers and aims to facilitate the implementation of an organization’s overall data quality policy formally expressed by top management.
Abstract: The field of information quality (IQ) has experienced significant advances during its relatively brief history. Today, researchers and practitioners alike have moved beyond establishing information quality as an important field to resolving IQ problems—problems ranging from IQ definition, measurement, analysis, and improvement to tools, methods, and processes. However, theoretically-grounded methodologies for Total Data Quality Management (TDQM) are still lacking. Based on cumulated research efforts, this article presents such a methodology for addressing these problems. The purpose of this TDQM methodology is to deliver highquality information products (IP) to information consumers. It aims to facilitate the implementation of an organization’s overall data quality policy formally expressed by top management [10]. Richard Y. Wang
886 citations