Topic
Data management
About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.
Papers published on a yearly basis
Papers
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01 Nov 1999TL;DR: It is found that KBS can be developed and employed for effective knowledge management support and its field application, as part of a major reengineering engagement, reveals four important knowledge effects enabled by this KBS.
Abstract: A fundamental problem with knowledge management is the information technology (IT) employed to enable knowledge work appears to target data and information, as opposed to knowledge itself. In contrast, knowledge-based systems (KBS) maintain an explicit and direct focus on knowledge. The research described in this article is focused on innovating knowledge management through KBS technology. We refer to this KBS-enabled transformation of knowledge work as knowledge-based knowledge management. Drawing from the recent literature, we identify a number of key activities associated with knowledge management to establish a set of requirements for knowledge management support. We match these requirements with textbook capabilities of intelligent systems and use this analysis to evaluate KOPeR, a KBS employed to automate and support knowledge management in the reengineering domain. We find KOPeR possesses the capabilities required for knowledge management support. And its field application, as part of a major reengineering engagement, reveals four important knowledge effects enabled by this KBS. From this study, we also find KOPeR to be effective in its automation and support of key knowledge management activities. And through its successful use and knowledge effects in this study, we conclude that KBS can be developed and employed for effective knowledge management support.
78 citations
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01 Jun 2014TL;DR: The AsterixDB software framework enables "LSM-ification" (conversion from an in-place update, disk-based data structure to a deferred-update, append-only data structure) of any kind of index structure that supports certain primitive operations, enabling the index to ingest data efficiently.
Abstract: Social networks, online communities, mobile devices, and instant messaging applications generate complex, unstructured data at a high rate, resulting in large volumes of data. This poses new challenges for data management systems that aim to ingest, store, index, and analyze such data efficiently. In response, we released the first public version of AsterixDB, an open-source Big Data Management System (BDMS), in June of 2013. This paper describes the storage management layer of AsterixDB, providing a detailed description of its ingestion-oriented approach to local storage and a set of initial measurements of its ingestion-related performance characteristics.In order to support high frequency insertions, AsterixDB has wholly adopted Log-Structured Merge-trees as the storage technology for all of its index structures. We describe how the AsterixDB software framework enables "LSM-ification" (conversion from an in-place update, disk-based data structure to a deferred-update, append-only data structure) of any kind of index structure that supports certain primitive operations, enabling the index to ingest data efficiently. We also describe how AsterixDB ensures the ACID properties for operations involving multiple heterogeneous LSM-based indexes. Lastly, we highlight the challenges related to managing the resources of a system when many LSM indexes are used concurrently and present AsterixDB's initial solution.
78 citations
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TL;DR: The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms, and targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis.
Abstract: Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.
78 citations
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30 Nov 2010TL;DR: This paper addresses this challenging open issue by defining and enforcing access policies based on data attributes and implementing user accountability by using traitor tracing, and shows that the proposed scheme is highly efficient and provably secure under existing security models.
Abstract: Cloud computing is an emerging computing paradigm in which IT resources and capacities are provided as services over the Internet. Promising as it is, this paradigm also brings forth new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are likely outside of the same trust domain of data owners. To maintain the confidentiality of, sensitive user data against untrusted servers, existing work usually apply cryptographic methods by disclosing data decryption keys only to authorized users. However, in doing so, these solutions inevitably introduce heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. In this paper, we present a way to implement, scalable and fine-grained access control systems based on attribute-based encryption (ABE). For the purpose of secure access control in cloud computing, the prevention of illegal key sharing among colluding users is missing from the existing access control systems based on ABE. This paper addresses this challenging open issue by defining and enforcing access policies based on data attributes and implementing user accountability by using traitor tracing. Furthermore, both the user grant and revocation are efficiently supported by using the broadcast encryption technique. Extensive analysis shows that the proposed scheme is highly efficient and provably secure under existing security models.
78 citations
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01 Jan 2001
TL;DR: This book provides a practical tutorial with compelling case studies on how to address the information avalanche the authors all face and is an essential read for any government manager with enterprise-wide information systems responsibilities.
Abstract: V DrChenFF.rs9/7for pdf-italic 11/20/01 8:28 AM Page 1 DrChenFF.rs9/7for pdf-italic 11/20/01 8:28 AM Page 2 " A concise and insightful text by one of the acknowledged leaders in the field. As evidenced by the case studies included here, Professor Chen's research program contributes to numerous application areas and promises to continue to do so. " " Hsinchun Chen for many years has lead the world in applying new information technologies to large complex information management problems encountered in all large enterprises. This book provides a practical tutorial with compelling case studies on how to address the information avalanche we all face. " " Knowledge management is crucial to the success of enterprises of varying sizes. This book gives an excellent explanation and illustration of how some of these new knowledge management techniques and concepts can be leveraged in modern organizations. Its potential for medical informatics and digital government applications, in particular, is tremendous. " " The projects and case studies described in this book are very insightful and useful. I would strongly urge IT researchers and practitioners to look closely into these new techniques and their potential applications in various private enterprises and governments. " " Text mining is an increasingly important topic in knowledge management especially after the September 11, 2001 tragedy in the United States. Hsinchun Chen provides us with a delightful set of introductory materials on this topic and how to apply them in the real world. The book comes with a wealth of references, making it easier for novices to find additional in-depth materials. " DrChenFF.rs9/7for pdf-italic 11/20/01 8:28 AM Page a " Dr. Chen's book is an essential read for any government manager with enterprise-wide information systems responsibilities. As perhaps the world's largest business, the Federal government is badly in need of KM capabilities, and far behind the best practices of the private sector. The book focuses appropriately on the bi-modal nature of knowledge management; i.e. it requires fresh and cutting-edge thinking in both the technical underpinnings and in organization design, process and culture. Neither is sufficient without the other. " Larry Brandt Program Manager, Digital Government program Experimental and Integrative Activities National Science Foundation " As a knowledge management practitioner, I am often deluged with vendor hype regarding the latest " fads " in KM technology. Each vendor promises to provide the " complete solution to all your corporate KM needs " , leading …
78 citations