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Auflistung nach Schlagwort "data management"

1 - 4 von 4
  • Konferenzbeitrag
    Challenges in Data Preservation for AI and ML Systems
    (INFORMATIK 2024, 2024) Tonkin, Emma L.; Tourte, Gregory J. L.
    The management and preservation of machine learning (ML) and artificial intelligence (AI) data is increasingly a concern for research institutions, as well as for institutions and industry organisations making use of this type of data and method. This paper summarises key issues in this area, presenting the case that there are significant benefits to the industry in developing best practices and joint standards in this area, and identifying the benefits of this approach, as well as highlighting risks and a current paucity of best practice in the area.
  • Textdokument
    Discover Barrier-free Accessible Locations with the Location Navigator
    (INFORMATIK 2017, 2017) Abicht, Konrad; Ackermann, Simeon; Martin, Michael
    We present the current version of the Location Navigator, which supports users by finding locations in Leipzig, that can be accessed without barriers. Besides this current version of the prototype we present additionally experiences regarding its engineering process and the previously performed conversion of Open Data provided by the registered association Behindertenverband Leipzig e.V. (BVL). Our vision of the underlying data is an inter-commune data network, in order to support persons with special needs and, furthermore, to apply developments such as the Location Navigator to other municipalities. For this purpose, RDF will be used for the representation and linking of data in the future. Besides the presentation of the Location Navigator, we sketch some approaches we evaluated during the creation of the respective data model.
  • Zeitschriftenartikel
    Fault-tolerant data management in the gaston peer-to-peer file system
    (Wirtschaftsinformatik: Vol. 45, No. 3, 2003) Dynda, Vladimír; Rydlo, Pavel
    Gaston is a peer-to-peer large-scale file system designed to provide a fault-tolerant and highly available file service for a virtually unlimited number of users. Data management in Gaston disseminates and stores replicas of files on multiple machines to achieve the requested level of data availability and uses a dynamic tree-topology structure to connect replication schema members. We present generic algorithms for replication schema creation and maintenance according to file user requirements and autonomous constraints that are set on individual nodes. We also show specific data object structure as well as mechanisms for secure and efficient update propagation among replicas with data consistency control. Finally, we introduce a scalable and efficient technique improving fault-tolerance of the tree-topology structure connecting replicas.
  • Zeitschriftenartikel
    Industrial analytics – An overview
    (it - Information Technology: Vol. 64, No. 1-2, 2022) Gröger, Christian
    The digital transformation generates huge amounts of heterogeneous data across the industrial value chain, from simulation data in engineering, over sensor data in manufacturing to telemetry data on product use. Extracting insights from these data constitutes a critical success factor for industrial enterprises, e. g., to optimize processes and enhance product features. This is referred to as industrial analytics, i. e., data analytics for industrial value creation. Industrial analytics is an interdisciplinary subject area between data science and industrial engineering and is at the core of Industry 4.0. Yet, existing literature on industrial analytics is fragmented and specialized. To address this issue, this paper presents a holistic overview of the field of industrial analytics integrating both current research as well as industry experiences on real-world industrial analytics projects. We define key terms, describe typical use cases and discuss characteristics of industrial analytics. Moreover, we present a conceptual framework for industrial analytics that structures essential elements, e. g., data platforms and data roles. Finally, we conclude and highlight future research directions.