The Experts below are selected from a list of 6 Experts worldwide ranked by ideXlab platform

Manalo, Brigida Aureus - One of the best experts on this subject based on the ideXlab platform.

  • A User-Oriented Conceptual Schema Model of A Data Base With A Supporting Design Strategy
    1
    Co-Authors: Manalo, Brigida Aureus
    Abstract:

    171 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1983.The Data Model to generate the Conceptual schema should make it easier for users to understand and to express the information in the Data base, but this consideration is most often ignored by the conventional Data Models currently in use today. Understandability and expressiveness of a Data base are achieved if the Data Model meets each of the following criteria: (1) it is structured to reflect information content only, not considerations of physical storage or access strategy; (2) it is able to reflect information content as closely as possible to natural or real world relationships; (3) it maintains clarity and consistency in the set of constructs it uses; (4) it can reflect as wide a set of Data relationships as is possible.This thesis presents a Conceptual Data Model that was developed with these criteria in mind. A design methodology that demonstrates the use of the Model in generating a schema is also presented.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Zimányi Esteba - One of the best experts on this subject based on the ideXlab platform.

  • Enabling instant- and interval-based semantics in multidimensional Data Models: the T+MultiDim Model
    2020
    Co-Authors: Combi Carlo, Oliboni Arbara, Pozzi Giuseppe, Sabaini Alberto, Zimányi Esteba
    Abstract:

    Time is a vital facet of every human activity. Data warehouses, which are huge repositories of historical information, must provide analysts with rich mechanisms for managing the temporal aspects of information. In this paper, we (i) propose T+MultiDim, a multidimensional Conceptual Data Model enabling both instant- and interval-based semantics over temporal dimensions, and (ii) provide suitable OLAP (On-Line Analytical Processing) operators for querying temporal information. T+MultiDim allows one to design typical concepts of a Data warehouse including temporal dimensions, and provides one with the new possibility of Conceptually connecting different temporal dimensions for exploiting temporally aggregated Data. The proposed approach allows one to specify and to evaluate powerful OLAP queries over information from Data warehouses. In particular, we define a set of OLAP operators to deal with interval-based temporal Data. Such operators allow the user to derive new measure values associated to different intervals/instants, according to different temporal semantics. Moreover, we propose and discuss through examples from the healthcare domain the SQL specification of all the temporal OLAP operators we define. (C) 2019 Elsevier Inc. All rights reserved

Combi Carlo - One of the best experts on this subject based on the ideXlab platform.

  • Enabling instant- and interval-based semantics in multidimensional Data Models: the T+MultiDim Model
    2020
    Co-Authors: Combi Carlo, Oliboni Arbara, Pozzi Giuseppe, Sabaini Alberto, Zimányi Esteba
    Abstract:

    Time is a vital facet of every human activity. Data warehouses, which are huge repositories of historical information, must provide analysts with rich mechanisms for managing the temporal aspects of information. In this paper, we (i) propose T+MultiDim, a multidimensional Conceptual Data Model enabling both instant- and interval-based semantics over temporal dimensions, and (ii) provide suitable OLAP (On-Line Analytical Processing) operators for querying temporal information. T+MultiDim allows one to design typical concepts of a Data warehouse including temporal dimensions, and provides one with the new possibility of Conceptually connecting different temporal dimensions for exploiting temporally aggregated Data. The proposed approach allows one to specify and to evaluate powerful OLAP queries over information from Data warehouses. In particular, we define a set of OLAP operators to deal with interval-based temporal Data. Such operators allow the user to derive new measure values associated to different intervals/instants, according to different temporal semantics. Moreover, we propose and discuss through examples from the healthcare domain the SQL specification of all the temporal OLAP operators we define. (C) 2019 Elsevier Inc. All rights reserved

Oliboni Arbara - One of the best experts on this subject based on the ideXlab platform.

  • Enabling instant- and interval-based semantics in multidimensional Data Models: the T+MultiDim Model
    2020
    Co-Authors: Combi Carlo, Oliboni Arbara, Pozzi Giuseppe, Sabaini Alberto, Zimányi Esteba
    Abstract:

    Time is a vital facet of every human activity. Data warehouses, which are huge repositories of historical information, must provide analysts with rich mechanisms for managing the temporal aspects of information. In this paper, we (i) propose T+MultiDim, a multidimensional Conceptual Data Model enabling both instant- and interval-based semantics over temporal dimensions, and (ii) provide suitable OLAP (On-Line Analytical Processing) operators for querying temporal information. T+MultiDim allows one to design typical concepts of a Data warehouse including temporal dimensions, and provides one with the new possibility of Conceptually connecting different temporal dimensions for exploiting temporally aggregated Data. The proposed approach allows one to specify and to evaluate powerful OLAP queries over information from Data warehouses. In particular, we define a set of OLAP operators to deal with interval-based temporal Data. Such operators allow the user to derive new measure values associated to different intervals/instants, according to different temporal semantics. Moreover, we propose and discuss through examples from the healthcare domain the SQL specification of all the temporal OLAP operators we define. (C) 2019 Elsevier Inc. All rights reserved

Pozzi Giuseppe - One of the best experts on this subject based on the ideXlab platform.

  • Enabling instant- and interval-based semantics in multidimensional Data Models: the T+MultiDim Model
    2020
    Co-Authors: Combi Carlo, Oliboni Arbara, Pozzi Giuseppe, Sabaini Alberto, Zimányi Esteba
    Abstract:

    Time is a vital facet of every human activity. Data warehouses, which are huge repositories of historical information, must provide analysts with rich mechanisms for managing the temporal aspects of information. In this paper, we (i) propose T+MultiDim, a multidimensional Conceptual Data Model enabling both instant- and interval-based semantics over temporal dimensions, and (ii) provide suitable OLAP (On-Line Analytical Processing) operators for querying temporal information. T+MultiDim allows one to design typical concepts of a Data warehouse including temporal dimensions, and provides one with the new possibility of Conceptually connecting different temporal dimensions for exploiting temporally aggregated Data. The proposed approach allows one to specify and to evaluate powerful OLAP queries over information from Data warehouses. In particular, we define a set of OLAP operators to deal with interval-based temporal Data. Such operators allow the user to derive new measure values associated to different intervals/instants, according to different temporal semantics. Moreover, we propose and discuss through examples from the healthcare domain the SQL specification of all the temporal OLAP operators we define. (C) 2019 Elsevier Inc. All rights reserved