A data model-independent approach to big research data integration

被引：0
|
作者：
Bartalesi V. [1 ]
Meghini C. [1 ]
Thanos C. [1 ]
机构：
[1] Istituto di Scienza e Tecnologie dell’Informazione, “Alessandro Faedo” (ISTI) – CNR, Via G. Moruzzi 1, Pisa
来源：
International Journal of Metadata, Semantics and Ontologies | 2019年 / 13卷 / 04期
关键词：
Big research data; Data integration; Ontology; Semantic web;
D O I：
10.1504/IJMSO.2019.102680
中图分类号：
学科分类号：
摘要：
The paper addresses the data integration problem in the context of the scientific domain. The main characteristics of the big research data that make the traditional approach of data integration unfeasible are presented. Two new emerging practices, i.e. an exploratory approach to data seeking and an empiricist epistemological approach to knowledge creation, are discussed. Based on these considerations, we present a new paradigm of data integration and an application ontology that supports it. The ontology is based on five types of events and every event is extensionally modelled as an input/output operation on the involved data entity. The strong point of the ontology and of the whole approach to data integration is that no assumption is made on the data models in which the databases or the views are expressed. This provides a level of generality that successfully deals with the heterogeneity of the domain. Copyright © 2019 Inderscience Enterprises Ltd.
引用
收藏
页码：330 / 345
页数：15
相关论文
共 50 条
  • [1] Model-independent schema and data translation
    Atzeni, Paolo
    Cappellari, Paolo
    Bernstein, Philip A.
    [J]. ADVANCES IN DATABASE TECHNOLOGY - EDBT 2006, 2006, 3896 : 368 - 385
  • [2] Model-independent representation of electroweak data
    Stuart, R. G.
    [J]. Physical Review D Particles, Fields, Gravitation and Cosmology, 56 (03):
  • [3] Model-independent representation of electroweak data
    Stuart, RG
    [J]. PHYSICAL REVIEW D, 1997, 56 (03): : 1515 - 1521
  • [4] MODEL-INDEPENDENT METHOD OF DATA-ANALYSIS
    COOK, BC
    WEBER, TA
    [J]. NUOVO CIMENTO DELLA SOCIETA ITALIANA DI FISICA B-GENERAL PHYSICS RELATIVITY ASTRONOMY AND MATHEMATICAL PHYSICS AND METHODS, 1986, 94 (02): : 175 - 192
  • [5] TOWARD A MODEL-INDEPENDENT ANALYSIS OF ELECTROWEAK DATA
    ALTARELLI, G
    BARBIERI, R
    JADACH, S
    [J]. NUCLEAR PHYSICS B, 1992, 369 (1-2) : 3 - 32
  • [6] Automated Data Slicing for Model Validation: A Big Data - AI Integration Approach
    Chung, Yeounoh
    Kraska, Tim
    Polyzotis, Neoklis
    Tae, Ki Hyun
    Whang, Steven Euijong
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2020, 32 (12) : 2284 - 2296
  • [7] Model-independent approach to η → π+π-γ and η′ → π+π-γ
    Stollenwerk, F.
    Hanhart, C.
    Kupsc, A.
    Meissner, U. -G.
    Wirzba, A.
    [J]. PHYSICS LETTERS B, 2012, 707 (01) : 184 - 190
  • [8] Towards a model-independent reconstruction approach for late-time Hubble data
    Bernardo, Reginald Christian
    Said, Jackson Levi
    [J]. JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS, 2021, (08):
  • [9] Cosmological parameter estimation from SN Ia data: a model-independent approach
    Benitez-Herrera, S.
    Ishida, E. E. O.
    Maturi, M.
    Hillebrandt, W.
    Bartelmann, M.
    Roepke, F.
    [J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2013, 436 (01) : 854 - 858
  • [10] Does big data mean big knowledge? Integration of big data analysis and conceptual model for social commerce research
    Tian, Xuemei
    Liu, Libo
    [J]. ELECTRONIC COMMERCE RESEARCH, 2017, 17 (01) : 169 - 183
12345