Using Ontologies for Official Statistics: The Istat Experience

被引:2
|
作者
Aracri, Raffaella M. [1 ]
Radini, Roberta [1 ]
Scannapieco, Monica [1 ]
Tosco, Laura [1 ]
机构
[1] Istat Italian Natl Inst Stat, Rome, Italy
关键词
OBDM; OBDA; LOD; Ontology-driven data integration Linked Data;
D O I
10.1007/978-3-319-74433-9_15
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we illustrate some experiences by the Italian National Institute of Statistics (Istat) on using ontologies for the purpose of both data integration and data dissemination. The shown data integration project is based on the Ontology Based Data Management (OBDM) paradigm, proposed for integrating multiple and heterogeneous data sources. The dissemination experience exploits the Linked Data paradigm and led to the publication of the Istat's Linked Open Data portal.
引用
收藏
页码:166 / 172
页数:7
相关论文
共 50 条
  • [21] Uncertainty in official statistics
    Humpherson, Ed
    JOURNAL OF RISK RESEARCH, 2024,
  • [22] Improvement of official statistics
    不详
    LANCET, 1908, 2 : 36 - 36
  • [23] BRITISH OFFICIAL STATISTICS
    不详
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-GENERAL, 1968, 131 : 1 - &
  • [24] Official cancer statistics
    不详
    JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1930, 94 : 1616 - 1616
  • [25] Outliers in official statistics
    Wada, Kazumi
    JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE, 2020, 3 (02) : 669 - 691
  • [26] Ontologies and tag-statistics
    Tibely, Gergely
    Pollner, Peter
    Vicsek, Tamas
    Palla, Gergely
    NEW JOURNAL OF PHYSICS, 2012, 14
  • [27] Integrating statistical data with the semantic web: The ISTAT experience
    Aracri, Raffaella Maria
    De Francisci, Stefano
    Pagano, Andrea
    Scannapieco, Monica
    Tosco, Laura
    Valentino, Luca
    Mondo Digitale, 2014, 13 (49):
  • [28] Official Statistics and Statistics Education: Bridging the Gap
    Gal, Iddo
    Ograjensek, Irena
    JOURNAL OF OFFICIAL STATISTICS, 2017, 33 (01) : 79 - 100
  • [29] Using huge amounts of road sensor data for official statistics
    Puts, Marco J. H.
    Daas, Piet J. H.
    Tennekes, Martijn
    de Blois, Chris
    AIMS MATHEMATICS, 2019, 4 (01): : 12 - 25
  • [30] An Evolutionary Schema for Using "it-is-what-it-is" Data in Official Statistics
    Lothian, Jack
    Holmberg, Anders
    Seyb, Allyson
    JOURNAL OF OFFICIAL STATISTICS, 2019, 35 (01) : 137 - 165