Data Provenance Analysis and Description for ETL based on PROV

被引:0
|
作者
Zhang Ran [1 ]
Dai Chao-fan [1 ]
Zeng Sai-hong [1 ]
机构
[1] Natl Univ Sci Technol, Dept Sci & Technol, Informat Syst Engn Lab, Changsha 410074, Hunan, Peoples R China
关键词
PROV ETL; Data provenance; Resource Description;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Data provenance, also calling it data lineage or pedigree, is related information of data about the process from its generation to present situation. W3C workshop proposes PROV standards that rule what vocabularies/ ontologies/rules were used to generate data. It is the uniform standard for data provenance, which strengthens interoperations between different provenance information. ETL, which Extract-Transform-Load abbreviates to, is a description for the change process from data source to end, including extraction, transformation an d loading. In this paper, what we do is to analyze and design a system that can trace data and process correctly and effectively,and we focus on reverse rules and tracing method. As a result, we will do research on data provenance, which will be based on ETL and use PROV standards can make the tracing process better. What's more,we will give an introduction about provenan cc tree that is graphical representation of data tracing process
引用
收藏
页码:1651 / 1656
页数:6
相关论文
共 50 条
  • [1] Research and Application of data provenance based on PROV
    Zhao, Yanpeng
    Dai, Chaofan
    Zhang, Xiaoyu
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING AND INDUSTRIAL INFORMATICS, 2015, 15 : 1551 - 1557
  • [2] Provenance Metadata of Open Government Data Based on PROV-JSON']JSON
    Zhai, Jun
    Chen, Hongyu
    Yuan, Changfeng
    DG.O 2017: THE PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE ON DIGITAL GOVERNMENT RESEARCH: INNOVATIONS AND TRANSFORMATIONS IN GOVERNMENT, 2017, : 594 - 595
  • [3] A Big Data Provenance Model for Data Security Supervision Based on PROV-DM Model
    Gao, Yuanzhao
    Chen, Xingyuan
    Du, Xuehui
    IEEE ACCESS, 2020, 8 : 38742 - 38752
  • [4] Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Data
    Kohwalter, Troy
    Oliveira, Thiago
    Freire, Juliana
    Clua, Esteban
    Murta, Leonardo
    PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, IPAW 2016, 2016, 9672 : 71 - 82
  • [5] Prov-Trust: Towards a Trustworthy SGX-based Data Provenance System
    Kaaniche, Nesrine
    Belguith, Sana
    Laurent, Maryline
    Gehani, Ashish
    Russello, Giovanni
    PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON E-BUSINESS AND TELECOMMUNICATIONS (SECRYPT), VOL 1, 2020, : 225 - 237
  • [6] RE_PROV: Modeling Requirement Provenance with PROV
    He, Yangfan
    Li, Xiaojian
    2016 23RD ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2016), 2016, : 397 - 400
  • [7] A PROV Encoding for Provenance Analysis Using Deductive Rules
    Missier, Paolo
    Belhajjame, Khalid
    PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, IPAW 2012, 2012, 7525 : 67 - 81
  • [8] A PROV-O Based Approach to Web Content Provenance
    Jing, Ni
    2015 INTERNATIONAL CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCES (LISS), 2015,
  • [9] Prov-Dominoes: An approach for knowledge discovery from provenance data
    Alencar, Victor
    Kohwalter, Troy
    Braganholo, Vanessa
    Da Silva Junior, Jose Ricardo
    Murta, Leonardo
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 245
  • [10] Extending PROV Data Model for Provenance-Aware Sensor Web
    Yue, Peng
    Guo, Xia
    Zhang, Mingda
    Jiang, Liangcun
    PROVENANCE AND ANNOTATION OF DATA AND PROCESSES (IPAW 2014), 2015, 8628 : 281 - 284