Tracking provenance of earth science data

被引:15
|
作者
Tilmes, Curt [1 ]
Yesha, Yelena [2 ]
Halem, Milton [2 ]
机构
[1] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[2] Univ Maryland, Baltimore, MD 21250 USA
基金
美国国家科学基金会;
关键词
Data processing; Provenance;
D O I
10.1007/s12145-010-0046-3
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Tremendous volumes of data have been captured, archived and analyzed. Sensors, algorithms and processing systems for transforming and analyzing the data are evolving over time. Web Portals and Services can create transient data sets on-demand. Data are transferred from organization to organization with additional transformations at every stage. Provenance in this context refers to the source of data and a record of the process that led to its current state. It encompasses the documentation of a variety of artifacts related to particular data. Provenance is important for understanding and using scientific datasets, and critical for independent confirmation of scientific results. Managing provenance throughout scientific data processing has gained interest lately and there are a variety of approaches. Large scale scientific datasets consisting of thousands to millions of individual data files and processes offer particular challenges. This paper uses the analogy of art history provenance to explore some of the concerns of applying provenance tracking to earth science data. It also illustrates some of the provenance issues with examples drawn from the Ozone Monitoring Instrument (OMI) Data Processing System (OMIDAPS) (Tilmes et al. 2004) run at NASA's Goddard Space Flight Center by the first author.
引用
收藏
页码:59 / 65
页数:7
相关论文
共 50 条
  • [31] Announcement FAIR data in Earth science
    不详
    NATURE, 2019, 565 (7738) : 134 - 134
  • [32] Data Management for Earth System Science
    Frew, James
    Dozier, Jeff
    SIGMOD Record (ACM Special Interest Group on Management of Data), 1997, 26 (01): : 27 - 31
  • [33] Overcoming Data Scarcity in Earth Science
    Gorgoglione, Angela
    Castro, Alberto
    Chreties, Christian
    Etcheverry, Lorena
    DATA, 2020, 5 (01)
  • [34] Strategizing Earth Science Data Development
    Liu, Zhong
    Yao, Tian
    SCIENTIFIC DATA, 2024, 11 (01)
  • [35] Recent Activities in Earth Data Science
    Yue, Peng
    Ramachandran, Rahul
    Baumann, Peter
    Khalsa, Siri Jodha S.
    Deng, Meixia
    Jiang, Liangcun
    IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2016, 4 (04): : 84 - 89
  • [36] Data Observation Network for Earth: Earth and environmental science data management and discovery
    Budden, Amber
    Michener, William
    Vieglais, Dave
    Koskela, Rebecca
    Soyka, Heather
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2016, 251
  • [37] Improving Data Quality, Privacy and Provenance in Citizen Science Applications
    Musto, Jiri
    Dahanayake, Ajantha
    INFORMATION MODELLING AND KNOWLEDGE BASES XXXI, 2020, 321 : 141 - 160
  • [38] Provenance Tracking in R
    Runnalls, Andrew
    Silles, Chris
    PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, IPAW 2012, 2012, 7525 : 237 - 239
  • [39] Data Science Landscape: Tracking the Ecosystem
    Munshi, Usha Mujoo
    DATA SCIENCE LANDSCAPE: TOWARDS RESEARCH STANDARDS AND PROTOCOLS, 2018, 38 : 1 - 31
  • [40] Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering
    Souza, Renan
    Azevedo, Leonardo
    Lourenco, Vitor
    Soares, Elton
    Thiago, Raphael
    Brandao, Rafael
    Civitarese, Daniel
    Brazil, Emilio Vital
    Moreno, Marcio
    Valduriez, Patrick
    Mattoso, Marta
    Cerqueira, Renato
    Netto, Marco A. S.
    PROCEEDINGS OF WORKS19: THE 2019 14TH IEEE/ACM WORKFLOWS IN SUPPORT OF LARGE-SCALE SCIENCE (WORKS), 2019, : 1 - 10