Publishing Research Data in NEEShub

By Stanislav Pejša

Network for Earthquake Engineering Simulations (NEES)

Category

Seminars

Published on

Abstract

Earthquake engineering is a highly interdisciplinary research area that brings together researchers from civil, geotechnical, and environmental engineering, as well as researchers from Earth sciences. NEEShub, a collaborative platform that provides a stable data repository and virtual research environment managed the Network for Earthquake Engineering Simulation (NEES), attempts to provide a secure repository not only for data that originate in earthquake engineering research, but for all data that can help mitigate natural disasters.

Such interdisciplinarity and diversity pose unique challenges for data management, data archiving, preservation, and data publication. The proposed presentation will demonstrate approaches to curation, visualization, and publishing of research data in the NEEShub, as well as current curation workflows and services at NEES that help researchers to archive their research data and turn them into citable published datasets that can be reused or interpreted through a variety of analytical and visualization tools.

The presentation will also document ways in which NEEShub exposes the curated datasets and facilitates research collaboration and data sharing, as well as data reuse and repurposing.

Bio

Stanislav Pejša is the Data Curator at the Network for Earthquake Engineering Simulations (NEES) located in Discovery Park at Purdue University. He is primarily responsible for the quality of data uploaded to the NEES data repository. He oversees evolution of data from mere aggregation of sensor measurements to fully curated research projects with metadata and documentation necessary for re-use, long-term access, and preservation. He is also involved in developing workflows and metadata solutions for improving access to and preservation of the research data stored in the repository and delivered through the NEEShub platform. He is interested in exploring new ways of effective sharing and interoperability of research data and issues related to their preservation.

Cite this work

Researchers should cite this work as follows:

  • Stanislav Pejša (2013), "Publishing Research Data in NEEShub," https://help.hubzero.org/resources/1054.

    BibTex | EndNote

Submitter

Nikki Huang

Purdue University

Tags

Publishing Research Data in NEEShub
by: Stanislav Pejša
  • Publication of Research Data in the NEEShub 1. Publication of Research Data i… 0
    00:00/00:00
  • Why Publish Data? 2. Why Publish Data? 37.971304637971308
    00:00/00:00
  • But Also … 3. But Also … 223.2565899232566
    00:00/00:00
  • Because … 4. Because … 257.99132465799136
    00:00/00:00
  • …And Is Doing It 5. …And Is Doing It 294.66132799466135
    00:00/00:00
  • G8 also Wants You to Do It 6. G8 also Wants You to Do It 337.80447113780451
    00:00/00:00
  • DCC Curation Life-Cycle Model 7. DCC Curation Life-Cycle Model 398.33166499833169
    00:00/00:00
  • What Is NEES? 8. What Is NEES? 434.63463463463466
    00:00/00:00
  • Cyberinfrastructure at NEES 9. Cyberinfrastructure at NEES 492.49249249249249
    00:00/00:00
  • NEEShub - www.nees.org 10. NEEShub - www.nees.org 521.75508842175509
    00:00/00:00
  • Data Archiving at NEES 11. Data Archiving at NEES 531.73173173173177
    00:00/00:00
  • What kind of data? 12. What kind of data? 574.44110777444109
    00:00/00:00
  • Data Publication in NEEShub 13. Data Publication in NEEShub 641.4414414414415
    00:00/00:00
  • Citation and Attribution 14. Citation and Attribution 705.17183850517188
    00:00/00:00
  • DOI – Digital Object Identifier 15. DOI – Digital Object Identif… 757.957957957958
    00:00/00:00
  • Exposure of EE Research Data 16. Exposure of EE Research Data 788.2882882882883
    00:00/00:00
  • Repository for EE Data 17. Repository for EE Data 840.27360694027368
    00:00/00:00
  • Visualisation 18. Visualisation 884.25091758425094
    00:00/00:00
  • Curated Experiment 19. Curated Experiment 922.68935602268937
    00:00/00:00
  • Curation Workflow 20. Curation Workflow 994.82816149482824
    00:00/00:00
  • Curation as Quality Assurance 21. Curation as Quality Assurance 1008.5752419085753
    00:00/00:00
  • Understandable data 22. Understandable data 1039.5061728395062
    00:00/00:00
  • Content - Metadata 23. Content - Metadata 1068.7020353687021
    00:00/00:00
  • Access and re-use 24. Access and re-use 1101.2345679012346
    00:00/00:00
  • Curation - Path to SWAMP 25. Curation - Path to SWAMP 1121.0543877210544
    00:00/00:00
  • Thank you. 26. Thank you. 1148.1147814481149
    00:00/00:00
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