WOVOdat - Data on Volcanic Unrest

News and Announcements

WOVOdat – An online, growing library of worldwide volcanic unrest
C.G. Newhall, F. Costa, A. Ratdomopurbo, D.Y. Venezky, C. Widiwijayanti, Nang Thin Zar Win, K. Tan, E. Fajiculay In Journal of Volcanology and Geothermal Research, Volume 345, 2017, Pages 184-199, ISSN 0377-0273,https://doi.org/10.1016/j.jvolgeores.2017.08.003 http://www.sciencedirect.com/science/article/pii/S0377027317302718


  • WOVOdat is a growing, online database of worldwide volcanic unrest.
  • Users may browse, plot, and download catalogue-level (processed) data.
  • Users may compare unrest through time at single and analogous volcanoes.
  • The value of WOVOdat will depend significantly on its completeness. Please add your data!
  • WOVOdat offers basic apps for data visualization and Boolean searches. Please offer new apps!

Young and research-intensive, Nanyang Technological University (NTU Singapore) is ranked 13th globally. It is also placed 1st among the world's best young universities. The Earth Observatory of Singapore (EOS) at NTU is a national science Research Centre of Excellence. Its mission is to conduct fundamental research on earthquakes, volcanic eruptions, tsunami and climate change in and around Southeast Asia, toward safer and more sustainable societies.

WOVOdat project aims at building a comprehensive global database on volcanic unrest tot understanding pre-eruptive processes and improving eruption forecasts (www.wovodat.org). We invite applications for a Research Fellow as part of the WOVOdat team to develop application tools by which WOVOdat can be used for probabilistic eruption forecasting, such as pattern recognition and event tree analysis.

Duties and responsibilities

  • Closely work with WOVOdat team members on developing WOVOdat project
  • Understanding multi-parameter volcano monitoring data from various data sources, especially data during episode of unrest. And further identifying the evolution of the unrest and eruption precursory pattern
  • Create application tools by which WOVOdat can be used for probabilistic eruption forecasting, such as pattern recognition and event tree analysis. Ensure complete integration with the existing database schema and structure
  • Conduct his/her own research while working effectively with local and international collaborators
  • Publish scientific outcomes in peer-reviewed scientific journals

Job Requirements

  • PhD in Earth Sciences
  • Have experience and familiar in handling volcano monitoring data (spatial and temporal datasets)
  • Understand volcanic processes, volcanic unrest, and eruption
  • Ability to perform statistical analysis such as pattern recognition and Bayesian probability
  • Self-driven, able to work independently but also a good team player
  • Good written and oral communication skills.
  • Working knowledge of foreign languages other than English will be valued.
  • Willingness to occasionally travel to other countries is necessary as well as interactions with a variety of cultures

Please submit your CV along with

  • a one page research interests
  • the copy of at least one paper related to the subject of the project
  • names and contact of 2 referees, with at least one external of your
  • former affiliated university, who would be willing to provide a reference, if necessary.

address to: eos_humanresources@ntu.edu.sg For additional enquiries: fidelcostarodriguez@gmail.com and c.widiwijayanti@gmail.com

WOVOdat organized a one week workshop on "How to Optimize the Use of Volcano Monitoring Database" at Earth Observatory of Singapore - NTU.

Participants: Centre for Volcanological and Geological Hazard Mitigation (CVGHM, Indonesia), Philippine Institute for Volcanology and Seismology (PHIVOLCS, Philippine), Rabaul Volcano Observatory (RVO, Papua New Guinea), and EOS volcano group.


  • Brainstorming and discussion on how WOVOdat system will be used and useful during volcano crisis, for eruption forecasting.
  • Exchange experiences between volcano observatory on using WOVOdat as their monitoring database. PHIVOLCS has been developing data processing automation (SEISAN to WOVOdat, SWARM to WOVOdat, VALVE to WOVOdat), and various operational tools developed in PHIVOLCS and CVGHM localhost.
  • New tools developed by WOVOdat team: installation and operational.
  • Future development and plan of WOVOdat.