BioVeL: A virtual laboratory for data analysis and modelling in biodiversity science and ecology

Research output: Contribution to journalArticlepeer-review

  • External authors:
  • Alex R. Hardisty
  • Niall Beard
  • Maria Paula Balcázar-Vargas
  • Bachir Balech
  • Zoltán Barcza
  • Sarah J. Bourlat
  • Renato Giovanni
  • Yde Jong
  • Francesca Leo
  • Laura Dobor
  • Giacinto Donvito
  • Donal Fellows
  • Antonio Fernandez Guerra
  • Nuno Ferreira
  • Yuliya Fetyukova
  • Bruno Fosso
  • Jonathan Giddy
  • Anton Güntsch
  • Vera Hernández Ernst
  • Hannes Hettling
  • Dóra Hidy
  • Ferenc Horváth
  • Dóra Ittzés
  • Péter Ittzés
  • Andrew Jones
  • Renzo Kottmann
  • Robert Kulawik
  • Sonja Leidenberger
  • Päivi Lyytikäinen-Saarenmaa
  • Cherian Mathew
  • Norman Morrison
  • Aleksandra Nenadic
  • Abraham Nieva Hidalga
  • Matthias Obst
  • Gerard Oostermeijer
  • Elisabeth Paymal
  • Graziano Pesole
  • Salvatore Pinto
  • Axel Poigné
  • Francisco Quevedo Fernandez
  • Monica Santamaria
  • Hannu Saarenmaa
  • Gergely Sipos
  • Karl Heinz Sylla
  • Marko Tähtinen
  • Saverio Vicario
  • Rutger Aldo Vos
  • Pelin Yilmaz

Abstract

Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.

Bibliographical metadata

Original languageEnglish
Article number49
JournalEcology
Volume16
Issue number1
DOIs
Publication statusPublished - 20 Oct 2016

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