BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology
- Hardisty, A.R.
- Bacall, F.
- Beard, N.
- Balcázar-Vargas, M.P.
- Balech, B.
- Barcza, Z.
- Bourlat, S.J.
- De Giovanni, R.
- de Jong, Y.
- De Leo, F.
- Dobor, L.
- Donvito, G.
- Fellows, D.
- Fernandez Guerra, A.
- Fereira, N.
- Fetyukova, Y.
- Fosso, B.
- Giddy, J.
- Goble, C.
- Güntsch, A.
- Haines, R.
- Hernández Ernst, V.
- Hettling, H.
- Hidy, D.
- Horváth, F.
- Ittzés, D.
- Ittzés, P.
- Jones, A.
- Kottmann, R.
- Kulawik, R.
- Leidenberger, S.
- Lyytikäinen-Saarenmaa, P.
- Mathew, C.
- Morrison, N.
- Nenadic, A.
- Nieva de la Hidalga, A.
- Obst, M.
- Oostermeijer, G.
- Paymal, E.
- Pesole, G.
- Pinto, S.
- Poigné, A.
- Quevedo Fernandez, F.
- Santamaria, M.
- Saarenmaa, H.
- Sipos, G.
- Sylla, K.-H.
- Tähtinen, M.
- Vicario, S.
- Vos, R.A.
- Williams, A.R.
- Yilmaz, P.
DOIAbstract
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 limit...
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