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

Alex R. Hardisty; Finn Bacall; 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; Carole Goble; Anton Güntsch; Robert Haines; 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; Alan Williams; Pelin Yilmaz

doi:10.1186/s12898-016-0103-y

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

Alex R. Hardisty^*, Finn Bacall, 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, Carole Goble, Anton GüntschRobert Haines, 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, Alan Williams, Pelin Yilmaz

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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.

Original language	English
Article number	49
Journal	Ecology
Volume	16
Issue number	1
DOIs	https://doi.org/10.1186/s12898-016-0103-y
Publication status	Published - 20 Oct 2016

Keywords

Analysis
Automation
Biodiversity science
Biodiversity virtual e-laboratory
Computing software
Data processing
Ecology
Informatics
Virtual laboratory
Workflows

Research Beacons, Institutes and Platforms

Manchester Institute of Biotechnology

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10.1186/s12898-016-0103-yLicence: CC BY

Cite this

Hardisty, A. R., Bacall, F., Beard, N., Balcázar-Vargas, M. P., Balech, B., Barcza, Z., Bourlat, S. J., Giovanni, R., Jong, Y., Leo, F., Dobor, L., Donvito, G., Fellows, D., Guerra, A. F., Ferreira, N., Fetyukova, Y., Fosso, B., Giddy, J., Goble, C., ... Yilmaz, P. (2016). BioVeL: A virtual laboratory for data analysis and modelling in biodiversity science and ecology. Ecology, 16(1), Article 49. https://doi.org/10.1186/s12898-016-0103-y

@article{13800686d9264f57a04d366776e43a33,

title = "BioVeL: A virtual laboratory for data analysis and modelling in biodiversity science and ecology",

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.",

keywords = "Analysis, Automation, Biodiversity science, Biodiversity virtual e-laboratory, Computing software, Data processing, Ecology, Informatics, Virtual laboratory, Workflows",

author = "Hardisty, {Alex R.} and Finn Bacall and Niall Beard and Balc{\'a}zar-Vargas, {Maria Paula} and Bachir Balech and Zolt{\'a}n Barcza and Bourlat, {Sarah J.} and Renato Giovanni and Yde Jong and Francesca Leo and Laura Dobor and Giacinto Donvito and Donal Fellows and Guerra, {Antonio Fernandez} and Nuno Ferreira and Yuliya Fetyukova and Bruno Fosso and Jonathan Giddy and Carole Goble and Anton G{\"u}ntsch and Robert Haines and Ernst, {Vera Hern{\'a}ndez} and Hannes Hettling and D{\'o}ra Hidy and Ferenc Horv{\'a}th and D{\'o}ra Ittz{\'e}s and P{\'e}ter Ittz{\'e}s and Andrew Jones and Renzo Kottmann and Robert Kulawik and Sonja Leidenberger and P{\"a}ivi Lyytik{\"a}inen-Saarenmaa and Cherian Mathew and Norman Morrison and Aleksandra Nenadic and Hidalga, {Abraham Nieva} and Matthias Obst and Gerard Oostermeijer and Elisabeth Paymal and Graziano Pesole and Salvatore Pinto and Axel Poign{\'e} and Fernandez, {Francisco Quevedo} and Monica Santamaria and Hannu Saarenmaa and Gergely Sipos and Sylla, {Karl Heinz} and Marko T{\"a}htinen and Saverio Vicario and Vos, {Rutger Aldo} and Alan Williams and Pelin Yilmaz",

year = "2016",

month = oct,

day = "20",

doi = "10.1186/s12898-016-0103-y",

language = "English",

volume = "16",

journal = "Ecology",

issn = "0012-9658",

publisher = "John Wiley & Sons Ltd",

number = "1",

}

Hardisty, AR, Bacall, F, Beard, N, Balcázar-Vargas, MP, Balech, B, Barcza, Z, Bourlat, SJ, Giovanni, R, Jong, Y, Leo, F, Dobor, L, Donvito, G, Fellows, D, Guerra, AF, Ferreira, N, Fetyukova, Y, Fosso, B, Giddy, J, Goble, C, Güntsch, A, Haines, R, Ernst, VH, 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, Hidalga, AN, Obst, M, Oostermeijer, G, Paymal, E, Pesole, G, Pinto, S, Poigné, A, Fernandez, FQ, Santamaria, M, Saarenmaa, H, Sipos, G, Sylla, KH, Tähtinen, M, Vicario, S, Vos, RA, Williams, A & Yilmaz, P 2016, 'BioVeL: A virtual laboratory for data analysis and modelling in biodiversity science and ecology', Ecology, vol. 16, no. 1, 49. https://doi.org/10.1186/s12898-016-0103-y

TY - JOUR

T1 - BioVeL

T2 - A virtual laboratory for data analysis and modelling in biodiversity science and ecology

AU - Hardisty, Alex R.

AU - Bacall, Finn

AU - Beard, Niall

AU - Balcázar-Vargas, Maria Paula

AU - Balech, Bachir

AU - Barcza, Zoltán

AU - Bourlat, Sarah J.

AU - Giovanni, Renato

AU - Jong, Yde

AU - Leo, Francesca

AU - Dobor, Laura

AU - Donvito, Giacinto

AU - Fellows, Donal

AU - Guerra, Antonio Fernandez

AU - Ferreira, Nuno

AU - Fetyukova, Yuliya

AU - Fosso, Bruno

AU - Giddy, Jonathan

AU - Goble, Carole

AU - Güntsch, Anton

AU - Haines, Robert

AU - Ernst, Vera Hernández

AU - Hettling, Hannes

AU - Hidy, Dóra

AU - Horváth, Ferenc

AU - Ittzés, Dóra

AU - Ittzés, Péter

AU - Jones, Andrew

AU - Kottmann, Renzo

AU - Kulawik, Robert

AU - Leidenberger, Sonja

AU - Lyytikäinen-Saarenmaa, Päivi

AU - Mathew, Cherian

AU - Morrison, Norman

AU - Nenadic, Aleksandra

AU - Hidalga, Abraham Nieva

AU - Obst, Matthias

AU - Oostermeijer, Gerard

AU - Paymal, Elisabeth

AU - Pesole, Graziano

AU - Pinto, Salvatore

AU - Poigné, Axel

AU - Fernandez, Francisco Quevedo

AU - Santamaria, Monica

AU - Saarenmaa, Hannu

AU - Sipos, Gergely

AU - Sylla, Karl Heinz

AU - Tähtinen, Marko

AU - Vicario, Saverio

AU - Vos, Rutger Aldo

AU - Williams, Alan

AU - Yilmaz, Pelin

PY - 2016/10/20

Y1 - 2016/10/20

N2 - 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.

AB - 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.

KW - Analysis

KW - Automation

KW - Biodiversity science

KW - Biodiversity virtual e-laboratory

KW - Computing software

KW - Data processing

KW - Ecology

KW - Informatics

KW - Virtual laboratory

KW - Workflows

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U2 - 10.1186/s12898-016-0103-y

DO - 10.1186/s12898-016-0103-y

M3 - Article

AN - SCOPUS:84992153613

SN - 0012-9658

VL - 16

JO - Ecology

JF - Ecology

IS - 1

M1 - 49

ER -

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

Abstract

Keywords

Research Beacons, Institutes and Platforms

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