BackgroundMaking 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.ResultsBioVeL 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.ConclusionsOur 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12898-016-0103-y) contains supplementary material, which is available to authorized users.

Ecological niche modelling (ENM) Components are a set of reusable workflow components specialized for performing ENM tasks within the Taverna workflow management system. Each component encapsulates specific functionality and can be combined with other components to facilitate the creation of larger and more complex workflows. One key distinguishing feature of ENM Components is that most tasks are performed remotely by calling web services, simplifying software setup and maintenance on the client side and allowing more powerful computing resources to be exploited. This paper presents the current set of ENM Components in the context of the Taverna family of tools for creating, publishing and sharing workflows. An example is included showing how the components can be used in a preliminary investigation of the effects of mixing different spatial resolutions in ENM experiments.

This article is about the GEOeBIZ project which wants to improve business opportunities in geomarketing for small and medium enterprises. The project's central hypothesis is that spatial data infrastructures will move from data catalogues to federated platforms for the development of low cost and low risk applications. To complement the data-retrieval services of the Open GeoSpatial Consortium the project will design, implement and apply both, visual analysis services for geomarketing and e-business services for commercial exploitation. The article proposes a framework and services for visual analysis

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