dataesr/scientific-paragraphs-categorization huggingface dataset:
Achieving the aims of the recently established Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES)  [4]  requires progressive developments in approach and method. The complexity and scope of analyses in biodiversity science and ecology is growing very fast. It is becoming more common to carry out complex analysis using hundreds of data files with different structures and data types (e. g. , genetic, species, geographical, environmental) combined with a variety of algorithms; producing results that need to be visualized in innovative ways. The requirement for scientists to work together, with collaborations that integrate datasets across many different parties and synthesize answers computationally to address larger scientific questions are becoming the norm.
Scientific workflow systems can be broadly organised into three categories. First, those developed for specialist domains, often with capabilities to be extended to other disciplines (e. g. , LONI pipeline for neuro-imaging  [18] ; Galaxy for omics data processing; KNIME for pharmacological drug discovery). Secondly, there are workflow systems developed to be independent of any particular science discipline, with features for incorporating specialised customisations (e. g. , Apache Taverna). Thirdly, there are those that cut across disciplines and focus on specific tasks (e. g. , RapidMiner for data mining). Workflows support both automation of routine tasks (data transformation, mining, integration, processing, modelling) and pursuit of novel, large-scale analysis across distributed data resources.
Today, such activities are typically done in the R environment and here the integration with workflow systems can add value to current practice in ecological research. Most importantly, the record of what was done (the provenance) and the reproducibility of complex analyses can be enhanced when migrating ecological analysis into workflow environments, while workflow systems are able to handle the procedures for scaling computation on cloud infrastructure, for example. For this purpose, scientific workflow systems are starting to become used in biodiversity science and ecology for example: in ecology  [19, 20] , niche and distribution modelling  [21] [22] [23] , and digitisation of biological collections  [24, 25]. Workflows can be deployed, executed, and shared in virtual laboratories. A modern virtual laboratory (sometimes also known as a virtual research environment, VRE) is a web-enabled software application that brings the digital, Internet-based data resources (which may include data collections, databases, sensors and/or other instruments) together with processing and analytical tools needed to carry out "in silico" or "e-science" work.
Implementation The biodiversity virtual e-laboratory (BioVeL) provides a flexible general-purpose approach to processing and analysing biodiversity and ecological data (such as species distribution, taxonomic, ecological and genetic data). It is based on distributed computerised services accessible via the Internet that can be combined into sequences of steps (workflows) to perform different tasks. The main components of the platform are illustrated in Fig. 1  and described following, with cross-references (A)-(F) between the text and the figure. Additional file 1 to the present article provides 'how-to' guidelines on how to make use of the various components. Web services for biodiversity science and ecology: (A) in Fig. 1  In computing terms, Web services are pieces of computing functionality (analytical software tools and data resources) deployed at different locations on the Internet (Worldwide Web)  [27].
Currently (date of writing), it catalogues 70+ services (some of which are aggregates of multiple capabilities) from 50+ service providers, including Global Biodiversity Information Facility (GBIF), European Bioinformatics Institute (EBI), EUBra-zilOpenBio, PenSoft Publishers, Royal Botanic Gardens Kew, Species2000/ITIS Catalogue of Life (CoL), Pangaea, World Register of Marines Species (WoRMS), Naturalis Biodiversity Center and Canadensys). It has 130+ contributing members and is open for any provider of similar kinds of capabilities to register their Web services there. The catalogue supports registration, discovery, curation and monitoring of Web services. Catalogue entries are contributed by the community and also curated by the community. Experts oversee the curation process to ensure that descriptions are high quality and that the services entries are properly annotated.
This public portrayal of service performance information encourages Service Providers to invest time and effort in maintaining and improving the availability and reliability of their offering. 1  Biodiversity virtual laboratory (BioVeL) is a software environment that assists scientists in collecting, organising, and sharing data processing and analysis tasks in biodiversity and ecological research. The main components of the platform are: A the Biodiversity Catalogue (a library with wellannotated data and analysis services); B the environment, such as RStudio for creating R programs; C the workbench for assembling data access and analysis pipelines; D the myExperiment workflow library that stores existing workflows; E the BioVeL Portal that allows researchers and collaborators to execute and share workflows; and F the documentation wiki.
Metagenomics Microbial metagenomic trait calculation and statistical analysis (MMT) workflow calculates key ecological traits of bacterial communities as observed by high throughput metagenomic DNA sequencing. Typical use is in the analysis of environmental sequencing information from natural and disturbed habitats as a routine part of monitoring programs purl: http://www. purl. ox. ac. uk/workflow/myexp-4489. 3 Portal: access on request (BioMaS) Bioinformatic analysis of Metagenomic ampliconS is a bioinformatic pipeline supporting biomolecular researchers to carry out taxonomic studies of environmental microbial communities by a completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data arrangement to final taxonomic identification. This workflow is typically used in meta-barcoding high-throughput-sequencing experiments url: https://www.
biodiversitycatalogue. org/services/71 Scientific studies:  [41] [42] [43]  Creating R programs that use Web services: (B) in Fig. 1  Users can interact with the Biodiversity Catalogue and its services in a variety of ways, one of which is by developing their own analysis programs that invoke services in the catalogue. Both the catalogue itself and the services that are advertised in it are exposed through Applications Programming Interfaces (API) that are accessible using standard Internet protocols (HTTP, with RESTful or SOAP functionality). Hence, writing custom analysis code is relatively straightforward in commonly-used programming languages, such as R  [31]. The advantage of this way of interacting with the Biodiversity Catalogue services is that users can do this within a development environment (such as RStudio  [48] ).
This enables them to go through their analysis one step at a time (in a "read-eval-print loop") visually probing their data as it accumulates. Users can include additional functionalities accessible through Web services  [49]  as well as from relevant third-party R packages for biodiversity and ecological analysis; many of which have been developed in recent years. These latter are available, for example via CRAN  [50]. The Additional file 1 'how-to' guidelines points to an example of how to create an R program that calls a Web service. Given the popularity of the R programming language in biodiversity and ecology, we expect to see not just ad hoc analysis programs but also published, re-usable analysis libraries written against Web services APIs. The Biodiversity Catalogue provides a single place where such Web services can be found.
Combined with other capabilities of the BioVeL platform, including transparent access to greater levels of computing capability and capacity for processing large amounts of data, managing the complexity of multiple workflow runs, sharing workflows and provenance, offering data services, etc. ) Web services can be applied (i) consistently and (ii) in combination. We have given further examples of potential areas of application where these functions can be combined to support and accelerate new research in the "Discussion" section below (under 'Towards more comprehensive and global investigations'). Creating a workflow from an R program: (B) and (C) in Fig. 1  It is possible to convert pre-existing R programs for inclusion into Taverna workflows as discrete 'R service' steps. We have developed some recommendations  [51]  to make this as easy as possible.
We have, for example taken an existing R program that uses data from a local directory and incorporated this into a workflow that generates graphical plots from Ocean Sampling Day (OSD) data  [41]  to visualise the metagenomic sequence diversity in ocean water samples. We exposed the inputs and outputs of the R program as 'ports' of the corresponding R service, such that the program can be easily re-run using different data. A user could re-use this or another R program, wrapped as a service into their own workflow. Because the workflow is executed on the BioVeL platform, including execution of the R service, there is no need to run R locally on their own computer. This approach gives the possibility to combine R programs and workflows in complementary fashion, the full power of which becomes evident when workflows are embedded as executable objects in 3rd party web sites and web applications (see "Execute a workflow in external applications" section, below).
Each step is in reality an encapsulation of a software tool (an R program, for example) with its own inputs and outputs. Workbench users link the inputs of a step to the outputs from a preceding step and the outputs to the inputs of the next step. Links can be edited when steps are inserted, removed or re-organised. The user can test the workflow by running it locally on their desktop computer or by uploading it to BioVeL Portal (described below). We have provided a customised version of the Workbench, Taverna Workbench for Biodiversity  [52] , configured with a selectable palette of services especially relevant to biodiversity science and ecology. This version provides a direct link to the Biodiversity Catalogue, allowing users to search for the most recent and useful external Web services provided by the community as a whole.
The required data management and visualization resources were already in place, provided by other elements of the existing workflow and the BioSTIF service (Table  1 ). The ESW DIFF workflow was modified to include the functionality of the new variant. In a further example: Aphia, the database underlying the World Register of Marine Species (WoRMS)  [53]  is a consolidated database for marine species information, containing valid species names, synonyms and vernacular names, higher taxon classification information and extra information such as literature and biogeographic data. Its principal aim is to aid data management, rather than to suggest any taxonomic or phylogenetic opinion on species relationships. As such it represents a resource that is complementary to those already programmed as part of the Data Refinement Workflow (Table  2 ).
Once initiated, users are able to follow the progress of the analysis and interact with it to adjust parameters or to view intermediate results. When satisfied with the final results, a user can share these with others or download them to their local computer. Results can be used as inputs to subsequent work or incorporated into publications, with citation to the workflow and parameters that produced them. We adopted and adapted SEEK, the systems biology and data model platform  [57]  to meet the needs of the biodiversity science and ecology community. We rebranded SEEK for BioVeL and gave it a user interface suited to typical tasks associated with uploading and executing workflows and managing the results of workflow runs. We equipped it to execute workflows on the users' behalf, for multiple users and multiple workflows simultaneously.
The BioVeL Portal offers functions for discovering, organising and sharing both blueprints for analyses (i. e. , workflows) as well as results of analyses (i. e. , workflow runs) among collaborators and groups. The Portal provides users with their own personal workspace in which to execute workflows using their own data and to keep their results. Users can manage how their results are shared. At any time, they can share workflows and results publicly, within and between projects, or in groups of individuals. Users can return to their work at any time and pick up where they left off. This ability to create 'pop-up' collaborations by inviting individuals into a shared workspace to explore an emerging topic, and to keep track of work offers an immediate way to establish exciting new collaborations with little administrative overhead.
Presently (at the time of writing) there are 50 workflows publicly available within the BioVeL Portal. To support them we have provided a Support Centre, including training materials, documentation (http://wiki. biovel. eu) and helpdesk (mailto:support@biovel. eu) where users can obtain assistance. The expanded version of Table  2  in the Additional file 3 gives full details. As an example, workflows created for invasive alien species studies  [54]  have been frequently re-used in other scientific analyses; for example, to predict potential range shifts of commercially important species under scenarios of climatic change  [36] , and to describe the biogeographic range of Asian horseshoe crabs  [58]. Here especially, seamless linkage of data access to species occurrence records and environmental data layers, as well as the partly automated cleaning and processing procedures are useful functions when running niche modelling experiments for several species across a large number of parameter settings.
The Data Refinement Workflow  [59]  has likewise been used in both preparation of niche modelling experiments as well as in analysis of historical changes in benthic community structure  [34]. Here especially, the Taxonomic Name Service and data cleaning functions were helpful in resolving synonyms, correcting misspellings, and dealing with other inconsistencies in datasets compiled from different sources. The Portal also offers functions for data and parameter sweeping. This includes batch processing of large quantities of separate input data using the same parameters (data sweeping) and batch processing the same data using different parameters (parameter sweeping). As example, the niche modelling workflow (Table  2 , ENM) has 15 user interaction steps where parameters or files have to be supplied.
When repeated manually multiple times this is error-prone. The sweep functions can be used to automate systematic exploration of how data and parameters affect the results in a larger analysis. In such cases the Portal can automatically initiate multiple workflow runs in parallel, significantly reducing the time needed to complete all the planned experiments. It is possible to delegate computing intensive operations to 3rd party computing facilities such as a high performance computing (HPC) centre or a cloud computing service. Scientists have used the batch processing capability of BioVeL to explore parameter space in models and to generate comparable results for a large number of species. For example, in investigations of present and future distributions of shellfish (Asian Horseshoe Crabs) under predicted climate changes, the technique has been used to generate consensus outputs based on several different, individually executed niche modelling algorithms (for example: Max-Ent, Support Vector Machine and Environmental Distance) to build and evaluate a wide range of models with different combinations of environmental data layers (parameter sweep with 12 different combinations of environmental layers); and to build models for multiple ecologically similar species (data sweep for six intertidal shellfish species).
Principal findings We wanted to kick-start familiarisation and application of the workflow approach in biodiversity science and ecology. Our work shows that the Biodiversity Virtual e-Laboratory (BioVeL) is a viable operational and flexible general-purpose approach to collaboratively processing and analysing biodiversity and ecological data. It integrates existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research. This includes functions for: accessing data through curated Web services; performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; on-line collaboration through sharing of workflows and workflow runs; experiment documentation through reproducibility and repeatability; and computational support via seamless connections to supporting computing infrastructures.
Towards more comprehensive and global investigations The principal BioVeL functionalities support more comprehensive and global investigations of biodiversity patterns and ecological processes. Such investigations are not impossible today but they are expensive and often can only be addressed with large and resourceful scientific networks. Exploiting such scalability is particularly attractive, for example to prepare and verify large-scale data products relating to the essential biodiversity variables (EBV)  [67] ; for phyloclimatic investigations  [68] ; and for characterisation of biogeographic regions  [69]. In addition, complex predictive approaches that couple mechanistic with statistical models may benefit from the use of the BioVeL environment  [70]. All these kinds of processing usually require integration of distributed biological, climate and environmental data, drawn from public databases as well as personal sources.
Dependency on supporting infrastructure and robust Web services One apparent drawback of the approach we describe is dependency on the ready availability of robust infrastructure to provide access to data and to processing capabilities. This is out of the control of the end-user scientists but it is a matter for service providers. It is the same issue we face as consumer users of the Internet, whereby we rely on a well-developed portfolio of robust related services; for example, for making our travel arrangements with airlines, rental cars and hotels. In the biodiversity and ecology domain this is not the case. The portfolio of services is not yet well developed. There are only a limited number of robust large-scale service providers thus far (GBIF, EMBL-EBI, OBIS, PANGAEA to name just four examples) and not many smaller ones.
Embedding elements of it within third party applications and contexts such as Scratchpads  [75] , Jupyter/iPython Notebooks  [76] , data analysis for Ocean Sampling Day collection events  [41] , national level biodiversity information infrastructures  [77]  and biodiversity observation networks has a multiplier effect, making it possible for all users of those wider communities and others to execute and exploit the power of workflows. The underlying SEEK platform  [57]  on which Bio-VeL is based (not to be confused with the SEEK project mentioned above) is designed fundamentally to assist scientists to organise their digital data analysis work. As well as supporting execution of workflows, it allows them to describe, manage and execute their projects. These normally consist of experiments, datasets, models, and results.
It helps scientists by gathering and organising pieces of information related to these different artefacts into different categories and making links between them; namely: yellow pages (programmes, people, projects, institutions); experiments (investigations, studies, assays); assets (datasets, models, standard operating procedures, publications); and activities (presentations, events). Not all the functionality of SEEK is presently enabled in the BioVeL Portal variant but in future it can be enabled as the needs of the community grow.
Ecosystem modellingA basic toolbox for studies of carbon sequestration and ecosystem function. It includes data-model integration and calibration services, model testing and Monte Carlo Experiment services, ecosystem valuation services, and bioclimatic services Metagenomics A basic set of services for studying community structure and function from metagenomic ecological datasets. It includes services for geo-referenced annotation, metadata services, taxonomic binning and classification services, metagenomic traits services, and services for multivariate analysis Phylogenetics Services to enable DNA sequence mining and alignment, core phylogenetic inference, tree.
Acknowledgements More than 80 persons across 15 partner organisations have been involved in the work over 4 years as part of the  BioVeL consortium. Without the contributions of each of them we would not have arrived at the position of being able to offer a pilot service to the scientific community for in silico digital biodiversity and ecosystems research. We thank you for your contribution. We acknowledge the contribution of  Yannick Legré , who contributed to the conception and design of the work but ultimately was unable to participate in the project. We acknowledge the helpful support and constructive criticism we received during the validation stage of our work from  A. Townsend Peterson  and  Jorge Soberón  (both of  Biodiversity Institute and Natural History Museum, University of Kansas ),  Robert Guralnick  ( Florida Museum of Natural History, University of Florida ) and  Mark P.
tual  e-Laboratory (BioVeL)  project (http://www. biovel. eu)funded by the  European Union   7th Framework Programme , Grant no. 283359  ( 2011-2014 ). The work was furthermore supported by the  Swedish LifeWatch  project funded by the  Swedish Research Council  (Grant no. 829-2009-6278 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the present article.
Ecosystem modellingA basic toolbox for studies of carbon sequestration and ecosystem function. It includes data-model integration and calibration services, model testing and Monte Carlo Experiment services, ecosystem valuation services, and bioclimatic services Metagenomics A basic set of services for studying community structure and function from metagenomic ecological datasets. It includes services for geo-referenced annotation, metadata services, taxonomic binning and classification services, metagenomic traits services, and services for multivariate analysis Phylogenetics Services to enable DNA sequence mining and alignment, core phylogenetic inference, tree visualization, and phylogenetic community structure, for broad use in evolutionary and ecological studiesPopulation modellingServices for demographic data and their integration into matrix projection models and integral projection models (MPM, IPM) Taxonomy Services for taxonomic name resolution, checklists and classification, and species occurrence data retrieval.
portal. biovel. eu/workflows/596 Integral projection models workflow provides an environment to create and test an integral projection model and to perform several analyses on that purl: http://www. purl. ox. ac. uk/researchobj/myexp-482 Portal: https://www. portal. biovel. eu/workflows/599 Scientific studies: no publication yet Ecosystem modelling Based around the Biome-BGC biogeochemical model, a collection of five workflows for calibrating and using Biome- BGC for modelling ecosystems and calculating a range of ecosystem service indicators. The Biome-BGC projects database and management system provides a user interface for setting of model parameters, for support sharing and reusing of datasets and parameter settings purl: http://www. purl. ox. ac. uk/researchobj/myexp-687 Portal: https://www.