Enriched biodiversity data as a resource and service

Background: Recent years have seen a surge in projects that produce large volumes of structured, machine-readable biodiversity data. To make these data amenable to processing by generic, open source “data enrichment” workflows, they are increasingly being represented in a variety of standards-compliant interchange formats. Here, we report on an initiative in which software developers and taxonomists came together to address the challenges and highlight the opportunities in the enrichment of such biodiversity data by engaging in intensive, collaborative software development: The Biodiversity Data Enrichment Hackathon. Results: The hackathon brought together 37 participants (including developers and taxonomists, i.e. scientific professionals that gather, identify, name and classify species) from 10 countries: Belgium, Bulgaria, Canada, Finland, Germany, Italy, the Netherlands, New Zealand, the UK, and the US. The participants brought expertise in processing structured data, text mining, development of ontologies, digital identification keys, geographic information systems, niche modeling, natural language processing, provenance annotation, semantic integration, taxonomic name resolution, web service interfaces, workflow tools and visualisation. Most use cases and exemplar data were provided by taxonomists. One goal of the meeting was to facilitate re-use and enhancement of biodiversity knowledge by a broad range of stakeholders, such as taxonomists, systematists, ecologists, niche modelers, informaticians and ontologists. The suggested use cases resulted in nine breakout groups addressing three main themes: i) mobilising heritage biodiversity knowledge; ii) formalising and linking concepts; and iii) addressing interoperability between service platforms. Another goal was to further foster a community of experts in biodiversity informatics and to build human links between research projects and institutions, in response to recent calls to further such integration in this research domain. Conclusions: Beyond deriving prototype solutions for each use case, areas of inadequacy were discussed and are being pursued further. It was striking how many possible applications for biodiversity data there were and how quickly solutions could be put together when the normal constraints to collaboration were broken down for a week. Conversely, mobilising biodiversity knowledge from their silos in heritage literature and natural history collections will continue to require formalisation of the concepts (and the links between them) that define the research domain, as well as increased interoperability between the software platforms that operate on these concepts

Recommendations for interoperability among infrastructures

The BiCIKL project is born from a vision that biodiversity data are most useful if they are presented as a network of data that can be integrated and viewed from different starting points. BiCIKL’s goal is to realise that vision by linking biodiversity data infrastructures, particularly for literature, molecular sequences, specimens, nomenclature and analytics. To make those links we need to better understand the existing infrastructures, their limitations, the nature of the data they hold, the services they provide and particularly how they can interoperate. In light of those aims, in the autumn of 2021, 74 people from the biodiversity data community engaged in a total of twelve hackathon topics with the aim to assess the current state of interoperability between infrastructures holding biodiversity data. These topics examined interoperability from several angles. Some were research subjects that required interoperability to get results, some examined modalities of access and the use and implementation of standards, while others tested technologies and workflows to improve linkage of different data types.These topics and the issues in regard to interoperability uncovered by the hackathon participants inspired the formulation of the following recommendations for infrastructures related to (1) the use of data brokers, (2) building communities and trust, (3) cloud computing as a collaborative tool, (4) standards and (5) multiple modalities of access:If direct linking cannot be supported between infrastructures, explore using data brokers to store linksCooperate with open linkage brokers to provide a simple way to allow two-way links between infrastructures, without having to co-organize between many different organisationsFacilitate and encourage the external reporting of issues related to their infrastructure and its interoperability.Facilitate and encourage requests for new features related to their infrastructure and its interoperability.Provide development roadmaps openlyProvide a mechanism for anyone to ask for helpDiscuss issues in an open forumProvide cloud-based environments to allow external participants to contribute and test changes to featuresConsider the opportunities that cloud computing brings as a means to enable shared management of the infrastructure.Promote the sharing of knowledge around big data technologies amongst partners, using cloud computing as a training environmentInvest in standards compliance and work with standards organisations to develop new, and extend existing standardsReport on and review standards compliance within an infrastructure with metrics that give credit for work on standard compliance and developmentProvide as many different modalities of access as possibleAvoid requiring personal contacts to download dataProvide a full description of an API and the data it servesFinally, the hackathons were an ideal meeting opportunity to build, diversify and extend the BiCIKL community further, and to ensure the alignment of the community with a common vision on how best to link data from specimens, samples, sequences, taxonomic names and taxonomic literature

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

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.Peer reviewe

ColeopteraAndLocalDatabases.zip

this is the coleoptera reference database used to assign reads of MPE4 and MPE5 samples

DenoidedSequences.zip

Read denoised by AmpliconNoise pipeline

Raw and Denoised Sequences with their Reference Datasets

Raw and Denoised sequences of the two environmental samples (MPE4, MPE5) and the reference datasets used in taxonomic assignment methods

run_HSTA.sh

this is a bash script able to run HSTA pipelin

SpeciesProfiles.zip

Reference species for MPE5 and MPE4 sample

OrdersProfiles.zip

Reference orders for MPE5 and MPE4 sample