Tag: FAIR data

BiCIKL Project supports article collection in Biodiversity Data Journal about use of linked data

Welcomed are taxonomic and other biodiversity-related research articles, which demonstrate the advantages and novel approaches in accessing and (re-)using linked biodiversity data

The EU-funded project BiCIKL (Biodiversity Community Integrated Knowledge Library) will support free of charge publications* submitted to the dedicated topical collection: “Linking FAIR biodiversity data through publications: The BiCIKL approach” in the Biodiversity Data Journal, demonstrating advanced publishing methods of linked biodiversity data, so that they can be easily harvested, distributed and re-used to generate new knowledge. 

BiCIKL is dedicated to building a new community of key research infrastructures, researchers and citizen scientists by using linked FAIR biodiversity data at all stages of the research lifecycle, from specimens through sequencing, imaging, identification of taxa, etc. to final publication in novel, re-usable, human-readable and machine-interpretable scholarly articles.

Achieving a culture change in how biodiversity data are being identified, linked, integrated and re-used is the mission of the BiCIKL consortium. By doing so, BiCIKL is to help increase the transparency, trustworthiness and efficiency of the entire research ecosystem.

The new article collection welcomes taxonomic and other biodiversity-related research articles, data papers, software descriptions, and methodological/theoretical papers. These should demonstrate the advantages and novel approaches in accessing and (re-)using linked biodiversity data.

To be eligible for the collection, a manuscript must comply with at least two of the conditions listed below. In the submission form, the author needs to specify the condition(s) applicable to the manuscript. The author should provide the explanation in a cover letter, using the Notes to the editor field.

All submissions must abide by the community-agreed standards for terms, ontologies and vocabularies used in biodiversity informatics. 

The data used in the articles must comply with the Data Quality Checklist and Fair Data Checklist available in the Authors’ instructions of the journal.

Conditions for publication in the article collection:

  • The authors are expected to use explicit Globally Unique Persistent and Resolvable Identifiers (GUPRI) or other persistent identifiers (PIDs), where such are available, for the different types of data they use and/or cite in the manuscripts (specimens IDs, sequence accession numbers, taxon name and taxon treatment IDs, image IDs, etc.)

  • Global taxon reviews in the form of “cyber-catalogues” are welcome if they contain links of the key data elements (specimens, sequences, taxon treatments, images, literature references, etc.) to their respective records in external repositories. Taxon names in the text should not be hyperlinked. Instead, under each taxon name in the catalogue, the authors should add external links to, for example, Catalogue of Life, nomenclators (e.g. IPNI, MycoBank, Index Fungorum, ZooBank), taxon treatments in Plazi’s TreatmentBank or other relevant trusted resources.

  • Taxonomic papers (e.g. descriptions of new species or revisions) must contain persistent identifiers for the holotype, paratypes and at least most of the specimens used in the study.

  • Specimen records that are used for new taxon descriptions or taxonomic revisions and are associated with a particular Barcode Identification Number (BIN) or Species Hypothesis (SH) should be imported directly from BOLD or PlutoF, respectively, via the ARPHA Writing Tool data-import plugin.

  • More generally, individual specimen records used for various purposes in taxonomic descriptions and inventories should be imported directly into the manuscript from GBIF, iDigBio, or BOLD via the ARPHA Writing Tool data-import plugin. 

  • In-text citations of taxon treatments from Plazi’s TreatmentBank are highly welcome in any taxonomic revision or catalogue. The in-text citations should be hyperlinked to the original treatment data at TreatmentBank.

  • Hyperlinking other terms of importance in the article text to their original external data sources or external vocabularies is encouraged.

  • Tables that list gene accession numbers, specimens and taxon names, should conform to the Biodiversity Data Journal’s linked data tables guidelines.

  • Theoretical or methodological papers on linking FAIR biodiversity data are eligible for the BiCIKL collection if they provide real examples and use cases.

  • Data papers or software descriptions are eligible if they use linked data from the BiCIKL’s partnering research infrastructures, or describe tools and services that facilitate access to and linking between FAIR biodiversity data.

  • Articles that contain nanopublications created or added during the authoring process in Biodiversity Data Journal. A nanopublication is a scientifically meaningful assertion about anything that can be uniquely identified and attributed to its author and serve to communicate a single statement, for example biotic relationship between taxa, or habitat preference of a taxon. The in-built workflow ensures the linkage and its persistence, while the information is simultaneously human-readable and machine-interpretable.
  • Manuscripts that contain or describe any other novel idea or feature related to linked or semantically enhanced biodiversity data will be considered too.

We recommend authors to get acquainted with these two papers before they decide to submit a manuscript to the collection: 

Here are several examples of research questions that might be explored using semantically enriched and linked biodiversity data: 

(1) How does linking taxon names or Operational Taxonomic Units (OTUs) to related external data (e.g. specimen records, sequences, distributions, ecological & bionomic traits, images) contribute to a better understanding of the functions and regional/local processes within faunas/floras/mycotas or biotic communities?

(2) How could the production and publication of taxon descriptions and inventories – including those based mostly on genomic and barcoding data – be streamlined? 

(3) How could general conclusions, assertions and citations in biodiversity articles be expressed in formal, machine-actionable language, either to update prior work or express new facts (e.g. via nanopublications)? 

(4) How could research data and narratives be re-used to support more extensive and data-rich studies? 

(5) Are there other taxon- or topic-specific research questions that would benefit from richer, semantically enhanced FAIR biodiversity data?

All manuscripts submitted to the Biodiversity Data Journal have their data audited by data scientists prior to the peer review stage.

Once published, specimen records data are being exported in Darwin Core Archive to GBIF.

The data and taxon treatments are also exported to several additional data aggregators, such as TreatmentBank, the Biodiversity Literature Repository, and SiBILS amongst others. The full-text articles are also converted to Linked Open Data indexed in the OpenBiodiv Knowledge Graph.

All articles will need to acknowledge the BiCIKL project, Grant No 101007492 in the Acknowledgements section.

* The publication fee (APC) is waived for standard-sized manuscripts (up to 40,000 characters, including spaces) normally charged by BDJ at € 650. Authors of larger manuscripts will need to cover the surplus charge (€10 for each 1,000 characters above 40,000). See more about the APC policy at Biodiversity Data Journal, or contact the journal editorial team at: bdj@pensoft.net.

Follow the BiCIKL Project on Twitter and Facebook. Join the conservation on via #BiCIKL_H2020.

You can also follow Biodiversity Data Journal on Twitter and Facebook.

BiCIKL keeps on adding project outcomes in own collection in RIO Journal

The publications so far include the grant proposal; conference abstracts, a workshop report, guidelines papers and deliverables submitted to the Commission.

The dynamic open-science project collection of BiCIKL, titled “Towards interlinked FAIR biodiversity knowledge: The BiCIKL perspective” (doi: 10.3897/rio.coll.105), continues to grow, as the project progresses into its third year and its results accumulate ever so exponentially. 

Following the publication of three important BiCIKL deliverables: the project’s Data Management Plan, its Visual identity package and a report, describing the newly built workflow and tools for data extraction, conversion and indexing and the user applications from OpenBiodiv, there are currently 30 research outcomes in the BiCIKL collection that have been shared publicly to the world, rather than merely submitted to the European Commission.

Shortly after the BiCIKL project started in 2021, a project-branded collection was launched in the open-science scholarly journal Research Ideas and Outcomes (RIO). There, the partners have been publishing – and thus preserving – conclusive research papers, as well as early and interim scientific outputs.

The publications so far also include the BiCIKL grant proposal, which earned the support of the European Commission in 2021; conference abstracts, submitted by the partners to two consecutive TDWG conferences; a project report that summarises recommendations on interoperability among infrastructures, as concluded from a hackathon organised by BiCIKL; and two Guidelines papers, aiming to trigger a culture change in the way data is shared, used and reused in the biodiversity field. 

In fact, one of the Guidelines papers, where representatives of the Consortium of European Taxonomic Facilities (CETAF), the Society for the Preservation of Natural History Collections (SPNHC) and the Biodiversity Heritage Library (BHL) came together to publish their joint statement on best practices for the citation of authorities of scientific names, has so far generated about 4,000 views by nearly 3,000 unique readers.

At the time of writing, the top three of the most read papers in the BiCIKL collection is completed by the grant proposal and the second Guidelines paper, where the partners – based on their extensive and versatile experience – present recommendations about the use of annotations and persistent identifiers in taxonomy and biodiversity publishing. 

Access to data and services along the entire data and research life cycle in biodiversity science.
The figure was featured in the BiCIKL grant proposal, now made available from the BiCIKL project collection in RIO Journal.

What one might find quite odd when browsing the BiCIKL collection is that each publication is marked with its own publication source, even though all contributions are clearly already accessible from RIO Journal. 

So, we can see many project outputs marked as RIO publications, but also others that have been published in the likes of F1000Research, the official journal of TDWG: Biodiversity Information Science and Standards, and even preprints servers, such as BiohackrXiv. 

This is because one of the unique features of RIO allows for consortia to use their project collection as a one-stop access point for all scientific results, regardless of their publication venue, by means of linking to the original source via metadata. Additionally, projects may also upload their documents in their original format and layout, thanks to the integration between RIO and ARPHA Preprints. This is in fact how BiCIKL chose to share their latest deliverables using the very same files they submitted to the Commission.

“In line with the mission of BiCIKL and our consortium’s dedication to FAIRness in science, we wanted to keep our project’s progress and results fully transparent and easily accessible and reusable to anyone, anywhere,” 

explains Prof Lyubomir Penev, BiCIKL’s Project Coordinator and founder and CEO of Pensoft. 

“This is why we opted to collate the outcomes of BiCIKL in one place – starting from the grant proposal itself, and then progressively adding workshop reports, recommendations, research papers and what not. By the time BiCIKL concludes, not only will we be ready to refer back to any step along the way that we have just walked together, but also rest assured that what we have achieved and learnt remains at the fingertips of those we have done it for and those who come after them,” he adds.

***

You can keep tabs on the BiCIKL project collection in RIO Journal by subscribing to the journal newsletter or following @RIOJournal on Twitter and Facebook.

Interoperable biodiversity data extracted from literature through open-ended queries

OpenBiodiv is a biodiversity database containing knowledge extracted from scientific literature, built as an Open Biodiversity Knowledge Management System. 

The OpenBiodiv contribution to BiCIKL

Apart from coordinating the Horizon 2020-funded project BiCIKL, scholarly publisher and technology provider Pensoft has been the engine behind what is likely to be the first production-stage semantic system to run on top of a reasonably-sized biodiversity knowledge graph.

OpenBiodiv is a biodiversity database containing knowledge extracted from scientific literature, built as an Open Biodiversity Knowledge Management System. 

As of February 2023, OpenBiodiv contains 36,308 processed articles; 69,596 taxon treatments; 1,131 institutions; 460,475 taxon names; 87,876 sequences; 247,023 bibliographic references; 341,594 author names; and 2,770,357 article sections and subsections.

In fact, OpenBiodiv is a whole ecosystem comprising tools and services that enable biodiversity data to be extracted from the text of biodiversity articles published in data-minable XML format, as in the journals published by Pensoft (e.g. ZooKeys, PhytoKeys, MycoKeys, Biodiversity Data Journal), and other taxonomic treatments – available from Plazi and Plazi’s specialised extraction workflow – into Linked Open Data.

“I believe that OpenBiodiv is a good real-life example of how the outputs and efforts of a research project may and should outlive the duration of the project itself. Something that is – of course – central to our mission at BiCIKL.”

explains Prof Lyubomir Penev, BiCIKL’s Project Coordinator and founder and CEO of Pensoft.

“The basics of what was to become the OpenBiodiv database began to come together back in 2015 within the EU-funded BIG4 PhD project of Victor Senderov, later succeeded by another PhD project by Mariya Dimitrova within IGNITE. It was during those two projects that the backend Ontology-O, the first versions of RDF converters and the basic website functionalities were created,”

he adds.

At the time OpenBiodiv became one of the nine research infrastructures within BiCIKL tasked with the provision of virtual access to open FAIR data, tools and services, it had already evolved into a RDF-based biodiversity knowledge graph, equipped with a fully automated extraction and indexing workflow and user apps.

Currently, Pensoft is working at full speed on new user apps in OpenBiodiv, as the team is continuously bringing into play invaluable feedback and recommendation from end-users and partners at BiCIKL. 

As a result, OpenBiodiv is already capable of answering open-ended queries based on the available data. To do this, OpenBiodiv discovers ‘hidden’ links between data classes, i.e. taxon names, taxon treatments, specimens, sequences, persons/authors and collections/institutions. 

Thus, the system generates new knowledge about taxa, scientific articles and their subsections, the examined materials and their metadata, localities and sequences, amongst others. Additionally, it is able to return information with a relevant visual representation about any one or a combination of those major data classes within a certain scope and semantic context.

Users can explore the database by either typing in any term (even if misspelt!) in the search engine available from the OpenBiodiv homepage; or integrating an Application Programming Interface (API); as well as by using SPARQL queries.

On the OpenBiodiv website, there is also a list of predefined SPARQL queries, which is continuously being expanded.

Sample of predefined SPARQL queries at OpenBiodiv.

“OpenBiodiv is an ambitious project of ours, and it’s surely one close to Pensoft’s heart, given our decades-long dedication to biodiversity science and knowledge sharing. Our previous fruitful partnerships with Plazi, BIG4 and IGNITE, as well as the current exciting and inspirational network of BiCIKL are wonderful examples of how far we can go with the right collaborators,”

concludes Prof Lyubomir Penev.

***

Follow BiCIKL on Twitter and Facebook. Join the conversation on Twitter at #BiCIKL_H2020.

You can also follow Pensoft on Twitter, Facebook and Linkedin and use #OpenBiodiv on Twitter.

‘Nature’s Envelope’ – a simple device that reveals the scope and scale of all biological processes

All processes fit into a broad S-shaped envelope extending from the briefest to the most enduring biological events. For the first time, we have the first simple model that depicts the scope and scale of biology.

Arctic tern by Mark Stock, Schleswig-Holstein Wadden Sea National Park. License: CC BY-SA.

As biology is progressing into a digital age, it is creating new opportunities for discovery. 

Increasingly, information from investigations into aspects of biology from ecology to molecular biology is available in a digital form. Older ‘legacy’ information is being digitized. Together, the digital information is accumulated in databases from which it can be harvested and examined with an increasing array of algorithmic and visualization tools.

From this trend has emerged a vision that, one day, we should be able to analyze any and all aspects of biology in this digital world. 

However, before this can happen, there will need to be an infrastructure that gathers information from ALL sources, reshapes it as standardized data using universal metadata and ontologies, and made freely available for analysis. 

That information also must make its way to trustworthy repositories to guarantee the permanent access to the data in a polished and fully suited for re-use state.

The first layer in the infrastructure is the one that gathers all old and new information, whether it be about the migrations of ocean mammals, the sequence of bases in ribosomal RNA, or the known locations of particular species of ciliated protozoa.

How many of these subdomains will be there?

To answer this, we need to have a sense of the scope and scale of biology.

With the Nature’s Envelope we have, for the first time, a simple model that depicts the scope and scale of biology. Presented as a rhetorical device by its author Dr David J. Patterson (University of Sydney, Australia), the Nature’s Envelope is described in a Forum Paper, published in the open-science journal Research Ideas and Outcomes (RIO).

This is achieved by compiling information about the processes conducted by all living organisms. The processes occur at all levels of organization, from sub-molecular transactions, such as those that underpin nervous impulses, to those within and among plants, animals, fungi, protists and prokaryotes. Further, they are also the actions and reactions of individuals and communities; but also the sum of the interactions that make up an ecosystem; and finally, the consequences of the biosphere as a whole system. 

Nature’s Envelope, in green, includes all processes carried out by, involving, or the result of the activities of any and all organisms. The axes depict the duration of events and the sizes of participants using a log10 scale. Image by David J. Patterson. License: CC BY.

In the Nature’s Envelope, information on sizes of participants and durations of processes from all levels of organization are plotted on a grid. The grid uses a logarithmic (base 10) scale, which has about 21 orders of magnitude of size and 35 orders of magnitude of time. Information on processes ranging from the subatomic, through molecular, cellular, tissue, organismic, species, communities to ecosystems is assigned to the appropriate decadal blocks. 

Examples include movements from the stepping motion of molecules like kinesin that move forward 8 nanometres in about 10 milliseconds; or the migrations of Arctic terns which follow routes of 30,000 km or more from Europe to Antarctica over 3 to 4 months.

The extremes of life processes are determined by the smallest and largest entities to participate, and the briefest and most enduring processes.

The briefest event to be included is the transfer of energy from a photon to a photosynthetic pigment as the photon passes through a chlorophyll molecule several nanometres in width at a speed of 300,000 km per second. That transaction is conducted in about 10-17 seconds. As it involves the smallest subatomic particles, it defines the lower left corner of the grid. 

The most enduring is the process of evolution that has been progressing for almost 4 billion years. The influence of the latter has created the biosphere (the largest living object) and affects the gas content of the atmosphere. This process established the upper right extreme of the grid.

All biological processes fit into a broad S-shaped envelope that includes about half of the decadal blocks in the grid. The envelope drawn round the initial examples is Nature’s Envelope.

“Nature’s envelope will be a useful addition to many discussions, whether they deal with the infrastructure that will manage the digital age of biology, or provide the context for education on the diversity and range of processes that living systems engage in.

The version of Nature’s Envelope published in the RIO journal is seen as a first version, to be refined and enhanced through community participation,”

comments Patterson.

***

Original source:

Patterson DJ (2022) The scope and scale of the life sciences (‘Nature’s envelope’). Research Ideas and Outcomes 8: e96132. https://doi.org/10.3897/rio.8.e96132

***

Follow Research Ideas and Outcomes (RIO Journal) on Twitter, Facebook and Linkedin.

BiCIKL partners sign the Leiden Declaration on FAIR Digital Objects

Key figures from Naturalis Biodiversity Center, Plazi and Pensoft were amongst the first to sign the Declaration at the closing session of the First International Conference on FAIR Digital Objects (FDO2022)

Several of the BiCIKL partners signed the Leiden Declaration on FAIR Digital Objects, thereby committing to “a new environment that works as a truly meaningful data space,” as framed by the organisers of the conference, whose first instalment turned out to be the perfect occasion for the formal publication of the pact. 

Key figures from Naturalis Biodiversity Center, Plazi and Pensoft were amongst the first to sign the Declaration at the closing session of the First International Conference on FAIR Digital Objects (FDO2022), which took place in October 2022 in Leiden, the Netherlands, where it was hosted by the Naturalis Biodiversity Center.

***

The conference brought together key international technical, scientific, industry and science-policy stakeholders with the aim to boost the development and implementation of FAIR Digital Objects (FDOs) worldwide. It was organised by the FDO Forum, an initiative supported by major global initiatives and by a variety of regional and national initiatives with the shared goal to achieve a better coherence amongst the increasing number of initiatives working on FDO-based designs and implementations.  

By joining the Declaration’s signees, the BiCIKL partners formally committed to:

  • Support the FAIR guiding principles to be applied (ultimately) to each digital object in a web of FAIR data and services;  
  • Support open standards and protocols;
  • Support data and services to be as open as possible, and only as restricted as necessary;
  • Support distributed solutions where useful to achieve robustness and scalability, but recognise the need for centralised approaches where necessary;
    • Support the restriction of standards and protocols to the absolute minimum;
    • Support freedom to operate wherever possible;
    • Help to avoid monopolies and provider lock-in wherever possible.

***

During the event, Plazi and Pensoft held a presentation demonstrating how their Biodiversity Literature Repository turns taxonomic treatments ‘locked’ in legacy scientific literature into FAIR Digital Objects. As a result of the collaboration between Plazi and Pensoft – a partnership long-preceding their involvement in BiCIKL – this workflow has also been adapted to modern-day publishing, in order to FAIRify data as soon as it is published.

A slide from the Plazi presentation at the FDO2022, Leiden, the Netherlands. Credit: Plazi.

***

Ahead of FDO2022, all submitted conference abstracts – including the one associated with Plazi’s presentation – were made publicly available in a collection of their own in Pensoft’s open-science journal Research Ideas and Outcomes (RIO). Thus, not only did the organisers make the conference outputs available to the participants early on, so that they can familiarise themselves with the upcoming talks and topics in advance, but they also ensure that the contributions are permanently preserved and FAIR in their own turn. 

The conference collection, guest edited by Tina Loo (Naturalis Biodiversity Center), contains a total of 51 conference abstracts, where each is published in HTML, XML and PDF formats, and assigned with its own persistent identifier (DOI) just like the collection in its entirety (10.3897/rio.coll.190).

***

Read more about the declaration and sign it yourself from this link. You can also follow the FDO Forum on Twitter (@FAIRDOForum).

One Biodiversity Knowledge Hub to link them all: BiCIKL 2nd General Assembly

The FAIR Data Place – the key and final product of the partnership – is meant to provide scientists with all types of biodiversity data “at their fingertips”

The Horizon 2020 – funded project BiCIKL has reached its halfway stage and the partners gathered in Plovdiv (Bulgaria) from the 22nd to the 25th of October for the Second General Assembly, organised by Pensoft. 

The BiCIKL project will launch a new European community of key research infrastructures, researchers, citizen scientists and other stakeholders in the biodiversity and life sciences based on open science practices through access to data, tools and services.

BiCIKL’s goal is to create a centralised place to connect all key biodiversity data by interlinking 15 research infrastructures and their databases. The 3-year European Commission-supported initiative kicked off in 2021 and involves 14 key natural history institutions from 10 European countries.

BiCIKL is keeping pace as expected with 16 out of the 48 final deliverables already submitted, another 9 currently in progress/under review and due in a few days. Meanwhile, 21 out of the 48 milestones have been successfully achieved.

Prof. Lyubomir Penev (BiCIKL’s project coordinator Prof. Lyubomir Penev and CEO and founder of Pensoft) opens the 2nd General Assembly of BiCIKL in Plovdiv, Bulgaria.

The hybrid format of the meeting enabled a wider range of participants, which resulted in robust discussions on the next steps of the project, such as the implementation of additional technical features of the FAIR Data Place (FAIR being an abbreviation for Findable, Accessible, Interoperable and Reusable).

This FAIR Data Place online platform – the key and final product of the partnership and the BiCIKL initiative – is meant to provide scientists with all types of biodiversity data “at their fingertips”.

This data includes biodiversity information, such as detailed images, DNA, physiology and past studies concerning a specific species and its ‘relatives’, to name a few. Currently, the issue is that all those types of biodiversity data have so far been scattered across various databases, which in turn have been missing meaningful and efficient interconnectedness.

Additionally, the FAIR Data Place, developed within the BiCIKL project, is to give researchers access to plenty of training modules to guide them through the different services.

Halfway through the duration of BiCIKL, the project is at a turning point, where crucial discussions between the partners are playing a central role in the refinement of the FAIR Data Place design. Most importantly, they are tasked with ensuring that their technologies work efficiently with each other, in order to seamlessly exchange, update and share the biodiversity data every one of them is collecting and taking care of.

By Year 3 of the BiCIKL project, the partners agree, when those infrastructures and databases become efficiently interconnected to each other, scientists studying the Earth’s biodiversity across the world will be in a much better position to build on existing research and improve the way and the pace at which nature is being explored and understood. At the end of the day, knowledge is the stepping stone for the preservation of biodiversity and humankind itself.

“Needless to say, it’s an honour and a pleasure to be the coordinator of such an amazing team spanning as many as 14 partnering natural history and biodiversity research institutions from across Europe, but also involving many global long-year collaborators and their infrastructures, such as Wikidata, GBIF, TDWG, Catalogue of Life to name a few,”

said BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft.

“I see our meeting in Plovdiv as a practical demonstration of our eagerness and commitment to tackle the long-standing and technically complex challenge of breaking down the silos in the biodiversity data domain. It is time to start building freeways between all biodiversity data, across (digital) space, time and data types. After the last three days that we spent together in inspirational and productive discussions, I am as confident as ever that we are close to providing scientists with much more straightforward routes to not only generate more biodiversity data, but also build on the already existing knowledge to form new hypotheses and information ready to use by decision- and policy-makers. One cannot stress enough how important the role of biodiversity data is in preserving life on Earth. These data are indeed the groundwork for all that we know about the natural world”  

Prof. Lyubomir Penev added.
Christos Arvanitidis (CEO of LifeWatch ERIC) at the 2nd General Assembly of the BiCIKL project.

Christos Arvanitidis, CEO of LifeWatch ERIC, added:

“The point is: do we want an integrated structure or do we prefer federated structures? What are the pros and cons of the two options? It’s essential to keep the community united and allied because we can’t afford any information loss and the stakeholders should feel at home with the Project and the Biodiversity Knowledge Hub.”

Joe Miller, Executive Secretary and Director at GBIF, commented:

“We are a brand new community, and we are in the middle of the growth process. We would like to already have answers, but it’s good to have this kind of robust discussion to build on a good basis. We must find the best solution to have linkages between infrastructures and be able to maintain them in the future because the Biodiversity Knowledge Hub is the location to gather the community around best practices, data and guidelines on how to use the BiCIKL services… In order to engage even more partners to fill the eventual gaps in our knowledge.”

Joana Pauperio (biodiversity curator at EMBL-EBI) at the 2nd General Assembly of the BiCIKL project.

“BiCIKL is leading data infrastructure communities through some exciting and important developments”  

said Dr Guy Cochrane, Team Leader for Data Coordination and Archiving and Head of the European Nucleotide Archive at EMBL’s European Bioinformatics Institute (EMBL-EBI).

“In an era of biodiversity change and loss, leveraging scientific data fully will allow the world to catalogue what we have now, to track and understand how things are changing and to build the tools that we will use to conserve or remediate. The challenge is that the data come from many streams – molecular biology, taxonomy, natural history collections, biodiversity observation – that need to be connected and intersected to allow scientists and others to ask real questions about the data. In its first year, BiCIKL has made some key advances to rise to this challenge,”

he added.

Deborah Paul, Chair of the Biodiversity Information Standards – TDWG said:

“As a partner, we, at the Biodiversity Information Standards – TDWG, are very enthusiastic that our standards are implemented in BiCIKL and serve to link biodiversity data. We know that joining forces and working together is crucial to building efficient infrastructures and sharing knowledge.”

The project will go on with the first Round Table of experts in December and the publications of the projects who participated in the Open Call and will be founded at the beginning of the next year.

***

Learn more about BiCIKL on the project’s website at: bicikl-project.eu

Follow BiCIKL Project on Twitter and Facebook. Join the conversation on Twitter at #BiCIKL_H2020.

***

All BiCIKL project partners:

New BiCIKL project to build a freeway between pieces of biodiversity knowledge

Within Biodiversity Community Integrated Knowledge Library (BiCIKL), 14 key research and natural history institutions commit to link infrastructures and technologies to provide flawless access to biodiversity data.

In a recently started Horizon 2020-funded project, 14 European institutions from 10 countries, representing both the continent’s and global key players in biodiversity research and natural history, deploy and improve their own and partnering infrastructures to bridge gaps between each other’s biodiversity data types and classes. By linking their technologies, they are set to provide flawless access to data across all stages of the research cycle.

Three years in, BiCIKL (abbreviation for Biodiversity Community Integrated Knowledge Library) will have created the first-of-its-kind Biodiversity Knowledge Hub, where a researcher will be able to retrieve a full set of linked and open biodiversity data, thereby accessing the complete story behind an organism of interest: its name, genetics, occurrences, natural history, as well as authors and publications mentioning any of those.

Ultimately, the project’s products will solidify Open Science and FAIR (Findable, Accessible, Interoperable and Reusable) data practices by empowering and streamlining biodiversity research.

Together, the project partners will redesign the way biodiversity data is found, linked, integrated and re-used across the research cycle. By the end of the project, BiCIKL will provide the community with a more transparent, trustworthy and efficient highly automated research ecosystem, allowing for scientists to access, explore and put into further use a wide range of data with only a few clicks.

“In recent years, we’ve made huge progress on how biodiversity data is located, accessed, shared, extracted and preserved, thanks to a vast array of digital platforms, tools and projects looking after the different types of data, such as natural history specimens, species descriptions, images, occurrence records and genomics data, to name a few. However, we’re still missing an interconnected and user-friendly environment to pull all those pieces of knowledge together. Within BiCIKL, we all agree that it’s only after we puzzle out how to best bridge our existing infrastructures and the information they are continuously sourcing that future researchers will be able to realise their full potential,” 

explains BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft, a scholarly publisher and technology provider company.

Continuously fed with data sourced by the partnering institutions and their infrastructures, BiCIKL’s key final output: the Biodiversity Knowledge Hub, is set to persist with time long after the project has concluded. On the contrary, by accelerating biodiversity research that builds on – rather than duplicates – existing knowledge, it will in fact be providing access to exponentially growing contextualised biodiversity data.

***

Learn more about BiCIKL on the project’s website at: bicikl-project.eu

Follow BiCIKL Project on Twitter and Facebook. Join the conversation on Twitter at #BiCIKL_H2020.

***

The project partners:

Pensoft Annotator – a tool for text annotation with ontologies

By Mariya Dimitrova, Georgi Zhelezov, Teodor Georgiev and Lyubomir Penev

The use of written language to record new knowledge is one of the advancements of civilisation that has helped us achieve progress. However, in the era of Big Data, the amount of published writing greatly exceeds the physical ability of humans to read and understand all written information. 

More than ever, we need computers to help us process and manage written knowledge. Unlike humans, computers are “naturally fluent” in many languages, such as the formats of the Semantic Web. These standards were developed by the World Wide Web Consortium (W3C) to enable computers to understand data published on the Internet. As a result, computers can index web content and gather data and metadata about web resources.

To help manage knowledge in different domains, humans have started to develop ontologies: shared conceptualisations of real-world objects, phenomena and abstract concepts, expressed in machine-readable formats. Such ontologies can provide computers with the necessary basic knowledge, or axioms, to help them understand the definitions and relations between resources on the Web. Ontologies outline data concepts, each with its own unique identifier, definition and human-legible label.

Matching data to its underlying ontological model is called ontology population and involves data handling and parsing that gives it additional context and semantics (meaning). Over the past couple of years, Pensoft has been working on an ontology population tool, the Pensoft Annotator, which matches free text to ontological terms.

The Pensoft Annotator is a web application, which allows annotation of text input by the user, with any of the available ontologies. Currently, they are the Environment Ontology (ENVO) and the Relation Ontology (RO), but we plan to upload many more. The Annotator can be run with multiple ontologies, and will return a table of matched ontological term identifiers, their labels, as well as the ontology from which they originate (Fig. 1). The results can also be downloaded as a Tab-Separated Value (TSV) file and certain records can be removed from the table of results, if desired. In addition, the Pensoft Annotator allows to exclude certain words (“stopwords”) from the free text matching algorithm. There is a list of default stopwords, common for the English language, such as prepositions and pronouns, but anyone can add new stopwords.

Figure 1. Interface of the Pensoft Annotator application

In Figure 1, we have annotated a sentence with the Pensoft Annotator, which yields a single matched term, labeled ‘host of’, from the Relation Ontology (RO). The ontology term identifier is linked to a webpage in Ontobee, which points to additional metadata about the ontology term (Fig. 2).

Figure 2. Web page about ontology term

Such annotation requests can be run to perform text analyses for topic modelling to discover texts which contain host-pathogen interactions. Topic modelling is used to build algorithms for content recommendation (recommender systems) which can be implemented in online news platforms, streaming services, shopping websites and others.

At Pensoft, we use the Pensoft Annotator to enrich biodiversity publications with semantics. We are currently annotating taxonomic treatments with a custom-made ontology based on the Relation Ontology (RO) to discover treatments potentially describing species interactions. You can read more about using the Annotator to detect biotic interactions in this abstract.

The Pensoft Annotator can also be used programmatically through an API, allowing you to integrate the Annotator into your own script. For more information about using the Pensoft Annotator, please check out the documentation.

Data checking for biodiversity collections and other biodiversity data compilers from Pensoft

Guest blog post by Dr Robert Mesibov

Proofreading the text of scientific papers isn’t hard, although it can be tedious. Are all the words spelled correctly? Is all the punctuation correct and in the right place? Is the writing clear and concise, with correct grammar? Are all the cited references listed in the References section, and vice-versa? Are the figure and table citations correct?

Proofreading of text is usually done first by the reviewers, and then finished by the editors and copy editors employed by scientific publishers. A similar kind of proofreading is also done with the small tables of data found in scientific papers, mainly by reviewers familiar with the management and analysis of the data concerned.

But what about proofreading the big volumes of data that are common in biodiversity informatics? Tables with tens or hundreds of thousands of rows and dozens of columns? Who does the proofreading?

Sadly, the answer is usually “No one”. Proofreading large amounts of data isn’t easy and requires special skills and digital tools. The people who compile biodiversity data often lack the skills, the software or the time to properly check what they’ve compiled.

The result is that a great deal of the data made available through biodiversity projects like GBIF is — to be charitable — “messy”. Biodiversity data often needs a lot of patient cleaning by end-users before it’s ready for analysis. To assist end-users, GBIF and other aggregators attach “flags” to each record in the database where an automated check has found a problem. These checks find the most obvious problems amongst the many possible data compilation errors. End-users often have much more work to do after the flags have been dealt with.

In 2017, Pensoft employed a data specialist to proofread the online datasets that are referenced in manuscripts submitted to Pensoft’s journals as data papers. The results of the data-checking are sent to the data paper’s authors, who then edit the datasets. This process has substantially improved many datasets (including those already made available through GBIF) and made them more suitable for digital re-use. At blog publication time, more than 200 datasets have been checked in this way.

Note that a Pensoft data audit does not check the accuracy of the data, for example, whether the authority for a species name is correct, or whether the latitude/longitude for a collecting locality agrees with the verbal description of that locality. For a more or less complete list of what does get checked, see the Data checklist at the bottom of this blog post. These checks are aimed at ensuring that datasets are correctly organised, consistently formatted and easy to move from one digital application to another. The next reader of a digital dataset is likely to be a computer program, not a human. It is essential that the data are structured and formatted, so that they are easily processed by that program and by other programs in the pipeline between the data compiler and the next human user of the data.

Pensoft’s data-checking workflow was previously offered only to authors of data paper manuscripts. It is now available to data compilers generally, with three levels of service:

  • Basic: the compiler gets a detailed report on what needs fixing
  • Standard: minor problems are fixed in the dataset and reported
  • Premium: all detected problems are fixed in collaboration with the data compiler and a report is provided

Because datasets vary so much in size and content, it is not possible to set a price in advance for basic, standard and premium data-checking. To get a quote for a dataset, send an email with a small sample of the data topublishing@pensoft.net.

—

Data checklist

Minor problems:

  • dataset not UTF-8 encoded
  • blank or broken records
  • characters other than letters, numbers, punctuation and plain whitespace
  • more than one version (the simplest or most correct one) for each character
  • unnecessary whitespace
  • Windows carriage returns (retained if required)
  • encoding errors (e.g. “Dum?ril” instead of “Duméril”)
  • missing data with a variety of representations (blank, “-“, “NA”, “?” etc)

Major problems:

  • unintended shifts of data items between fields
  • incorrect or inconsistent formatting of data items (e.g. dates)
  • different representations of the same data item (pseudo-duplication)
  • for Darwin Core datasets, incorrect use of Darwin Core fields
  • data items that are invalid or inappropriate for a field
  • data items that should be split between fields
  • data items referring to unexplained entities (e.g. “habitat is type A”)
  • truncated data items
  • disagreements between fields within a record
  • missing, but expected, data items
  • incorrectly associated data items (e.g. two country codes for the same country)
  • duplicate records, or partial duplicate records where not needed

For details of the methods used, see the author’s online resources:

***

Find more for Pensoft’s data audit workflow provided for data papers submitted to Pensoft journals on Pensoft’s blog.

FAIR biodiversity data in Pensoft journals thanks to a routine data auditing workflow

Pensoft – GloBI workflow for FAIR data exchange and indexing of biotic interactions locked within scholarly articles

Pensoft – GloBI workflow for FAIR data exchange and indexing of biotic interactions locked within scholarly articles.

by Mariya Dimitrova, Jorrit Poelen, Georgi Zhelezov, Teodor Georgiev, Lyubomir Penev

Fig. 1. Pensoft-GloBI workflow for indexing biotic interactions from scholarly literature

Tables published in scholarly literature are a rich source of primary biodiversity data. They are often used for communicating species occurrence data, morphological characteristics of specimens, links of species or specimens to particular genes, ecology data and biotic interactions between species, etc. Tables provide a structured format for sharing numerous facts about biodiversity in a concise and clear way. 

Together with the rest of the article narrative, Pensoft publishes all tables in the semi-structured eXtensible Markup Language (XML) format. Tables are semantically enhanced with annotated taxonomic names, coordinates, localities and other fields from the Darwin Core Standard. 

Inspired by the potential use of semantically-enhanced tables for text and data mining, Pensoft and Global Biotic Interactions (GloBI) developed a workflow for extracting and indexing biotic interactions from tables published in scholarly literature. GloBI is an open infrastructure enabling the discovery and sharing of species interaction data. GloBI ingests and accumulates individual datasets containing biotic interactions and standardises them by mapping them to community-accepted ontologies, vocabularies and taxonomies. Data integrated by GloBI is accessible through an application programming interface (API) and as archives in different formats (e.g. n-quads). GloBI has indexed millions of species interactions from hundreds of existing datasets spanning over a hundred thousand taxa.

The workflow

First, all tables extracted from Pensoft publications and stored in the OpenBiodiv triple store were automatically retrieved (Step 1 in Fig. 1). There were 6993 tables from 21 different journals. To identify only the tables containing biotic interactions, we used an ontology annotator, currently developed by Pensoft using terms from the OBO Relation Ontology (RO). The Pensoft Annotator analyses free text and finds words and phrases matching ontology term labels.

We used the RO to create a custom ontology, or list of terms, describing different biotic interactions (e.g. ‘host of’, ‘parasite of’, ‘pollinates’) (Step 2 in Fig. 1).. We used all subproperties of the RO term labeled ‘biotically interacts with’ and expanded the list of terms with additional word spellings and variations (e.g. ‘hostof’, ‘host’) which were added to the custom ontology as synonyms of already existing terms using the property oboInOwl:hasExactSynonym.

This custom ontology was used to perform annotation of all tables via the Pensoft Annotator (Step 3 in Fig. 1). Tables were split into rows and columns and accompanying table metadata (captions). Each of these elements was then processed through the Pensoft Annotator and if a match from the custom ontology was found, the resulting annotation was written to a MongoDB database, together with the article metadata. The original table in XML format, containing marked-up taxa, was also stored in the records.

Thus, we detected 233 tables which contain biotic interactions, constituting about 3.4% of all examined tables. The scripts used for parsing the tables and annotating them, together with the custom ontology, are open source and available on GitHub. The database records were exported as json to a GitHub repository, from where they could be accessed by GloBI.

GloBI processed the tables further, involving the generation of a table citation from the article metadata and the extraction of interactions between species from the table rows (Step 4 in Fig. 1). Table citations were generated by querying the OpenBiodiv database with the DOI of the article containing each table to obtain the author list, article title, journal name and publication year. The extraction of table contents was not a straightforward process because tables do not follow a single schema and can contain both merged rows and columns (signified using the ‘rowspan’ and ‘colspan’ attributes in the XML). GloBI were able to index such tables by duplicating rows and columns where needed to be able to extract the biotic interactions within them. Taxonomic name markup allowed GloBI to identify the taxonomic names of species participating in the interactions. However, the underlying interaction could not be established for each table without introducing false positives due to the complicated table structures which do not specify the directionality of the interaction. Hence, for now, interactions are only of the type ‘biotically interacts with’ (Fig. 2) because it is a bi-directional one (e.g. ‘Species A interacts with Species B’ is equivalent to ‘Species B interacts with Species A’).

Fig. 2. Example of a biotic interaction indexed by GloBI.

Examples of species interactions provided by OpenBiodiv and indexed by GloBI are available on GloBI’s website.

In the future we plan to expand the capacity of the workflow to recognise interaction types in more detail. This could be implemented by applying part of speech tagging to establish the subject and object of an interaction.

In addition to being accessible via an API and as archives, biotic interactions indexed by GloBI are available as Linked Open Data and can be accessed via a SPARQL endpoint. Hence, we plan on creating a user-friendly service for federated querying of GloBI and OpenBiodiv biodiversity data. 

This collaborative project is an example of the benefits of open and FAIR data, enabling the enhancement of biodiversity data through the integration between Pensoft and GloBI. Transformation of knowledge contained in existing scholarly works into giant, searchable knowledge graphs increases the visibility and attributed re-use of scientific publications.

Tables published in scholarly literature are a rich source of primary biodiversity data. They are often used for communicating species occurrence data, morphological characteristics of specimens, links of species or specimens to particular genes, ecology data and biotic interactions between species etc. Tables provide a structured format for sharing numerous facts about biodiversity in a concise and clear way.

Together with the rest of the article narrative, Pensoft publishes all tables in the semi-structured eXtensible Markup Language (XML) format. Tables are semantically enhanced with annotated taxonomic names, coordinates, localities and other fields from the Darwin Core Standard.

Inspired by the potential use of semantically-enhanced tables for text and data mining, Pensoft and Global Biotic Interactions (GloBI) developed a workflow for extracting and indexing biotic interactions from tables published in scholarly literature. GloBI is an open infrastructure enabling the discovery and sharing of species interaction data. GloBI ingests and accumulates individual datasets containing biotic interactions and standardises them by mapping them to community-accepted ontologies, vocabularies and taxonomies. Data integrated by GloBI is accessible through an application programming interface (API) and as archives in different formats (e.g. n-quads). GloBI has indexed millions of species interactions from hundreds of existing datasets spanning over a hundred thousand taxa.

The workflow

First, all tables extracted from Pensoft publications and stored in the OpenBiodiv triple store were automatically retrieved (Step 1 in Fig. 1). There were 6,993 tables from 21 different journals. To identify only the tables containing biotic interactions, we used an ontology annotator, currently developed by Pensoft using terms from the OBO Relation Ontology (RO). The Pensoft Annotator analyses free text and finds words and phrases matching ontology term labels.

We used the RO to create a custom ontology, or list of terms, describing different biotic interactions (e.g. ‘host of’, ‘parasite of’, ‘pollinates’) (Step 1 in Fig. 1). We used all subproperties of the RO term labeled ‘biotically interacts with’ and expanded the list of terms with additional word spellings and variations (e.g. ‘hostof’, ‘host’) which were added to the custom ontology as synonyms of already existing terms using the property oboInOwl:hasExactSynonym.

This custom ontology was used to perform annotation of all tables via the Pensoft Annotator (Step 3 in Fig. 1). Tables were split into rows and columns and accompanying table metadata (captions). Each of these elements was then processed through the Pensoft Annotator and if a match from the custom ontology was found, the resulting annotation was written to a MongoDB database, together with the article metadata. The original table in XML format, containing marked-up taxa, was also stored in the records.

Thus, we detected 233 tables which contain biotic interactions, constituting about 3.4% of all examined tables. The scripts used for parsing the tables and annotating them, together with the custom ontology, are open source and available on GitHub. The database records were exported as JSON to a GitHub repository, from where they could be accessed by GloBI.

GloBI processed the tables further, involving the generation of a table citation from the article metadata and the extraction of interactions between species from the table rows (Step 4 in Fig. 1). Table citations were generated by querying the OpenBiodiv database with the DOI of the article containing each table to obtain the author list, article title, journal name and publication year. The extraction of table contents was not a straightforward process because tables do not follow a single schema and can contain both merged rows and columns (signified using the ‘rowspan’ and ‘colspan’ attributes in the XML). GloBI were able to index such tables by duplicating rows and columns where needed to be able to extract the biotic interactions within them. Taxonomic name markup allowed GloBI to identify the taxonomic names of species participating in the interactions. However, the underlying interaction could not be established for each table without introducing false positives due to the complicated table structures which do not specify the directionality of the interaction. Hence, for now, interactions are only of the type ‘biotically interacts with’ because it is a bi-directional one (e.g. ‘Species A interacts with Species B’ is equivalent to ‘Species B interacts with Species A’).

In the future, we plan to expand the capacity of the workflow to recognise interaction types in more detail. This could be implemented by applying part of speech tagging to establish the subject and object of an interaction.

In addition to being accessible via an API and as archives, biotic interactions indexed by GloBI are available as Linked Open Data and can be accessed via a SPARQL endpoint. Hence, we plan on creating a user-friendly service for federated querying of GloBI and OpenBiodiv biodiversity data. 

This collaborative project is an example of the benefits of open and FAIR data, enabling the enhancement of biodiversity data through the integration between Pensoft and GloBI. Transformation of knowledge contained in existing scholarly works into giant, searchable knowledge graphs increases the visibility and attributed re-use of scientific publications.

References

Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.

Additional Information

The work has been partially supported by the International Training Network (ITN) IGNITE funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 764840.