|
Getting your Trinity Audio player ready...
|
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.)
- Manuscripts must use data linked between at least three of the BiCIKL’s partnering research infrastructures (e.g. GBIF, BOLD, DiSSCo, Zenodo, INDSC (ENA), PlutoF, OpenBiodiv, TreatmentBank, Biodiversity Literature Repository, Biodiversity Heritage Library, SiBILS, Catalogue of Life). Highly welcome are also submissions that include additional data from research infrastructures which are not part of BiCIKL (e.g. iDigBio, OBIS, Atlas of Living Australia, Encyclopedia of Life, GLOBI). In their cover letter, the author needs to specify which infrastructures are used and how the data are linked between these.
- 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.
- Data papers describing omics data should use the omics data paper workflow (see also https://doi.org/10.1093/gigascience/giab034).
- 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.