scholarly journals European Journal of Taxonomy: a deeper look into a decade of data

2021 ◽  
Vol 782 ◽  
pp. 173-196
Author(s):  
Laurence Bénichou ◽  
Marcus Guidoti ◽  
Isabelle Gérard ◽  
Donat Agosti ◽  
Tony Robillard ◽  
...  

The European Journal of Taxonomy (EJT) is a decade-old journal dedicated to the taxonomy of living and fossil eukaryotes. Launched in 2011, the EJT published exactly 900 articles (31 778 pages) from 2011 to 2021. The journal has been processed in its entirety by Plazi, liberating the data therein, depositing it into TreatmentBank, Biodiversity Literature Repository and disseminating it to partners, including the Global Biodiversity Information Facility (GBIF) using a combination of a highly automated workflow, quality control tools, and human curation. The dissemination of original research along with the ability to use and reuse data as freely as possible is the key to innovation, opening the corpus of known published biodiversity knowledge, and furthering advances in science. This paper aims to discuss the advantages and limitations of retro-conversion and to showcase the potential analyses of the data published in EJT and made findable, accessible, interoperable and reusable (FAIR) by Plazi. Among others, taxonomic and geographic coverage, geographical distribution of authors, citation of previous works and treatments, timespan between the publication and treatments with their cited works are discussed. Manually counted data were compared with the automated process, the latter being analysed and discussed. Creating FAIR data from a publication results in an average multiplication factor of 166 for additional access through the taxonomic treatments, figures and material citations citing the original publication in TreatmentBank, the Biodiversity Literature Repository and the Global Biodiversity Information Facility. Despite the advances in processing, liberating data remains cumbersome and has its limitations which lead us to conclude that the future of scientific publishing involves semantically enhanced publications.

2018 ◽  
Vol 2 ◽  
pp. e26328
Author(s):  
Boikhutso Lerato Rapalai

The Botswana National Museum is mandated to protect, preserve and promote Botswana’s cultural and natural heritage for sustainable utilization thereof by collecting, researching, conserving and exhibiting for public education and appreciation. The Entomology Section of the museum is aiming towards becoming the national center for entomology collections as well as contributing to the monitoring and enhancement of natural heritage sites in Botswana. The Botswana National Museum entomology collection was assembled over more than three decades by a succession of collectors, curators and technical officers. Specimens are carefully prepared and preserved, labelled with field data, sorted and safely stored. The collection is preserved as wet (ethanol preserved) or as dry pinned specimens in drawers. This collection is invaluable for reference, research, baseline data and educational purposes. As a way of mobilizing insect biodiversity data and making it available online for conservation efforts and decision making processes, in 2016 the Botswana National Museum collaborated with five other African states to implement the Biodiversity Information for Development (BID) and Global Biodiversity Information Facility (GBIF) funded African Insect Atlas’ Project (https://www.gbif.org/project/82632/african-insect-atlas). This collaborative project was initiated to move biodiversity knowledge out of select insect collections into the hands of a new generation of global biodiversity researchers interested in direct outcomes. To date, the Botswana National Museum has been instrumental through the efforts of this project in storing, maintaining and mobilizing insect digital collections and making the data available online through the GBIF Platform.


Author(s):  
Donald Hobern ◽  
Joseph Miller

There has been major progress over the last two decades in digitising historical knowledge of biodiversity and in making biodiversity data freely and openly accessible. Interlocking efforts bring together international partnerships and networks, national, regional and institutional projects and investments and countless individual contributors, spanning diverse biological and environmental research domains, government agencies and non-governmental organisations, citizen science and commercial enterprise. However, current efforts remain inefficient and inadequate to address the global need for accurate data on the world's species and on changing patterns and trends in biodiversity. Significant challenges include imbalances in regional engagement in biodiversity informatics activity, uneven progress in data mobilisation and sharing, the lack of stable persistent identifiers for data records, redundant and incompatible processes for cleaning and interpreting data and the absence of functional mechanisms for knowledgeable experts to curate and improve data. The first Global Biodiversity Informatics Conference (GBIC) in 2012 delivered the Global Biodiversity Informatics Outlook (GBIO, Hobern et al. 2012), an architectural vision for the major components of a distributed global infrastructure for biodiiversity information, but realigning the work of existing organisations and projects to achieve this vision remains challenging. Recognising the need for greater alignment between efforts at all scales, the Global Biodiversity Information Facility (GBIF) convened the second Global Biodiversity Informatics Conference (GBIC2) in July 2018 to propose a coordination mechanism for developing shared roadmaps for biodiversity informatics. GBIC2 attendees reached consensus on the need for a global alliance for biodiversity knowledge, learning from examples such as the Global Alliance for Genomics and Health (GA4GH) and the open software communities under the Apache Software Foundation. These initiatives provide models for multiple stakeholders with decentralised funding and independent governance to combine resources and develop sustainable solutions that address common needs. GBIF was asked to coordinate next steps following GBIC2, including publication of a paper, Connecting data and expertise: a new alliance for biodiversity knowledge (Hobern et al. 2019). The supplementary materials for the paper include PDF brochures explaining the concept in eleven languages. During 2019, GBIF is coordinating further consultations to establish an optimal model for the governance and operations of the alliance and to advance collaboration around some of the major building blocks of the GBIO. Collaboration at this scale, and across all aspects of biodiversity information, is essential for effective delivery of important information products such as the Essential Biodiversity Variables and the planned pan-European natural history collections infrastructure, DiSSCo. This presentation explains the goals for this alliance and updates on progress during 2019 in operationalising the concept.


2020 ◽  
Vol 8 ◽  
Author(s):  
Sonia Ferreira ◽  
Rui Andrade ◽  
Ana Gonçalves ◽  
Pedro Sousa ◽  
Joana Paupério ◽  
...  

The InBIO Barcoding Initiative (IBI) Diptera 01 dataset contains records of 203 specimens of Diptera. All specimens have been morphologically identified to species level, and belong to 154 species in total. The species represented in this dataset correspond to about 10% of continental Portugal dipteran species diversity. All specimens were collected north of the Tagus river in Portugal. Sampling took place from 2014 to 2018, and specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources. This dataset contributes to the knowledge on the DNA barcodes and distribution of 154 species of Diptera from Portugal and is the first of the planned IBI database public releases, which will make available genetic and distribution data for a series of taxa. All specimens have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).


Author(s):  
Amy Davis ◽  
Tim Adriaens ◽  
Rozemien De Troch ◽  
Peter Desmet ◽  
Quentin Groom ◽  
...  

To support invasive alien species risk assessments, the Tracking Invasive Alien Species (TrIAS) project has developed an automated, open, workflow incorporating state-of-the-art species distribution modelling practices to create risk maps using the open source language R. It is based on Global Biodiversity Information Facility (GBIF) data and openly published environmental data layers characterizing climate and land cover. Our workflow requires only a species name and generates an ensemble of machine-learning algorithms (Random Forest, Boosted Regression Trees, K-Nearest Neighbors and AdaBoost) stacked together as a meta-model to produce the final risk map at 1 km2 resolution (Fig. 1). Risk maps are generated automatically for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission scenarios and are accompanied by maps illustrating the confidence of each individual prediction across space, thus enabling the intuitive visualization and understanding of how the confidence of the model varies across space and scenario (Fig. 2). The effects of sampling bias are accounted for by providing options to: use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. The risk maps generated by our workflow are defensible and repeatable and provide forecasts of alien species distributions under further climate change scenarios. They can be used to support risk assessments and guide surveillance efforts on alien species in Europe. The detailied modeling framework and code are available on GitHub: https://github.com/trias-project.


2013 ◽  
Vol 64 (2) ◽  
Author(s):  
Shakina Mohd Talkah ◽  
Iylia Zulkiflee ◽  
Mohd Shahir Shamsir

Currently, all the information regarding ethnobotanical, phytochemical and pharmaceutical information of South East Asia are scattered over many different publications, depositories and databases using various digital and analogue formats. Although there are taxonomic databases of medicinal plants, they are not linked to phytochemical and pharmaceutical information which are often resides in scientific literature. We present Phyknome; an ethnobotanical and phytochemical database with more than 22,000 species of ethnoflora of Asia. The creation of this database will enable a biotechnology researcher to seek and identify ethnobotanical information based on a species’ scientific name, description and phytochemical information. It is constructed using a digitization pipeline that allow high throughput digitization of archival data, an automated dataminer to mine for pharmaceutical compounds information and an online database to integrated these information. The main functions include an automated taxonomy, bibliography and API interface with primary databases such as Global Biodiversity Information Facility (GBIF). We believe that Phyknome will contribute to the digital knowledge ecosystem to elevate access and provide tools for ethnobotanical research and contributes to the management, assessment and stewardship of biodiversity. The database is available at http://mapping.fbb.utm.my/phyknome/.


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