scholarly journals BioDATA - Biodiversity Data for Internationalisation in Higher Education

2019 ◽  
Vol 5 ◽  
Author(s):  
Oleh Prylutskyi ◽  
Armine Abrahamyan ◽  
Nina Voronova ◽  
Tatevik Aloyan ◽  
Oleg Borodin ◽  
...  

BioDATA is an international project on developing skills in biodiversity data management and data publishing. Between 2018 and 2021, undergraduate and postgraduate students from Armenia, Belarus, Tajikistan, and Ukraine, have an opportunity to take part in the intensive courses to become certified professionals in biodiversity data management. They will gain practical skills and obtain appropriate knowledge on: international data standards (Darwin Core); data cleaning software, data publishing software such as the Integrated Publishing Toolkit (IPT), and preparation of data papers. Working with databases, creating datasets, managing data for statistical analyses and publishing research papers are essential for the everyday tasks of a modern biologist. At the same time, these skills are rarely taught in higher education. Most of the contemporary professionals in biodiversity have to gain these skills independently, through colleagues, or through supervision. In addition, all the participants familiarize themselves with one of the important international research data infrastructures such as the Global Biodiversity Information Facility (GBIF). The project is coordinated by the University of Oslo (Norway) and supported by the Global Biodiversity Information Facility (GBIF). The project is funded by the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education (DIKU).

Author(s):  
Dag Endresen ◽  
Armine Abrahamyan ◽  
Akobir Mirzorakhimov ◽  
Andreas Melikyan ◽  
Brecht Verstraete ◽  
...  

BioDATA (Biodiversity Data for Internationalisation in Higher Education) is an international project to develop and deliver biodiversity data training for undergraduate and postgraduate students from Armenia, Belarus, Tajikistan, and Ukraine. By training early career (student) biodiversity scholars, we aim at turning the current academic and education biodiversity landscape into a more open-data-friendly one. Professional practitioners (researchers, museum curators, and collection managers involved in data publishing) from each country were also invited to join the project as assistant teachers (mentors). The project is developed by the Research School in Biosystematics - ForBio and the Norwegian GBIF-node, both at the Natural History Museum of the University of Oslo in collaboration with the Secretariat of the Global Biodiversity Information Facility (GBIF) and partners from each of the target countries. The teaching material is based on the GBIF curriculum for data mobilization and all students will have the opportunity to gain the respective GBIF certification. All materials are made freely available for reuse and even in this very early phase of the project, we have already seen the first successful reuse of teaching materials among the project partners. The first BioDATA training event was organized in Minsk (Belarus) in February 2019 with the objective to train a minimum of four mentors from each target country. The mentor-trainees from this event will help us to teach the course to students in their home country together with teachers from the project team. BioDATA mentors will have the opportunity to gain GBIF certification as expert mentors which will open opportunities to contribute to future training events in the larger GBIF network. The BioDATA training events for the students will take place in Dushanbe (Tajikistan) in June 2019, in Minsk (Belarus) in November 2019, in Yerevan (Armenia) in April 2020, and in Kiev (Ukraine) in October 2020. Students from each country are invited to express their interest to participate by contacting their national project partner. We will close the project with a final symposium at the University of Oslo in March 2021. The project is funded by the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education (DIKU).


Author(s):  
Edward Gilbert ◽  
Corinna Gries ◽  
Nico Franz ◽  
Landrum Leslie R. ◽  
Thomas H. Nash III

The SEINet Portal Network has a complex social and development history spanning nearly two decades. Initially established as a basic online search engine for a select handful of biological collections curated within the southwestern United States, SEINet has since matured into a biodiversity data network incorporating more than 330 institutions and 1,900 individual data contributors. Participating institutions manage and publish over 14 million specimen records, 215,000 observations, and 8 million images. Approximately 70% of the collections make use of the data portal as their primary "live" specimen management platform. The SEINet interface now supports 13 regional data portals distributed across the United States and northern Mexico (http://symbiota.org/docs/seinet/). Through many collaborative efforts, it has matured into a tool for biodiversity data exploration, which includes species inventories, interactive identification keys, specimen and field images, taxonomic information, species distribution maps, and taxonomic descriptions. SEINet’s initial developmental goals were to construct a read-only interface that integrated specimen records harvested from a handful of distributed natural history databases. Intermittent network conductivity and inconsistent data exchange protocols frequently restricted data persistence. National funding opportunities supported a complete redesign towards the development of a centralized data cache model with periodic "snapshot" updates from original data sources. A service-based management infrastructure was integrated into the interface to mobilize small- to medium-sized collections (<1 million specimen records) that commonly lack consistent infrastructure and technical expertise to maintain a standard compliant specimen database. These developments were the precursors to the Symbiota software project (Gries et al. 2014). Through further development of Symbiota, SEINet transformed into a robust specimen management system specifically geared toward specimen digitization with features including data entry from label images, harvesting data from specimen duplicates, batch georeferencing, data validation and cleaning, generating progress reports, and additional tools to improve the efficiency of the digitization process. The central developmental paradigm focused on data mobilization through the production of: a versatile import module capable of ingesting a diverse range of data structures, a robust toolkit to assist in digitizing and managing specimen data and images, and a Darwin Core Archive (DwC-A) compliant data publishing and export toolkit to facilitate data distribution to global aggregators such as Global Biodiversity Information Facility (GBIF) and iDigBio. a versatile import module capable of ingesting a diverse range of data structures, a robust toolkit to assist in digitizing and managing specimen data and images, and a Darwin Core Archive (DwC-A) compliant data publishing and export toolkit to facilitate data distribution to global aggregators such as Global Biodiversity Information Facility (GBIF) and iDigBio. User interfaces consist of a decentralized network of regional data portals, all connecting to a centralized shared data source. Each of the 13 data portals are configured to present a regional perspective specifically tailored to represent the needs of the local research community. This infrastructure has supported the formation of regional consortia, who provide network support to aid local institutions in digitizing and publishing their collections within the network. The community-based infrastructure creates a sense of ownership – perhaps even good-natured competition – by the data providers and provides extra incentive to improve data quality and expand the network. Certain areas of development remain challenging in spite of the project's overall success. For instance, data managers continuously struggle to maintain a current local taxonomic thesaurus used for name validation, data cleaning, and to resolve taxonomic discrepancies commonly encountered when integrating collection datasets. We will discuss the successes and challenges associated with the long-term sustainability model and explore potential future paths for SEINet that support the long-term goal of maintaining a data provider that is in full compliance with the FAIR use principles of making the datasets findable, accessible, interoperable, and reusable (Wilkinson et al. 2016).


Author(s):  
Dmitry Schigel ◽  
Anders Andersson ◽  
Andrew Bissett ◽  
Anders Finstad ◽  
Frode Fossøy ◽  
...  

Most users will foresee the use of genetic sequences in the context of molecular ecology or phylogenetic research, however, a sequence with coordinates and a timestamp is a valuable biodiversity occurrence that is useful in a much broader context than its original purpose. To uncover this potential, sequence-derived data need to become findable, accessible, interoperable, and reusable through generalist biodiversity data platforms. Stimulated by the Biodiversity_Next discussions in 2019, we have worked for about 10 months to put together practical data mapping and data publishing experiences in Norway, Australia, Sweden, and Denmark, as well as in the UNITE and the GBIF (Global Biodiversity Information Facility) networks. The resulting guide was put together to provide practical instruction for mapping sequence-derived data. Biodiversity data communities remain dominated by the macroscopic, easily detectable, morphologically identifiable species. This is not only true for citizen science and other forms of biodiversity popularization, but is also visible in the university and museum department structures, financial resource allocations, biodiversity legislation, and policy design. Recent decades of molecular advances have increased the power of genetic methods for detecting, describing, and documenting global biodiversity. We have yet to see the wide shift of data generating efforts from the traditional taxonomic foci of biodiversity assesments to the more balanced and inclusive systems focusing on all functionally important taxa and environments. These include soil, limnic and marine environments, decomposing plants and deadwood, and all life therein. Environmental DNA data enable recording of present and past presence of micro- and macroscopic organisms with minimal effort and by non-invasive methods. The apparent ease of these methods requires a cautious approach to the resulting data and their interpretation. It remains important to define and agree on the organism recording and reporting routines for genetic data. DNA data represent a major addition to the many ways in which GBIF and other biodiversity data platforms index the living world. Our guide is resting on the shoulders of those who have been developing and improving MIxS (Minimum Information about any (x) Sequence), GGBN (Global Genome Biodiversity Network) and other data standards. The added value of publishing sequence-derived data through non-genetic biodiversity discovery platforms relates to spatio-temporal occurrences and sequence-based names. Reporting sequence-derived occurrences in an open and reproducible way has a wide range of benefits: notably, it increases citability, highlights the taxa concerned in the context of biological conservation, and contributes to taxonomic and ecological knowledge.


2021 ◽  
Vol 9 ◽  
Author(s):  
Domingos Sandramo ◽  
Enrico Nicosia ◽  
Silvio Cianciullo ◽  
Bernardo Muatinte ◽  
Almeida Guissamulo

The collections of the Natural History Museum of Maputo have a crucial role in the safeguarding of Mozambique's biodiversity, representing an important repository of data and materials regarding the natural heritage of the country. In this paper, a dataset is described, based on the Museum’s Entomological Collection recording 409 species belonging to seven orders and 48 families. Each specimen’s available data, such as geographical coordinates and taxonomic information, have been digitised to build the dataset. The specimens included in the dataset were obtained between 1914–2018 by collectors and researchers from the Natural History Museum of Maputo (once known as “Museu Alváro de Castro”) in all the country’s provinces, with the exception of Cabo Delgado Province. This paper adds data to the Biodiversity Network of Mozambique and the Global Biodiversity Information Facility, within the objectives of the SECOSUD II Project and the Biodiversity Information for Development Programme. The aforementioned insect dataset is available on the GBIF Engine data portal (https://doi.org/10.15468/j8ikhb). Data were also shared on the Mozambican national portal of biodiversity data BioNoMo (https://bionomo.openscidata.org), developed by SECOSUD II Project.


2019 ◽  
Vol 7 ◽  
Author(s):  
Valéria da Silva ◽  
Manoel Aguiar-Neto ◽  
Dan Teixeira ◽  
Cleverson Santos ◽  
Marcos de Sousa ◽  
...  

We present a dataset with information from the Opiliones collection of the Museu Paraense Emílio Goeldi, Northern Brazil. This collection currently has 6,400 specimens distributed in 13 families, 30 genera and 32 species and holotypes of four species: Imeri ajuba Coronato-Ribeiro, Pinto-da-Rocha & Rheims, 2013, Phareicranaus patauateua Pinto-da-Rocha & Bonaldo, 2011, Protimesius trocaraincola Pinto-da-Rocha, 1997 and Sickesia tremembe Pinto-da-Rocha & Carvalho, 2009. The material of the collection is exclusive from Brazil, mostly from the Amazon Region. The dataset is now available for public consultation on the Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr) (https://ipt.sibbr.gov.br/goeldi/resource?r=museuparaenseemiliogoeldi-collection-aracnologiaopiliones). SiBBr is the Brazilian Biodiversity Information System, an initiative of the government and the Brazilian node of the Global Biodiversity Information Facility (GBIF), which aims to consolidate and make primary biodiversity data available on a platform (Dias et al. 2017). Harvestmen or Opiliones constitute the third largest arachnid order, with approximately 6,500 described species. Brazil is the holder of the greatest diversity in the world, with more than 1,000 described species, 95% (960 species) of which are endemic to the country. Of these, 32 species were identified and deposited in the collection of the Museu Paraense Emílio Goeldi.


2018 ◽  
Vol 2 ◽  
pp. e25488
Author(s):  
Anne-Sophie Archambeau ◽  
Fabien Cavière ◽  
Kourouma Koura ◽  
Marie-Elise Lecoq ◽  
Sophie Pamerlon ◽  
...  

Atlas of Living Australia (ALA) (https://www.ala.org.au/) is the Global Biodiversity Information Facility (GBIF) node of Australia. They developed an open and free platform for sharing and exploring biodiversity data. All the modules are publicly available for reuse and customization on their GitHub account (https://github.com/AtlasOfLivingAustralia). GBIF Benin, hosted at the University of Abomey-Calavi, has published more than 338 000 occurrence records from 87 datasets and 2 checklists. Through the GBIF Capacity Enhancement Support Programme (https://www.gbif.org/programme/82219/capacity-enhancement-support-programme), GBIF Benin, with the help of GBIF France, is in the process of deploying the Beninese data portal using the GBIF France back-end architecture. GBIF Benin is the first African country to implement this module of the ALA infrastructure. In this presentation, we will show you an overview of the registry and the occurrence search engine using the Beninese data portal. We will begin with the administration interface and how to manage metadata, then we will continue with the user interface of the registry and how you can find Beninese occurrences through the hub.


2018 ◽  
Vol 2 ◽  
pp. e25486
Author(s):  
Nick dos Remedios ◽  
Marie-Elise Lecoq ◽  
David Martin ◽  
Sophia Ratcliffe

Atlas of Living Australia (ALA) (https://www.ala.org.au/) is the Global Biodiversity Information Facility (GBIF) node of Australia. Since 2010, they have developed and improved a platform for sharing and exploring biodiversity information. All the modules are publicly available for reuse and customization on their GitHub account (https://github.com/AtlasOfLivingAustralia). The National Biodiversity Network, a registered charity, is the UK GBIF node and has been sharing biodiversity data since 2000. They published more than 79 million occurrences from 818 datasets. In 2016, they launched the NBN Atlas Scotland (https://scotland.nbnatlas.org/) based on the Atlas of Living Australia infrastructure. Since then, they released the NBN Atlas (https://nbnatlas.org/), the NBN Atlas Wales (https://wales.nbnatlas.org/) and soon the NBN Atlas Isle of Man. In addition to the occurrence/species search engine and the metadata registry, they put in place several tools that help users to work with data published in the network: the spatial portal and "explore your region" module. Both elements are based on Atlas of Living Australia developments. Because the Atlas of Living Australia platform is really powerful an reusable, we want to show you these two applications used to make geographical analyses. In order to perform this, we will present you the specificities of each component by giving examples of some functionalities.


2021 ◽  
Vol 118 (6) ◽  
pp. e2018093118
Author(s):  
J. Mason Heberling ◽  
Joseph T. Miller ◽  
Daniel Noesgaard ◽  
Scott B. Weingart ◽  
Dmitry Schigel

The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world’s largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.


2020 ◽  
Vol 15 (4) ◽  
pp. 411-437 ◽  
Author(s):  
Marcos Zárate ◽  
Germán Braun ◽  
Pablo Fillottrani ◽  
Claudio Delrieux ◽  
Mirtha Lewis

Great progress to digitize the world’s available Biodiversity and Biogeography data have been made recently, but managing data from many different providers and research domains still remains a challenge. A review of the current landscape of metadata standards and ontologies in Biodiversity sciences suggests that existing standards, such as the Darwin Core terminology, are inadequate for describing Biodiversity data in a semantically meaningful and computationally useful way. As a contribution to fill this gap, we present an ontology-based system, called BiGe-Onto, designed to manage data together from Biodiversity and Biogeography. As data sources, we use two internationally recognized repositories: the Global Biodiversity Information Facility (GBIF) and the Ocean Biogeographic Information System (OBIS). BiGe-Onto system is composed of (i) BiGe-Onto Architecture (ii) a conceptual model called BiGe-Onto specified in OntoUML, (iii) an operational version of BiGe-Onto encoded in OWL 2, and (iv) an integrated dataset for its exploitation through a SPARQL endpoint. We will show use cases that allow researchers to answer questions that manage information from both domains.


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