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Estoque RC. Some key considerations for implementing the nexus approach in biodiversity conservation research and practice. Sci Prog 2024; 107:368504231223023. [PMID: 38262423 PMCID: PMC10807393 DOI: 10.1177/00368504231223023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Affiliation(s)
- Ronald C. Estoque
- Center for Biodiversity and Climate Change, Forestry and Forest Products Research Institute, Tsukuba, Japan
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Lu YR, Fang CC, He SP. cnfishbase: A cyber Chinese fish database. Zool Res 2023; 44:950-953. [PMID: 37721104 PMCID: PMC10559084 DOI: 10.24272/j.issn.2095-8137.2023.087] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 05/17/2023] [Indexed: 09/19/2023] Open
Affiliation(s)
- Yong-Rui Lu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Cheng-Chi Fang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China
| | - Shun-Ping He
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China. E-mail:
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Abdelmageed N, Löffler F, Feddoul L, Algergawy A, Samuel S, Gaikwad J, Kazem A, König-Ries B. BiodivNERE: Gold standard corpora for named entity recognition and relation extraction in the biodiversity domain. Biodivers Data J 2022; 10:e89481. [PMID: 36761617 PMCID: PMC9836593 DOI: 10.3897/bdj.10.e89481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/07/2022] [Indexed: 11/12/2022] Open
Abstract
Background Biodiversity is the assortment of life on earth covering evolutionary, ecological, biological, and social forms. To preserve life in all its variety and richness, it is imperative to monitor the current state of biodiversity and its change over time and to understand the forces driving it. This need has resulted in numerous works being published in this field. With this, a large amount of textual data (publications) and metadata (e.g. dataset description) has been generated. To support the management and analysis of these data, two techniques from computer science are of interest, namely Named Entity Recognition (NER) and Relation Extraction (RE). While the former enables better content discovery and understanding, the latter fosters the analysis by detecting connections between entities and, thus, allows us to draw conclusions and answer relevant domain-specific questions. To automatically predict entities and their relations, machine/deep learning techniques could be used. The training and evaluation of those techniques require labelled corpora. New information In this paper, we present two gold-standard corpora for Named Entity Recognition (NER) and Relation Extraction (RE) generated from biodiversity datasets metadata and abstracts that can be used as evaluation benchmarks for the development of new computer-supported tools that require machine learning or deep learning techniques. These corpora are manually labelled and verified by biodiversity experts. In addition, we explain the detailed steps of constructing these datasets. Moreover, we demonstrate the underlying ontology for the classes and relations used to annotate such corpora.
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Affiliation(s)
- Nora Abdelmageed
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany,Michael-Stifel-Center for Data-Driven and Simulation Science, Jena, GermanyMichael-Stifel-Center for Data-Driven and Simulation ScienceJenaGermany
| | - Felicitas Löffler
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany
| | - Leila Feddoul
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany
| | - Alsayed Algergawy
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany
| | - Sheeba Samuel
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany,Michael-Stifel-Center for Data-Driven and Simulation Science, Jena, GermanyMichael-Stifel-Center for Data-Driven and Simulation ScienceJenaGermany
| | - Jitendra Gaikwad
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany
| | - Anahita Kazem
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany,German Center for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, GermanyGerman Center for Integrative Biodiversity Research (iDiv)Halle-Jena-LeipzigGermany
| | - Birgitta König-Ries
- Heinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, GermanyHeinz Nixdorf Chair for Distributed Information Systems, Department of Mathematics and Computer Science, Friedrich Schiller University JenaJenaGermany,Michael-Stifel-Center for Data-Driven and Simulation Science, Jena, GermanyMichael-Stifel-Center for Data-Driven and Simulation ScienceJenaGermany,German Center for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, GermanyGerman Center for Integrative Biodiversity Research (iDiv)Halle-Jena-LeipzigGermany
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SMEP (Science Museum Exhibition Platform) for Sharing and exchange system of natural history collection. JOURNAL OF ASIA-PACIFIC BIODIVERSITY 2021. [DOI: 10.1016/j.japb.2021.07.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Assis J, Fragkopoulou E, Frade D, Neiva J, Oliveira A, Abecasis D, Faugeron S, Serrão EA. A fine-tuned global distribution dataset of marine forests. Sci Data 2020; 7:119. [PMID: 32286314 PMCID: PMC7156423 DOI: 10.1038/s41597-020-0459-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 03/19/2020] [Indexed: 11/08/2022] Open
Abstract
Species distribution records are a prerequisite to follow climate-induced range shifts across space and time. However, synthesizing information from various sources such as peer-reviewed literature, herbaria, digital repositories and citizen science initiatives is not only costly and time consuming, but also challenging, as data may contain thematic and taxonomic errors and generally lack standardized formats. We address this gap for important marine ecosystem-structuring species of large brown algae and seagrasses. We gathered distribution records from various sources and provide a fine-tuned dataset with ~2.8 million dereplicated records, taxonomically standardized for 682 species, and considering important physiological and biogeographical traits. Specifically, a flagging system was implemented to signal potentially incorrect records reported on land, in regions with limiting light conditions for photosynthesis, and outside the known distribution of species, as inferred from the most recent published literature. We document the procedure and provide a dataset in tabular format based on Darwin Core Standard (DwC), alongside with a set of functions in R language for data management and visualization.
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Affiliation(s)
- Jorge Assis
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal.
| | - Eliza Fragkopoulou
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
| | - Duarte Frade
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
| | - João Neiva
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
| | - André Oliveira
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
| | - David Abecasis
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
| | - Sylvain Faugeron
- Centro de Conservación Marina and CeBiB, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile
- UMI 3614 Evolutionary Biology and Ecology of Algae, CNRS, Sorbonne Université, Pontificia Universidad Católica de Chile, Universidad Austral de Chile, Station Biologique, Roscoff, France
| | - Ester A Serrão
- CCMAR - Centre of Marine Sciences, University of Algarve, 8005-139, Faro, Portugal
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da Silva TM, Dos Santos JC, Ferreira VAV, Ramos LADC, Wosiacki WB, de Sousa MPA. Data from the ichthyological collection of the Museu Paraense Emílio Goeldi. Zookeys 2017:89-99. [PMID: 29114167 PMCID: PMC5672575 DOI: 10.3897/zookeys.687.11233] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Accepted: 06/26/2017] [Indexed: 11/30/2022] Open
Abstract
This dataset contains information on the occurrence of Neotropical fishes (Actinopterygii, Chondrichthyes, Sarcopterygii) collected in South America, mostly from the Brazilian Amazon. The ichthyology collections of the Museu Paraense Emílio Goeldi (MPEG: http://www.museu-goeldi.br/) include specimens collected between 1900 and 2014. The dataset is now available for public consultation on the Global Biodiversity Information Facility portal (http://www.gbif.org/dataset/b0059a3a-5cab-4a08-8d14-d92c23378e43), and through Sistema de Informação sobre a Biodiversidade Brasileira (http://gbif.sibbr.gov.br/explorador/pt/recurso/62).
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Nelson G, Sweeney P, Wallace LE, Rabeler RK, Allard D, Brown H, Carter JR, Denslow MW, Ellwood ER, Germain-Aubrey CC, Gilbert E, Gillespie E, Goertzen LR, Legler B, Marchant DB, Marsico TD, Morris AB, Murrell Z, Nazaire M, Neefus C, Oberreiter S, Paul D, Ruhfel BR, Sasek T, Shaw J, Soltis PS, Watson K, Weeks A, Mast AR. Digitization workflows for flat sheets and packets of plants, algae, and fungi. APPLICATIONS IN PLANT SCIENCES 2015; 3:apps1500065. [PMID: 26421256 PMCID: PMC4578381 DOI: 10.3732/apps.1500065] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Accepted: 07/30/2015] [Indexed: 05/25/2023]
Abstract
Effective workflows are essential components in the digitization of biodiversity specimen collections. To date, no comprehensive, community-vetted workflows have been published for digitizing flat sheets and packets of plants, algae, and fungi, even though latest estimates suggest that only 33% of herbarium specimens have been digitally transcribed, 54% of herbaria use a specimen database, and 24% are imaging specimens. In 2012, iDigBio, the U.S. National Science Foundation's (NSF) coordinating center and national resource for the digitization of public, nonfederal U.S. collections, launched several working groups to address this deficiency. Here, we report the development of 14 workflow modules with 7-36 tasks each. These workflows represent the combined work of approximately 35 curators, directors, and collections managers representing more than 30 herbaria, including 15 NSF-supported plant-related Thematic Collections Networks and collaboratives. The workflows are provided for download as Portable Document Format (PDF) and Microsoft Word files. Customization of these workflows for specific institutional implementation is encouraged.
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Affiliation(s)
- Gil Nelson
- Integrated Digitized Biocollections (iDigBio), Florida State University, Tallahassee, Florida 32306-2100 USA
| | - Patrick Sweeney
- Peabody Museum of Natural History, Yale University, New Haven, Connecticut, USA
| | - Lisa E. Wallace
- Department of Biological Sciences, Mississippi State University, Mississippi State, Mississippi, USA
| | | | - Dorothy Allard
- Department of Plant Biology, University of Vermont, Burlington, Vermont, USA
| | - Herrick Brown
- Department of Biological Sciences, University of South Carolina, Columbia, South Carolina, USA
| | - J. Richard Carter
- Biology Department, Valdosta State University, Valdosta, Georgia, USA
| | - Michael W. Denslow
- Department of Biology, Appalachian State University, Boone, North Carolina, USA
| | - Elizabeth R. Ellwood
- Department of Biological Science, Florida State University, Tallahassee, Florida, USA
| | | | - Ed Gilbert
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Emily Gillespie
- Department of Biological Sciences, Marshall University, Huntington, West Virginia, USA
| | - Leslie R. Goertzen
- Department of Biological Sciences, Auburn University, Auburn, Alabama, USA
| | - Ben Legler
- Burke Museum, University of Washington, Seattle, Washington, USA
| | - D. Blaine Marchant
- Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA
- Department of Biology, University of Florida, Gainesville, Florida, USA
| | - Travis D. Marsico
- Department of Biological Sciences, Arkansas State University, Jonesboro, Arkansas, USA
| | - Ashley B. Morris
- Department of Biology, Middle Tennessee State University, Murfreesboro, Tennessee, USA
| | - Zack Murrell
- Department of Biology, Appalachian State University, Boone, North Carolina, USA
| | - Mare Nazaire
- Rancho Santa Ana Botanic Garden, Claremont, California, USA
| | - Chris Neefus
- Department of Biological Sciences, University of New Hampshire, Durham, New Hampshire, USA
| | - Shanna Oberreiter
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Deborah Paul
- Integrated Digitized Biocollections (iDigBio), Florida State University, Tallahassee, Florida 32306-2100 USA
| | - Brad R. Ruhfel
- Department of Biological Sciences, Eastern Kentucky University, Richmond, Kentucky, USA
| | - Thomas Sasek
- Department of Biology, University of Louisiana at Monroe, Monroe, Louisiana, USA
| | - Joey Shaw
- Biological and Environmental Sciences, University of Tennessee, Chattanooga, Tennessee, USA
| | - Pamela S. Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, Florida, USA
| | - Kimberly Watson
- William and Lynda Steere Herbarium, The New York Botanical Garden, Bronx, New York, USA
| | - Andrea Weeks
- Department of Biology and the Ted R. Bradley Herbarium, George Mason University, Fairfax, Virginia, USA
| | - Austin R. Mast
- Department of Biological Science, Florida State University, Tallahassee, Florida, USA
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Ningthoujam SS, Talukdar AD, Potsangbam KS, Choudhury MD. Challenges in developing medicinal plant databases for sharing ethnopharmacological knowledge. JOURNAL OF ETHNOPHARMACOLOGY 2012; 141:9-32. [PMID: 22401841 DOI: 10.1016/j.jep.2012.02.042] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Revised: 02/19/2012] [Accepted: 02/25/2012] [Indexed: 05/31/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Major research contributions in ethnopharmacology have generated vast amount of data associated with medicinal plants. Computerized databases facilitate data management and analysis making coherent information available to researchers, planners and other users. Web-based databases also facilitate knowledge transmission and feed the circle of information exchange between the ethnopharmacological studies and public audience. However, despite the development of many medicinal plant databases, a lack of uniformity is still discernible. Therefore, it calls for defining a common standard to achieve the common objectives of ethnopharmacology. AIM OF THE STUDY The aim of the study is to review the diversity of approaches in storing ethnopharmacological information in databases and to provide some minimal standards for these databases. MATERIALS AND METHODS Survey for articles on medicinal plant databases was done on the Internet by using selective keywords. Grey literatures and printed materials were also searched for information. Listed resources were critically analyzed for their approaches in content type, focus area and software technology. RESULTS Necessity for rapid incorporation of traditional knowledge by compiling primary data has been felt. While citation collection is common approach for information compilation, it could not fully assimilate local literatures which reflect traditional knowledge. Need for defining standards for systematic evaluation, checking quality and authenticity of the data is felt. Databases focussing on thematic areas, viz., traditional medicine system, regional aspect, disease and phytochemical information are analyzed. Issues pertaining to data standard, data linking and unique identification need to be addressed in addition to general issues like lack of update and sustainability. In the background of the present study, suggestions have been made on some minimum standards for development of medicinal plant database. CONCLUSION In spite of variations in approaches, existence of many overlapping features indicates redundancy of resources and efforts. As the development of global data in a single database may not be possible in view of the culture-specific differences, efforts can be given to specific regional areas. Existing scenario calls for collaborative approach for defining a common standard in medicinal plant database for knowledge sharing and scientific advancement.
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