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Green TA, Hutchings PA, Scarff FR, Tweedley JR, Calver MC. Research publications of Australia's natural history museums, 1981-2020: Enduring relevance in a changing world. PLoS One 2023; 18:e0287659. [PMID: 37352318 PMCID: PMC10289469 DOI: 10.1371/journal.pone.0287659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 06/12/2023] [Indexed: 06/25/2023] Open
Abstract
As a case study of the responses of natural history museums to changing scientific and funding environments, we analysed research publications of Australia's Natural History Museums (ANHMs) 1981-2020. Using Scopus, 9,923 relevant documents 1981-2020 were identified, mainly research papers but with a growing proportion of reviews. The number of documents published increased over tenfold from 39 (1981) to 553 (2020), likely driven by collaborations (rising from 28.5% of documents 1981-1985 to 87.2% of documents 2016-2020), contributions from retired staff, and volunteer support. The mean length of documents (pages) ranged from a low of 15.3 in 2001-2005 to a high of 17.4 in 1991-1995, but this statistically significant result was trivial in practical terms. The sources (i.e., journals, book titles, conference proceedings) in which ANHM authors published changed over time, with growing proportions of publications in journals covering molecular ecology/phylogenetics and biological conservation. We identified the major areas of study canvassed within the corpus of publications by developing structural topic models based on patterns of word use in document titles, abstracts and keyword lists. The topics discovered included study subjects traditional for natural history museums (new taxa, phylogeny, systematics, animal morphology, palaeontology, minerals), new directions (molecular genetics, ecology, biological conservation) and marine biology (probably reflecting Australia's large coastline). Most citations came from Australia, USA and UK, although in 2016-2020 only 27.9% of citing documents included an Australian author. Growth in numbers of documents and collaborations, as well as use of documents internationally over a period of great change in scientific and funding environments, indicate an enduring legacy of ANHM research, grounded on the intrinsic value of the collections.
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Affiliation(s)
- Tayla A. Green
- Environmental and Conservation Sciences, Murdoch University, Murdoch, Western Australia, Australia
| | - Pat A. Hutchings
- Australian Museum Research Institute, Australian Museum, Sydney, NSW, Australia
- Department of Biological Sciences, Macquarie University, North Ryde, Australia
| | - Fiona R. Scarff
- Environmental and Conservation Sciences, Murdoch University, Murdoch, Western Australia, Australia
| | - James R. Tweedley
- Environmental and Conservation Sciences, Murdoch University, Murdoch, Western Australia, Australia
| | - Michael C. Calver
- Environmental and Conservation Sciences, Murdoch University, Murdoch, Western Australia, Australia
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2
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Research on the Development of Digital Creative Sports Industry Based on Deep Learning. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:7760263. [PMID: 35140778 PMCID: PMC8818437 DOI: 10.1155/2022/7760263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 11/26/2021] [Accepted: 12/09/2021] [Indexed: 11/24/2022]
Abstract
The core of the digital entrepreneurial sports culture creative industry lies in innovation, which emphasizes the new impetus brought by the digital entrepreneurial sports culture to the social economy. The digital entrepreneurial sports cultural creative industry is rooted in the cultural creative industry. The digital entrepreneurial sports cultural creative industry is also an important part of the sports industry, and its development highly depends on the development of the sports industry. The digital entrepreneurial sports cultural creative industry has the characteristics of both the sports industry and the cultural creative industry. This paper uses the deep learning technology to study the development of the digital creative sports industry and build an intelligent model. Moreover, this paper assigns weights to the input multidimensional features, extracts the most relevant data features, and analyzes the performance of the proposed model through simulation experiments. From the experimental analysis results, we can see that the model proposed in this paper has certain practicality.
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3
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Spaulding SA, Potapova MG, Bishop IW, Lee SS, Gasperak TS, Jovanoska E, Furey PC, Edlund MB. Diatoms.org: supporting taxonomists, connecting communities. DIATOM RESEARCH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR DIATOM RESEARCH 2022; 36:291-304. [PMID: 35958044 PMCID: PMC9359083 DOI: 10.1080/0269249x.2021.2006790] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 09/22/2021] [Indexed: 05/23/2023]
Abstract
Consistent identification of diatoms is a prerequisite for studying their ecology, biogeography, and successful application as environmental indicators. However, taxonomic consistency among observers has been difficult to achieve, because taxonomic information is scattered across numerous literature sources, presenting challenges to the diatomist. First, literature is often inaccessible because of cost, or its location in journals that are not widely circulated. Second, taxonomic revisions of diatoms are taking place faster than floras can be updated. Finally, taxonomic information is often contradictory across literature sources. These issues can be addressed by developing a content creation community dedicated to making taxonomic, ecological, and image-based data freely available for diatom researchers. Diatoms.org represents such a content curation community, providing open, online access to a vast amount of recent and historical information on North American diatom taxonomy and ecology. The content curation community aggregates existing taxonomic information, creates new content, and provides feedback in the form of corrections and notice of literature with nomenclatural changes. The website not only addresses the needs of experienced diatom scientists for consistent identification, but is also designed to meet users at their level of expertise, including engaging the lay public in the importance of diatom science. The website now contains over 1000 species pages contributed by over 100 content contributors, from students to established scientists. The project began with the intent to provide accurate information on diatom identification, ecology, and distribution using an approach that incorporates engaging design, user feedback, and advanced data access technology. In retrospect, the project that began as an "extended electronic book" has emerged not only as a means to support taxonomists, but for practitioners to communicate and collaborate, expanding the size of and benefits to the content curation community. In this paper, we outline the development of diatoms.org, document key elements of the project, examine ongoing challenges, and consider the unexpected emergent properties, including the value of diatoms.org as a source of data. Ultimately, if the field of diatom taxonomy, ecology, and biodiversity is to be relevant, a new generation of taxonomists needs to be trained and employed using new tools. We propose that diatoms.org is in a key position to serve as a hub of training and continuity for the study of diatom biodiversity and aquatic conditions.
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Affiliation(s)
- Sarah A Spaulding
- U.S. Geological Survey/INSTAAR, 4001 Discovery Drive, Boulder, CO 80309
| | - Marina G Potapova
- The Academy of Natural Sciences of Drexel University, 1900 Benjamin Franklin Parkway, Philadelphia PA 19103
| | - Ian W Bishop
- Graduate School of Oceanography, University of Rhode Island, 215 S. Ferry Rd, Narragansett, RI 02882
| | - Sylvia S Lee
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, 1200 Pennsylvania Ave. NW, Mail code 8623-P, Washington, D.C. 20460
| | | | - Elena Jovanoska
- Department of Palaeoanthropology, Senckenberg Research Institute, Senckenberganlage 25, 60325, Frankfurt am Main, Germany
| | - Paula C Furey
- Department of Biology, St. Catherine University, 2004 Randolph Ave., St. Paul, MN 55105
| | - Mark B Edlund
- St. Croix Watershed Res. Station, Science Museum of Minnesota, Marine on St. Croix MN 55047
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Owen D, Groom Q, Hardisty A, Leegwater T, Livermore L, van Walsum M, Wijkamp N, Spasić I. Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections. RESEARCH IDEAS AND OUTCOMES 2020. [DOI: 10.3897/rio.6.e58030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
We describe an effective approach to automated text digitisation with respect to natural history specimen labels. These labels contain much useful data about the specimen including its collector, country of origin, and collection date. Our approach to automatically extracting these data takes the form of a pipeline. Recommendations are made for the pipeline's component parts based on state-of-the-art technologies.
Optical Character Recognition (OCR) can be used to digitise text on images of specimens. However, recognising text quickly and accurately from these images can be a challenge for OCR. We show that OCR performance can be improved by prior segmentation of specimen images into their component parts. This ensures that only text-bearing labels are submitted for OCR processing as opposed to whole specimen images, which inevitably contain non-textual information that may lead to false positive readings. In our testing Tesseract OCR version 4.0.0 offers promising text recognition accuracy with segmented images.
Not all the text on specimen labels is printed. Handwritten text varies much more and does not conform to standard shapes and sizes of individual characters, which poses an additional challenge for OCR. Recently, deep learning has allowed for significant advances in this area. Google's Cloud Vision, which is based on deep learning, is trained on large-scale datasets, and is shown to be quite adept at this task. This may take us some way towards negating the need for humans to routinely transcribe handwritten text.
Determining the countries and collectors of specimens has been the goal of previous automated text digitisation research activities. Our approach also focuses on these two pieces of information. An area of Natural Language Processing (NLP) known as Named Entity Recognition (NER) has matured enough to semi-automate this task. Our experiments demonstrated that existing approaches can accurately recognise location and person names within the text extracted from segmented images via Tesseract version 4.0.0.
We have highlighted the main recommendations for potential pipeline components. The paper also provides guidance on selecting appropriate software solutions. These include automatic language identification, terminology extraction, and integrating all pipeline components into a scientific workflow to automate the overall digitisation process.
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Owen D, Livermore L, Groom Q, Hardisty A, Leegwater T, van Walsum M, Wijkamp N, Spasić I. Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections. RESEARCH IDEAS AND OUTCOMES 2020. [DOI: 10.3897/rio.6.e55789] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
We describe an effective approach to automated text digitisation with respect to natural history specimen labels. These labels contain much useful data about the specimen including its collector, country of origin, and collection date. Our approach to automatically extracting these data takes the form of a pipeline. Recommendations are made for the pipeline's component parts based on some of the state-of-the-art technologies.
Optical Character Recognition (OCR) can be used to digitise text on images of specimens. However, recognising text quickly and accurately from these images can be a challenge for OCR. We show that OCR performance can be improved by prior segmentation of specimen images into their component parts. This ensures that only text-bearing labels are submitted for OCR processing as opposed to whole specimen images, which inevitably contain non-textual information that may lead to false positive readings. In our testing Tesseract OCR version 4.0.0 offers promising text recognition accuracy with segmented images.
Not all the text on specimen labels is printed. Handwritten text varies much more and does not conform to standard shapes and sizes of individual characters, which poses an additional challenge for OCR. Recently, deep learning has allowed for significant advances in this area. Google's Cloud Vision, which is based on deep learning, is trained on large-scale datasets, and is shown to be quite adept at this task. This may take us some way towards negating the need for humans to routinely transcribe handwritten text.
Determining the countries and collectors of specimens has been the goal of previous automated text digitisation research activities. Our approach also focuses on these two pieces of information. An area of Natural Language Processing (NLP) known as Named Entity Recognition (NER) has matured enough to semi-automate this task. Our experiments demonstrated that existing approaches can accurately recognise location and person names within the text extracted from segmented images via Tesseract version 4.0.0. Potentially, NER could be used in conjunction with other online services, such as those of the Biodiversity Heritage Library to map the named entities to entities in the biodiversity literature (https://www.biodiversitylibrary.org/docs/api3.html).
We have highlighted the main recommendations for potential pipeline components. The document also provides guidance on selecting appropriate software solutions. These include automatic language identification, terminology extraction, and integrating all pipeline components into a scientific workflow to automate the overall digitisation process.
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Cobb NS, Gall LF, Zaspel JM, Dowdy NJ, McCabe LM, Kawahara AY. Assessment of North American arthropod collections: prospects and challenges for addressing biodiversity research. PeerJ 2019; 7:e8086. [PMID: 31788358 PMCID: PMC6882419 DOI: 10.7717/peerj.8086] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 10/23/2019] [Indexed: 12/21/2022] Open
Abstract
Over 300 million arthropod specimens are housed in North American natural history collections. These collections represent a "vast hidden treasure trove" of biodiversity -95% of the specimen label data have yet to be transcribed for research, and less than 2% of the specimens have been imaged. Specimen labels contain crucial information to determine species distributions over time and are essential for understanding patterns of ecology and evolution, which will help assess the growing biodiversity crisis driven by global change impacts. Specimen images offer indispensable insight and data for analyses of traits, and ecological and phylogenetic patterns of biodiversity. Here, we review North American arthropod collections using two key metrics, specimen holdings and digitization efforts, to assess the potential for collections to provide needed biodiversity data. We include data from 223 arthropod collections in North America, with an emphasis on the United States. Our specific findings are as follows: (1) The majority of North American natural history collections (88%) and specimens (89%) are located in the United States. Canada has comparable holdings to the United States relative to its estimated biodiversity. Mexico has made the furthest progress in terms of digitization, but its specimen holdings should be increased to reflect the estimated higher Mexican arthropod diversity. The proportion of North American collections that has been digitized, and the number of digital records available per species, are both much lower for arthropods when compared to chordates and plants. (2) The National Science Foundation's decade-long ADBC program (Advancing Digitization of Biological Collections) has been transformational in promoting arthropod digitization. However, even if this program became permanent, at current rates, by the year 2050 only 38% of the existing arthropod specimens would be digitized, and less than 1% would have associated digital images. (3) The number of specimens in collections has increased by approximately 1% per year over the past 30 years. We propose that this rate of increase is insufficient to provide enough data to address biodiversity research needs, and that arthropod collections should aim to triple their rate of new specimen acquisition. (4) The collections we surveyed in the United States vary broadly in a number of indicators. Collectively, there is depth and breadth, with smaller collections providing regional depth and larger collections providing greater global coverage. (5) Increased coordination across museums is needed for digitization efforts to target taxa for research and conservation goals and address long-term data needs. Two key recommendations emerge: collections should significantly increase both their specimen holdings and their digitization efforts to empower continental and global biodiversity data pipelines, and stimulate downstream research.
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Affiliation(s)
- Neil S. Cobb
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Lawrence F. Gall
- Entomology Division, Yale Peabody Museum of Natural History, New Haven, CT, United States of America
| | - Jennifer M. Zaspel
- Department of Zoology, Milwaukee Public Museum, Milwaukee, WI, United States of America
- Department of Entomology, Purdue University, West Lafayette, IN, United States of America
| | - Nicolas J. Dowdy
- Department of Zoology, Milwaukee Public Museum, Milwaukee, WI, United States of America
- Department of Biology, Wake Forest University, Winston-Salem, NC, United States of America
| | - Lindsie M. McCabe
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States of America
| | - Akito Y. Kawahara
- Florida Museum of Natural History, University of Florida, Gainesville, FL, United States of America
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7
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Ortega-Sánchez D, de la Cal ES, Quintana JI. Literacies and the Development of Social, Critical, and Creative Thought in Textbook Activities for Primary Education in Social Sciences and the Spanish Language. Front Psychol 2019; 10:2572. [PMID: 31798508 PMCID: PMC6863956 DOI: 10.3389/fpsyg.2019.02572] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 10/30/2019] [Indexed: 11/13/2022] Open
Abstract
The skills of thinking, reading conceptions and reading practice (literacy levels) found in textbook activities for the sixth year of Primary Education in Social Sciences and Spanish Language in Spain are analyzed in this paper. A mixed methodology is used to triangulate the data, integrating the critical analysis of discourse and two types of statistical analysis: descriptive (frequencies and percentages) and inferential (χ2, ANOVA, and the Mann-Whitney U Test). The results inform us of both the permanence and the strengthening of the design of an activity oriented toward the development of traditional conceptions of linguistic-cognitive reading. In the framework of education for global citizenship, the conclusion is the need for student reading practices that begin with the principles of critical literacy directed at the acquisition of social, critical, and creative thinking skills.
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Affiliation(s)
- Delfín Ortega-Sánchez
- Department of Specific Didactics, Faculty of Education, University of Burgos, Burgos, Spain
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8
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Heberling JM, Prather LA, Tonsor SJ. The Changing Uses of Herbarium Data in an Era of Global Change: An Overview Using Automated Content Analysis. Bioscience 2019. [DOI: 10.1093/biosci/biz094] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Abstract
Widespread specimen digitization has greatly enhanced the use of herbarium data in scientific research. Publications using herbarium data have increased exponentially over the last century. Here, we review changing uses of herbaria through time with a computational text analysis of 13,702 articles from 1923 to 2017 that quantitatively complements traditional review approaches. Although maintaining its core contribution to taxonomic knowledge, herbarium use has diversified from a few dominant research topics a century ago (e.g., taxonomic notes, botanical history, local observations), with many topics only recently emerging (e.g., biodiversity informatics, global change biology, DNA analyses). Specimens are now appreciated as temporally and spatially extensive sources of genotypic, phenotypic, and biogeographic data. Specimens are increasingly used in ways that influence our ability to steward future biodiversity. As we enter the Anthropocene, herbaria have likewise entered a new era with enhanced scientific, educational, and societal relevance.
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Affiliation(s)
| | - L Alan Prather
- Department of Plant Biology at Michigan State University
| | - Stephen J Tonsor
- Director of Science & Research, Carnegie Museum of Natural History
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9
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Lorieul T, Pearson KD, Ellwood ER, Goëau H, Molino J, Sweeney PW, Yost JM, Sachs J, Mata‐Montero E, Nelson G, Soltis PS, Bonnet P, Joly A. Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras. APPLICATIONS IN PLANT SCIENCES 2019; 7:e01233. [PMID: 30937225 PMCID: PMC6426157 DOI: 10.1002/aps3.1233] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 01/28/2019] [Indexed: 05/20/2023]
Abstract
PREMISE OF THE STUDY Phenological annotation models computed on large-scale herbarium data sets were developed and tested in this study. METHODS Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time-consuming, requires substantial human investment, and is difficult to mobilize at large taxonomic scales. We created and evaluated new methods based on deep learning techniques to automate annotation of phenological stages and tested these methods on four herbarium data sets representing temperate, tropical, and equatorial American floras. RESULTS Deep learning allowed correct detection of fertile material with an accuracy of 96.3%. Accuracy was slightly decreased for finer-scale information (84.3% for flower and 80.5% for fruit detection). DISCUSSION The method described has the potential to allow fine-grained phenological annotation of herbarium specimens at large ecological scales. Deeper investigation regarding the taxonomic scalability of this approach is needed.
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Affiliation(s)
- Titouan Lorieul
- University of MontpellierMontpellierCEDEX 5France
- Institut national de recherche en informatique et en automatique (INRIA) Sophia‐Antipolis, ZENITH team, Laboratory of InformaticsRobotics and Microelectronics–Joint Research Unit, 34095MontpellierCEDEX 5France
| | - Katelin D. Pearson
- Department of Biological ScienceFlorida State University319 Stadium DriveTallahasseeFlorida32306USA
| | - Elizabeth R. Ellwood
- La Brea Tar Pits and MuseumNatural History Museum of Los Angeles County5801 Wilshire BoulevardLos AngelesCalifornia90036USA
| | - Hervé Goëau
- AMAPUniversité de MontpellierCIRAD, CNRS, INRA, IRDMontpellierFrance
- CIRAD, UMR AMAPMontpellierFrance
| | | | - Patrick W. Sweeney
- Division of BotanyPeabody Museum of Natural HistoryYale UniversityP.O. Box 208118New HavenConnecticut06520USA
| | - Jennifer M. Yost
- Department of Biological SciencesCalifornia Polytechnic State University1 Grand AvenueSan Luis ObispoCalifornia93407USA
| | - Joel Sachs
- Agriculture and Agri‐Food CanadaOttawaCanada
| | | | - Gil Nelson
- iDigBioFlorida State UniversityTallahasseeFlorida32306USA
| | - Pamela S. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFlorida32611USA
| | - Pierre Bonnet
- AMAPUniversité de MontpellierCIRAD, CNRS, INRA, IRDMontpellierFrance
- CIRAD, UMR AMAPMontpellierFrance
| | - Alexis Joly
- Institut national de recherche en informatique et en automatique (INRIA) Sophia‐Antipolis, ZENITH team, Laboratory of InformaticsRobotics and Microelectronics–Joint Research Unit, 34095MontpellierCEDEX 5France
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10
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Mast AR, Ellwood ER. Scaling up public engagement in botanical research. AMERICAN JOURNAL OF BOTANY 2018; 105:628-630. [PMID: 29727466 DOI: 10.1002/ajb2.1075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 02/27/2018] [Indexed: 06/08/2023]
Affiliation(s)
- Austin R Mast
- Department of Biological Science, Florida State University, 319 Stadium Drive, Tallahassee, FL, 32306, USA
| | - Elizabeth R Ellwood
- La Brea Tar Pits & Museum, Natural History Museum of Los Angeles County, 5801 Wilshire Blvd, Los Angeles, CA, 90036, USA
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Ellwood ER, Kimberly P, Guralnick R, Flemons P, Love K, Ellis S, Allen JM, Best JH, Carter R, Chagnoux S, Costello R, Denslow MW, Dunckel BA, Ferriter MM, Gilbert EE, Goforth C, Groom Q, Krimmel ER, LaFrance R, Martinec JL, Miller AN, Minnaert-Grote J, Nash T, Oboyski P, Paul DL, Pearson KD, Pentcheff ND, Roberts MA, Seltzer CE, Soltis PS, Stephens R, Sweeney PW, von Konrat M, Wall A, Wetzer R, Zimmerman C, Mast AR. Worldwide Engagement for Digitizing Biocollections (WeDigBio): The Biocollections Community's Citizen-Science Space on the Calendar. Bioscience 2018; 68:112-124. [PMID: 29599548 PMCID: PMC5862351 DOI: 10.1093/biosci/bix143] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The digitization of biocollections is a critical task with direct implications for the global community who use the data for research and education. Recent innovations to involve citizen scientists in digitization increase awareness of the value of biodiversity specimens; advance science, technology, engineering, and math literacy; and build sustainability for digitization. In support of these activities, we launched the first global citizen-science event focused on the digitization of biodiversity specimens: Worldwide Engagement for Digitizing Biocollections (WeDigBio). During the inaugural 2015 event, 21 sites hosted events where citizen scientists transcribed specimen labels via online platforms (DigiVol, Les Herbonautes, Notes from Nature, the Smithsonian Institution's Transcription Center, and Symbiota). Many citizen scientists also contributed off-site. In total, thousands of citizen scientists around the world completed over 50,000 transcription tasks. Here, we present the process of organizing an international citizen-science event, an analysis of the event's effectiveness, and future directions—content now foundational to the growing WeDigBio event.
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Affiliation(s)
- Elizabeth R Ellwood
- La Brea Tar Pits & Museum, in Los Angeles, California, and was with the Department of Biological Science at Florida State University, in Tallahassee
| | - Paul Kimberly
- Smithsonian Institution, National Museum of Natural History, in Washington, DC
| | - Robert Guralnick
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | | | - Kevin Love
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | - Shari Ellis
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | - Julie M Allen
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | - Jason H Best
- Botanical Research Institute of Texas, in Fort Worth
| | - Richard Carter
- Biology Department at Valdosta State University, in Georgia
| | | | - Robert Costello
- Smithsonian Institution, National Museum of Natural History, in Washington, DC
| | - Michael W Denslow
- Florida Museum of Natural History at the University of Florida, in Gainesville, and the Department of Biology at Appalachian State University, in Boone, North Carolina
| | - Betty A Dunckel
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | - Meghan M Ferriter
- Smithsonian Institution Transcription Center at the Smithsonian Institution Office of the Chief Information Officer, in Washington, DC
| | | | | | | | - Erica R Krimmel
- Department of Biology at The Chicago Academy of Sciences and the Peggy Notebaert Nature Museum, in Chicago, Illinois
| | - Raphael LaFrance
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | - Joann Lacey Martinec
- Gantz Family Collections Center, Science and Education, at The Field Museum, in Chicago, Illinois
| | - Andrew N Miller
- Illinois Natural History Survey at the University of Illinois Urbana-Champaign
| | | | | | - Peter Oboyski
- Essig Museum of Entomology at the University of California, in Berkeley
| | - Deborah L Paul
- Institute for Digital Information and Scientific Communication at Florida State University, in Tallahassee
| | - Katelin D Pearson
- Department of Biological Science at Florida State University, in Tallahassee
| | - N Dean Pentcheff
- Research and Collections at the Natural History Museum of Los Angeles County
| | - Mari A Roberts
- William and Lynda Steere Herbarium at the New York Botanical Garden
| | | | - Pamela S Soltis
- Florida Museum of Natural History at the University of Florida, in Gainesville
| | | | - Patrick W Sweeney
- Yale Peabody Museum of Natural History at Yale University, in New Haven, Connecticut
| | - Matt von Konrat
- Gantz Family Collections Center, Science and Education, at The Field Museum, in Chicago, Illinois
| | - Adam Wall
- Research and Collections at the Natural History Museum of Los Angeles County
| | - Regina Wetzer
- Research and Collections at the Natural History Museum of Los Angeles County
| | | | - Austin R Mast
- Department of Biological Science at Florida State University, in Tallahassee
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