A Standardised Vocabulary for Identifying Benthic Biota and Substrata from Underwater Imagery: The CATAMI Classification Scheme
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{"title"=>"A standardised vocabulary for identifying benthic biota and substrata from underwater imagery: The CATAMI classification scheme", "type"=>"journal", "authors"=>[{"first_name"=>"Franziska", "last_name"=>"Althaus", "scopus_author_id"=>"7006003735"}, {"first_name"=>"Nicole", "last_name"=>"Hill", "scopus_author_id"=>"9276975200"}, {"first_name"=>"Renata", "last_name"=>"Ferrari", "scopus_author_id"=>"56320859000"}, {"first_name"=>"Luke", "last_name"=>"Edwards", "scopus_author_id"=>"57004323800"}, {"first_name"=>"Rachel", "last_name"=>"Przeslawski", "scopus_author_id"=>"8927320900"}, {"first_name"=>"Christine H.L.", "last_name"=>"Schönberg", "scopus_author_id"=>"6602585081"}, {"first_name"=>"Rick", "last_name"=>"Stuart-Smith", "scopus_author_id"=>"6507368501"}, {"first_name"=>"Neville", "last_name"=>"Barrett", "scopus_author_id"=>"7102133208"}, {"first_name"=>"Graham", "last_name"=>"Edgar", "scopus_author_id"=>"7005803258"}, {"first_name"=>"Jamie", "last_name"=>"Colquhoun", "scopus_author_id"=>"24733807900"}, {"first_name"=>"Maggie", "last_name"=>"Tran", "scopus_author_id"=>"56215485900"}, {"first_name"=>"Alan", "last_name"=>"Jordan", "scopus_author_id"=>"7202511691"}, {"first_name"=>"Tony", "last_name"=>"Rees", "scopus_author_id"=>"57004436800"}, {"first_name"=>"Karen", "last_name"=>"Gowlett-Holmes", "scopus_author_id"=>"6507092118"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"26509918", "doi"=>"10.1371/journal.pone.0141039", "sgr"=>"84949988610", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84949988610", "issn"=>"19326203", "pui"=>"607232468"}, "id"=>"b7f474e3-05c5-3051-ac5f-2d582f5478c8", "abstract"=>"<p>Imagery collected by still and video cameras is an increasingly important tool for minimal impact, repeatable observations in the marine environment. Data generated from imagery includes identification, annotation and quantification of biological subjects and environmental features within an image. To be long-lived and useful beyond their project-specific initial purpose, and to maximize their utility across studies and disciplines, marine imagery data should use a standardised vocabulary of defined terms. This would enable the compilation of regional, national and/or global data sets from multiple sources, contributing to broad-scale management studies and development of automated annotation algorithms. The classification scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) project provides such a vocabulary. The CATAMI classification scheme introduces Australian-wide acknowledged, standardised terminology for annotating benthic substrates and biota in marine imagery. It combines coarse-level taxonomy and morphology, and is a flexible, hierarchical classification that bridges the gap between habitat/biotope characterisation and taxonomy, acknowledging limitations when describing biological taxa through imagery. It is fully described, documented, and maintained through curated online databases, and can be applied across benthic image collection methods, annotation platforms and scoring methods. Following release in 2013, the CATAMI classification scheme was taken up by a wide variety of users, including government, academia and industry. This rapid acceptance highlights the scheme’s utility and the potential to facilitate broad-scale multidisciplinary studies of marine ecosystems when applied globally. Here we present the CATAMI classification scheme, describe its conception and features, and discuss its utility and the opportunities as well as challenges arising from its use.</p>", "link"=>"http://www.mendeley.com/research/standardised-vocabulary-identifying-benthic-biota-substrata-underwater-imagery-catami-classification", "reader_count"=>54, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Researcher"=>20, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>2, "Student > Master"=>9, "Other"=>3, "Student > Bachelor"=>5, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Researcher"=>20, "Student > Doctoral Student"=>1, "Student > Ph. D. 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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2385945"], "description"=>"<p>The figure illustrates the level of detail achieved within each classification system. Image 1: taken by IMAS with the ACFR AUV off the east coast of Tasmania, Australia at 24 m depth; Image 2 taken by CSIRO with the ‘Deep Camera Platform’ at Hill U Seamount south of Tasmania, Australia at 1167 m depth.</p>", "links"=>[], "tags"=>["taxonomy", "marine environment", "data sets", "annotation platforms", "annotation algorithms", "Automated Tools", "classification scheme", "benthic image collection methods", "Standardised Vocabulary", "video cameras", "Underwater Imagery", "utility", "marine imagery data", "Marine Imagery", "CATAMI Classification Scheme Imagery", "management studies", "repeatable observations", "CATAMI classification scheme", "annotating benthic substrates", "Marine ecosystems", "standardised terminology", "multidisciplinary studies", "Benthic Biota"], "article_id"=>1587981, "categories"=>["Uncategorised"], "users"=>["Franziska Althaus", "Nicole Hill", "Renata Ferrari", "Luke Edwards", "Rachel Przeslawski", "Christine H. L. Schönberg", "Rick Stuart-Smith", "Neville Barrett", "Graham Edgar", "Jamie Colquhoun", "Maggie Tran", "Alan Jordan", "Tony Rees", "Karen Gowlett-Holmes"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0141039.g002", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_classification_of_two_underwater_images_using_a_habitat_biotope_classification_EUNIS_33_34_the_CATAMI_Classification_Scheme_CCS_and_a_taxonomic_classification_WoRMS_37_/1587981", "title"=>"Comparison of the classification of two underwater images using a habitat/biotope classification (EUNIS–[33, 34]), the CATAMI Classification Scheme (CCS) and a taxonomic classification (WoRMS–[37]).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-10-28 03:44:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/2385946"], "description"=>"<p>A range of macroalgal indices have been proposed for subtidal environments that utilise morphological and biological traits of species or groups. Table 1 shows how CATAMI macroalgal classifications aligned with life-history characteristics often used in the derivation of indicators, and with the ecological status groups proposed by Orfandis et al. for monitoring the health of marine systems [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141039#pone.0141039.ref088\" target=\"_blank\">88</a>].Ecological state group I—late successional species, ecological state group II—opportunistic species.</p><p>CATAMI macroalgal classification aligned with life-history characteristics often used in the derivation of indicators, and with the ecological status groups for monitoring the health of marine systems.</p>", "links"=>[], "tags"=>["taxonomy", "marine environment", "data sets", "annotation platforms", "annotation algorithms", "Automated Tools", "classification scheme", "benthic image collection methods", "Standardised Vocabulary", "video cameras", "Underwater Imagery", "utility", "marine imagery data", "Marine Imagery", "CATAMI Classification Scheme Imagery", "management studies", "repeatable observations", "CATAMI classification scheme", "annotating benthic substrates", "Marine ecosystems", "standardised terminology", "multidisciplinary studies", "Benthic Biota"], "article_id"=>1587982, "categories"=>["Uncategorised"], "users"=>["Franziska Althaus", "Nicole Hill", "Renata Ferrari", "Luke Edwards", "Rachel Przeslawski", "Christine H. L. Schönberg", "Rick Stuart-Smith", "Neville Barrett", "Graham Edgar", "Jamie Colquhoun", "Maggie Tran", "Alan Jordan", "Tony Rees", "Karen Gowlett-Holmes"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0141039.t001", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CATAMI_macroalgal_classification_aligned_with_life_history_characteristics_often_used_in_the_derivation_of_indicators_and_with_the_ecological_status_groups_for_monitoring_the_health_of_marine_systems_/1587982", "title"=>"CATAMI macroalgal classification aligned with life-history characteristics often used in the derivation of indicators, and with the ecological status groups for monitoring the health of marine systems.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-28 03:44:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/2385940"], "description"=>"<p>The biological classification at coarsest level is into phyla or broad groups, which are then divided using either taxonomy or morphology (as shown here), depending on what can be more consistently determined from imagery. The number of categories (C) and levels (L) defined under each branch are shown. The full classification scheme can be viewed at <a href=\"http://www.catami.org/classification\" target=\"_blank\">http://www.catami.org/classification</a> [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141039#pone.0141039.ref053\" target=\"_blank\">53</a>].</p>", "links"=>[], "tags"=>["taxonomy", "marine environment", "data sets", "annotation platforms", "annotation algorithms", "Automated Tools", "classification scheme", "benthic image collection methods", "Standardised Vocabulary", "video cameras", "Underwater Imagery", "utility", "marine imagery data", "Marine Imagery", "CATAMI Classification Scheme Imagery", "management studies", "repeatable observations", "CATAMI classification scheme", "annotating benthic substrates", "Marine ecosystems", "standardised terminology", "multidisciplinary studies", "Benthic Biota"], "article_id"=>1587977, "categories"=>["Uncategorised"], "users"=>["Franziska Althaus", "Nicole Hill", "Renata Ferrari", "Luke Edwards", "Rachel Przeslawski", "Christine H. L. Schönberg", "Rick Stuart-Smith", "Neville Barrett", "Graham Edgar", "Jamie Colquhoun", "Maggie Tran", "Alan Jordan", "Tony Rees", "Karen Gowlett-Holmes"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0141039.g001", "stats"=>{"downloads"=>0, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_the_coarsest_levels_of_the_CATAMI_Classification_Scheme_for_a_physical_and_b_biological_annotations_in_imagery_c_and_d_show_details_of_the_8216_bryozoa_8217_and_the_8216_echinoderms_8217_branches_/1587977", "title"=>"Overview of the coarsest levels of the CATAMI Classification Scheme for (a) physical and (b) biological annotations in imagery; (c) and (d) show details of the ‘bryozoa’ and the ‘echinoderms’ branches.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-10-28 03:44:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/2385947", "https://ndownloader.figshare.com/files/2385948", "https://ndownloader.figshare.com/files/2385949"], "description"=>"<div><p>Imagery collected by still and video cameras is an increasingly important tool for minimal impact, repeatable observations in the marine environment. Data generated from imagery includes identification, annotation and quantification of biological subjects and environmental features within an image. To be long-lived and useful beyond their project-specific initial purpose, and to maximize their utility across studies and disciplines, marine imagery data should use a standardised vocabulary of defined terms. This would enable the compilation of regional, national and/or global data sets from multiple sources, contributing to broad-scale management studies and development of automated annotation algorithms. The classification scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) project provides such a vocabulary. The CATAMI classification scheme introduces Australian-wide acknowledged, standardised terminology for annotating benthic substrates and biota in marine imagery. It combines coarse-level taxonomy and morphology, and is a flexible, hierarchical classification that bridges the gap between habitat/biotope characterisation and taxonomy, acknowledging limitations when describing biological taxa through imagery. It is fully described, documented, and maintained through curated online databases, and can be applied across benthic image collection methods, annotation platforms and scoring methods. Following release in 2013, the CATAMI classification scheme was taken up by a wide variety of users, including government, academia and industry. This rapid acceptance highlights the scheme’s utility and the potential to facilitate broad-scale multidisciplinary studies of marine ecosystems when applied globally. Here we present the CATAMI classification scheme, describe its conception and features, and discuss its utility and the opportunities as well as challenges arising from its use.</p></div>", "links"=>[], "tags"=>["taxonomy", "marine environment", "data sets", "annotation platforms", "annotation algorithms", "Automated Tools", "classification scheme", "benthic image collection methods", "Standardised Vocabulary", "video cameras", "Underwater Imagery", "utility", "marine imagery data", "Marine Imagery", "CATAMI Classification Scheme Imagery", "management studies", "repeatable observations", "CATAMI classification scheme", "annotating benthic substrates", "Marine ecosystems", "standardised terminology", "multidisciplinary studies", "Benthic Biota"], "article_id"=>1587983, "categories"=>["Uncategorised"], "users"=>["Franziska Althaus", "Nicole Hill", "Renata Ferrari", "Luke Edwards", "Rachel Przeslawski", "Christine H. L. Schönberg", "Rick Stuart-Smith", "Neville Barrett", "Graham Edgar", "Jamie Colquhoun", "Maggie Tran", "Alan Jordan", "Tony Rees", "Karen Gowlett-Holmes"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0141039.s001", "https://dx.doi.org/10.1371/journal.pone.0141039.s002", "https://dx.doi.org/10.1371/journal.pone.0141039.s003"], "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_Standardised_Vocabulary_for_Identifying_Benthic_Biota_and_Substrata_from_Underwater_Imagery_The_CATAMI_Classification_Scheme_/1587983", "title"=>"A Standardised Vocabulary for Identifying Benthic Biota and Substrata from Underwater Imagery: The CATAMI Classification Scheme", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-10-28 03:44:22"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"15", "full-text"=>"11", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"17", "full-text"=>"21", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"20", "full-text"=>"13", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"3", "cited-by"=>"1", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"3", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"9", "full-text"=>"7", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"11", "full-text"=>"11", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"20", "full-text"=>"24", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"16", "full-text"=>"16", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"16", "full-text"=>"14", "pdf"=>"10", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"20", "full-text"=>"20", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"20", "full-text"=>"18", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"17", "full-text"=>"14", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
  • {"unique-ip"=>"11", "full-text"=>"9", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"11", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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