Dataset search in biodiversity research: Do metadata in data repositories reflect scholarly information needs?

large number of datasets with a status “Item is not available”, which we left out, too. The num- ber in brackets denotes the amount of datasets we used for the following considerations. Timelines. Based on the given publication dates, we computed timelines (Fig 5) for the introduction of the various standards over time per data repository. The code and all charts are available as supplementary material in our GitHub repository. As Dryad provides several dc:date elements in the metadata, we used the first available date entry as publication date for the timeline chart. Per repository, the timelines for the different metadata formats are almost identical. Obvi- ously, when introducing a new metadata format, publication dates were adopted from existing metadata formats. Only Figshare uses new date stamps when a new metadata format is pro- vided. For instance, Figshare’s timeline shows that QDC and RDF were launched in 2015. The result for RDF was too large to process it together with the other metadata formats. Hence, we produced the timeline for RDF separately. The timelines across all repositories reveal a steadily increasing number of datasets being published at GBIF, Dryad, Zenodo and Figshare. For PAN- GAEA, the timeline points to a constant number of published datasets of around 10,000 data- sets a year apart from an initial release phase between 2003 and 2007. Metadata field usage. Fig 6 presents how many metadata elements of the best matching standard were filled. The individual results per data archive are available in our repository as

supplementary material (https://github.com/fusion-jena/QuestionsMetadataBiodiv/tree/ master/data_repositories/charts). Dryad used 9 out of 15 available metadata fields from OAI-DC very often (> 80%) including important fields such as dc:title, dc:descrip- tion and dc:subject. dc:publisher and dc:contributor were provided in less that 20%. For GBIF, the EML standard does not provide a fixed number of core elements. Hence, we analyzed the 129 available fields. Most of them (89 elements) were not filled, e.g., fields describing taxonomic information. Data about author, title and description were pro- vided in more than 80%. The general field eml:keyword was used in around 20%. Out of 124 used fields in PANGAEA’s Pan-MD format, 43 fields were filled in more than 80% of the harvested metadata files including information on the author, project name, coordinates, data parameters and used devices. Fields that were less filled are supplementary fields, for instance for citation, e.g., volume, pages. For Zenodo, all required fields in DataCite (identifier, creator, title, publisher, publication year) were always filled. In Table 6. Total number of datasets parsed per data repository and metadata standards and schemata. The numbers in brackets denote the number of datasets used for the analysis. All datasets were harvested and parsed in May 2019. Metadata Standard Dryad PANGAEA GBIF Zenodo Figshare OAI-DC 186951 (142329) 383899 (383899) 44718 (42444) 255000 (255000) 3128798 (3128798) QDC 1718059 (1718059) RDF 186955 (142989) 3157347 (3157347) DATACITE 1268155 (1268155)

DATACITE3 383906 (383906) 1268232 (1268232) OAI-DATACITE 1266522 (1266522) 3134958 (3134958) OAI-DATACITE3 1268679 (1268679) DATACITE4 1268262 (1268262) EML 44718 (42444) DIF 383899 (383899) ISO19139 383899 (383899) ISO19139.iodp 383899 (383899) PAN-MD 383899 (383899) https://doi.org/10.1371/journal.pone.0246099.t006 PLOS ONE Dataset search in biodiversity research PLOS ONE | https://doi.org/10.1371/journal.pone.0246099 March 24, 2021 23 / 36