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

general fields or longer textual fields such as title and description contain useful keywords. Most repositories indeed enhance metadata with numerous keywords in general fields. They reflect scholarly information needs to some extent. The extracted keyword list emphasizes the heterogeneity of research data in biodiversity research and shows in which different granular- ity data are described. Keywords vary between broad subject categories and concrete measur- ing methods. In addition, different spellings amplify the problem of inconsistency. D—Discussion In this study, we explored what hampers dataset retrieval in biodiversity research. The follow- ing section discusses our findings, highlights topics that should be further discussed in the bio- diversity research community and lists remaining challenges for computer science. Scholarly search interests in biodiversity research We identified five information categories being important for search tasks in biodiversity research, namely, ENVIRONMENT, MATERIAL, ORGANISM, PROCESS and LOCATION. The categories QUALITY and DATA TYPE only got a fair agreement but are mentioned quite often in the search questions. Comparing our question analysis to the outcome of the content assessment analysis con- ducted in the GBIF community [28] in 2009, the authors’ assumption of this study that user interests change over time has been confirmed. Species are still an important category scholars are interested in, however, further important topics for the acquisition and description of eco-

system services are emerging. Our results confirm some of the defined dimensions in EASE [43], a metadata schema developed for search purposes. Common categories are ORGANISM, PROCESS, TIME and LOCATION (Space). Instead of the category QUALITY, data parame- ters in EASE are collected in sub-elements of the dimension METHOD. For some categories, our definitions go beyond the EASE dimensions. We found that MATERIALs in a broader sense are relevant to biodiversity researchers and not only chemicals. The same applies for environmental terms. They are in general important for dataset retrieval in biodiversity research and not just biomes. In addition to EASE we found that a separate category DATA TYPE should be considered as many researchers asked for specific result types of research methods. In summary, we conclude that the diversity of scholarly search interests in biodiversity research can indeed be structured and grouped into a limited amount of categories. Consider- ing these interests in dataset descriptions and search interfaces will facilitate dataset retrieval. Metadata analysis of selected data repositories Our study reveals that current metadata in data repositories match scholarly search interests only to some extent. Only if proper keywords are contained in general or descriptive fields, conventional retrieval algorithms are able to find relevant datasets. Poorly described data in combination with keyword-based retrieval techniques that are mainly used in retrieval systems

of data repositories [4] result in less relevant hits in search results or a long time spent until suitable data have been retrieved [3, 6, 7]. That might cause users to send explicit data requests to data repositories [5] or to switch to other data sources such as literature and general search engines [8]. Improved filter options such as a faceted search only support data seekers if either relevant, explicit metadata fields are provided or keywords are aligned and grouped [33]. Arbitrary metadata descriptions hamper both. Although metadata are not only created for search pur- poses, they are a key building block for successful data retrieval. Therefore, scholars need to be PLOS ONE Dataset search in biodiversity research PLOS ONE | https://doi.org/10.1371/journal.pone.0246099 March 24, 2021 29 / 36