dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2013). The Access to Biological Collections Data (ABCD) schema and its extensions establish a data exchange standard for mobilizing data about DNA, specimens, observations and geological samples from museums and botanical gardens  (Access to Biological Collections Data Task Group, 2005; Holetschek et al. , 2012). Ecological Metadata Language administers a comprehensive set of vocabularies for describing research data and associated details, such as the temporal/spatial extents of data and methods  (Fegraus et al. , 2005; Jones et al. , 2019). These communitymaintained metadata standards and their associated software development are the key to mobilizing data from all kinds of data sources. In this paper, we aim to inform potential database users and contributors of the strengths and weaknesses of all mainstream biodiversity databases that include ostracod records.
, 2019; Yasuhara, 2019; Chiu et al. , 2020; Martins et al. , 2020). Because of their diverse applications, they have clear potential in the era of open science. Data resources of ostracods have been steadily growing since the pioneering databases, such as the Kempf Database Ostracoda  (Viehberg et al. , 2014)  and  Ellis & Messina Catalogues (Ellis and Messina, 1952). Thus, it is timely to evaluate the current role of ostracods in the growing trend of database-oriented research. The aims of this paper are: • to give an overview of key database projects that involve ostracods, including taxonomically oriented databases (Section 3), Aphia: a multipurpose biodiversity platform (Section 4), marine occurrencebased (paleo)biodiversity databases (Section 5), non-marine occurrence-based (paleo)biodiversity databases (Section 6), and GBIF (Section 8); • to assess the potential role of ostracod data in understanding the history of life, based on records in the Paleobiology Database (Section 7); and • to discuss challenges and future directions in developing ostracod databases and their applications (Section 9).
Database categories To provide the reader with some orientation in the huge pool of existing databases and tools in general, we have divided them into the following categories (Table  1 ): (1) taxonomically oriented databases, (2) multipurpose biodiversity databases, (3) data archives/repositories, (4) data harvesters/recombiners, (5) occurrence-based (paleo)biodiversity databases, and (6) application programming interfaces (APIs). The term database can be used to describe a system where datasets are stored, or alternatively to mean a group of datasets. Taxonomically oriented databases focus on authoritative lists of taxonomic names and classification. The multipurpose biodiversity databases category refers to the Aphia platform and its associated databases. Data harvesters/ recombiners, such as GBIF (Global Biodiversity Information Facility) and OBIS (Ocean Biodiversity Information System), aggregate data through the Integrated Publishing Toolkit (IPT) and currently host the largest amount of biodiversity data among all the databases discussed herein.
The IPT is a free software tool developed by GBIF for registered data publishers, such as the U. S. Geological Survey and the Natural History Museum London, to share biodiversity datasets in the Darwin Core Archive standard  (Robertson et al. , 2014). Occurrence-based (paleo)biodiversity databases, such as the Arctic Ostracode Database and the Paleobiology Database, rely on authorized scientists or working groups to enter/compile data which mainly come from the published literature. Application Programming Interfaces are not databases, but a general software term to describe an interface system that connects programs and endpoints; they are mentioned here due to their ubiquity and usefulness in data accessibility. Each database has its own unique underlying structure for hosting data. Whereas some database designs may facilitate addressing certain questions better than others, the diversity of designs is complementary and beneficial to almost all lines of research and education (e.
Reviewed databases We have reviewed both key ostracod database projects and broader databases that house ostracod data (Fig. 1  and Table  2 ). For each database, we have studied its stated objectives, data sources, data accessibility, geographical and temporal coverage, and interaction with other databases. In Section 3, we review the Kempf Database Ostracoda and Ellis & Messina Catalogues that are designed to preserve taxonomic information for both marine and freshwater ostracods. In Section 4, we review the Aphia platform and the World Ostracoda Database (WOD) that house multiple types of data for both marine and freshwater ostracods, including recent and fossil taxa. The Freshwater Animal Diversity Assessment (FADA) project is briefly reviewed in the Aphia platform section because they are in a close collaboration.
In Section 5, we review the Arctic Ostracode Database, Ocean Biogeographic Information System, "Atlas of Atlantic Planktonic Ostracods" and "An Atlas of Southern Ocean Planktonic Ostracods". An atlas is usually not a database but represents a static output of a database. Nonetheless, we include these two atlases here because they are valuable resources for planktonic ostracods, and because the original data have been partially published by the Natural History Museum London in OBIS as a dataset called "Personal library collection of Martin Angel of published and unpublished Halocyprid (Ostracoda) occurrences"  (Angel, 2016). In Section 6, we review non-marine occurrence-based (paleo)biodiversity databases. In Section 7, we visit ostracods in the Paleobiology Database (PBDB), one of the most comprehensive spatiotemporal paleoecological databases that accommodate fossil data (Ordovician to Quaternary for ostracods).
In Section 8, we introduce GBIF, which aggregates data from all above databases through Integrated Publishing Toolkits. We do not list static individual datasets deposited in data archives/ repositories, such as PANGAEA and NOAA's National Centers for Environmental Information. This is because many mainstream data repositories have joined data harvesters, such as OBIS and GBIF. In Sections 5. 2. and 8, we consider how OBIS and GBIF use metadata standards and recombine datasets from numerous data repositories, respectively. Among these data repositories, PANGAEA and ANTABIF are introduced to illustrate the ostracod data in OBIS. Neptune Sandbox Berlin curates microfossil occurrence and biostratigraphy data from the DSDP/ODP/IODP projects, but include only fossil microplankton (e. g. , calcareous nannofossils, foraminifera, radiolarians, diatoms, and dinoflagellates)  (Lazarus, 1994).
Thus, it is excluded from our review since planktonic ostracods (and other planktonic arthropods) rarely become microfossils due to their poorly calcified carapace  (Perrier et al. , 2015). However, it should be mentioned that numerous studies have generated excellent fossil records of benthic ostracods from DSDP/ODP/IODP samples (e. g. ,  Majoran and Dingle, 2001; Bergue and Govindan, 2010; Alvarez Zarikian, 2015). Abbreviations: Antarctic Biodiversity Information Facility (ANTA-BIF), Arctic Ostracode Database (AOD), Australian Non-marine Ostracode Database (AUNODe), Freshwater Biodiversity Data Portal (BioFresh), Catalogue of Life (CoL), Chinese Non-marine Ostracode Database (CHINODe), Delorme Ostracode Autecological Database (DOAD), East Asia Non-marine Ostracod Database (EANODe), Encyclopedia of Life (EoL), EU-FP6 project Marine Biodiversity and Ecosystem Functioning Network of Excellence (MarBEF), Ellis & Messina Catalogues (E&M), Freshwater Animal Diversity Assessment (FADA), Global Biodiversity Information Facility (GBIF), Kempf Database Ostracoda (KDO), Nonmarine Ostracod Distribution in Europe (NODE), North American Combined Ostracode Database (NACODe), North American Nonmarine Ostracode Database (NANODe), Ocean Biogeographic Information System (OBIS), Ostracod Metadatabase of Environmental and Geographical Attributes (OMEGA), Paleobiology Database (PBDB), South African Non-marine Ostracode Database (SANODe), World Register of Marine Species (WoRMS), World Ostracoda Database (WOD).
Data analysis We calculated database status metrics where possible, including spatial coverage, temporal coverage, resolution of taxonomic identification, and database growth over time. Table  3  summarizes the download information, the requested taxa, and parameters applied on the raw data for each analysis. In Section 5. 1. , although a detailed biogeographical analysis is beyond the scope of this paper, we applied a network-based clustering analysis on the census data from the Arctic Ostracode Database to show a simple example of what type of analyses this database allows. This network-based clustering analysis determines biogeographical clusters or regions by calculating number of cooccurrences between pairs of species and number of shared species between pairs of sites in a bipartite occurrence network  (Vilhena and Antonelli, 2015; Kocsis et al.
Taxonomically oriented databases The Kempf Database Ostracoda (KDO) is one of the earliest initiatives to compile taxonomic indexes and references. Kempf objectively compiled citations for more than 40,000 marine and 9000 non-marine taxonomic names of living and fossil species from the Ordovician to the present day  (Matzke-Karasz, 2014). It is the single most complete and comprehensive listing of ostracod taxonomic names available, referenced to the publications in which taxa were originally described, and constituting a unique and valuable resource. It was published in CD and book forms by the University of Cologne; the data do not include images, descriptions, or synonymies. Since Kempf's death in 2017 there has been a necessary pause in the entry of new data while efforts are made to establish support for the KDO and thus ensure its future.
The World Ostracoda Database (WOD) was established as a taxonomically oriented database in its first phase of database construction, compiling taxonomic information on fossil and Recent/living marine and non-marine ostracods. Using the robust infrastructure of the Aphia platform, the taxonomic information is accessible online and constantly growing. Ongoing further development phases include adding a wider range of data (e. g. , biogeographical, ecological, evolutionary) (see Section 4. for more details).
Aphia, a multipurpose biodiversity platform, and the World Ostracoda Database The European Register of Marine Species (ERMS) is an authoritative (i. e. , made by taxonomic experts) list (initially published as a printed book) of >29,000 (geologically) Recent marine and brackish-water species from European waters, of which some 700 are ostracods, together with information on their taxonomy and references for their taxonomic identification  (Costello et al. , 2001; Cuvelier et al. , 2006). ERMS can now be accessed via the MarBEF web site  (MarBEF, 2004). Through a series of mostly EU funded programs, projects, initiatives, and institutions (e. g. , MarBEF, Species 2000 Europa, Flanders Marine Institute, Species 2000), ERMS was fed into a relational digital database  (Cuvelier et al. , 2006) , which later became the Aphia platform.
ERMS was then expanded to a global register, the World Register of Marine Species (WoRMS), and later the initiative expanded further to compiling information on all living and fossil species from all ecosystems (marine and non-marine), as well as starting to incorporate all aspects of taxonomy and nomenclature, also biological, ecological, evolutionary, biogeographical, genetic, bibliographical and nomenclatural information, conservation importance, economic importance, images, and notes (e. g. , stratigraphy, taxonomic remarks, description). All these data are displayed to the public in the form of taxonomic, regional, and thematic registers, each one with its own webpage. Examples of these three kinds. This diagram shows that many databases are in partnership rather than in isolation. Marine databases (blue) and non-marine databases (green) are connected through databases (orange) that accommodate both information.
Some databases (bold) are independent, and some (not bold) are a part of or adopted into Aphia or BioFresh. We simplified the connections to three kinds: (1) data exchange (solid double arrows) between independent databases, (2) data ingestion from regional databases to broader-scale databases (solid arrows), and (3) data ingestion in progress (dashed arrows). Paleobiology Database (PBDB) and Neotoma Database are in close collaboration (a solid line) through Earth Life Consortium. GBIF and OBIS aggregate data through Integrated Publishing Toolkits (gray circles); NCEI, ANTABIF, and PANGAEA (thickened box border) are contributed by authors of publications; other databases are maintained by authorized editors/enterers/data stewards/working groups. Specimens and collections from museums (gray) are important data sources to GBIF and OBIS.
"Planktonic ostracod atlases" refer to "Atlas of Atlantic Planktonic Ostracods" and "An Atlas of Southern Ocean Planktonic Ostracods". Abbreviations: see Section 2. 2. for full names. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article. ) of registers are, respectively, the World Ostracoda Database (WOD), the Register of Antarctic Species (RAS) and the World Register of Introduced Marine Species (WRiMS). The different registers' web interfaces make the information contained in Aphia available to the public in a more accessible way. For example, someone looking for data on ostracods will tend to access the WOD webpage, while someone looking for Antarctic species will access RAS. However, all data are housed within Aphia, and the web interfaces provide search tools which communicate with the Aphia database.
Since its inception Aphia grew significantly and several tools were created; one worthy of mention is the online editing environment available since 2006, through which hundreds of accredited editors can log into the system and edit or add information only to their specific taxa  (Costello, 2000; Vandepitte et al. , 2015). In this way, although the information in the database is accessible to the general public, the quality of the data is assured by the fact that only accredited specialists can edit the information in the database. For example, only an editor can add, delete and correct taxonomic, ecological, evolutionary, biogeographical, genetic, bibliographical and nomenclatural information, conservation importance, economic importance, images, stratigraphical and other kinds of notes, etc.
(Vandepitte et al. , 2015). Furthermore, mistakes and omissions can be constantly detected and passed to and corrected by the responsible editors. However, the lack of editors responsible for specific subjects or taxa will surely delay the correction of such mistakes. The low number of editors is now the main problem of WOD, with the consequence that mistakes take longer to be corrected. Nevertheless, a clear advantage of these open access, online databases (such as WOD) is to simplify or avoid taxonomic confusion, e. g. , synonyms and homonyms. One example in ostracodology is Vandenboldina Wilson, 2010 published as a new name for Pseudoceratina Bold, 1965, after Simone N. Brandão (editor-in-chief of the WOD) advertised it via Ostracon (the email list for ostracod researchers) as a junior homonym of Pseudoceratina Carter, 1885 (Porifera).
Although the first objective of ERMS was to produce a species list, a much broader idea lay behind its initial proposals (e. g. ,  Costello, 2000, Fig. 3 ), encompassing networking with other databases and scientific programs (for example, oceanographic atlases with information on water masses, bathymetry, nutrients, etc. ), online tools for capturing, storing and displaying biogeographical information, and modelling of future species distribution and ocean ecosystem functions. The Aphia platform contains a database, which hosts all data from WOD, WoRMS and the remaining ~80 global, regional, and thematic registers. The SQL database of Aphia with "over 400 fields, spread over 81 related tables", which are grouped in relation to the content in "10 modules: taxonomy, distribution, traits, specimen information, vernacular names, notes, links, images, identification keys and sources"  (Vandepitte et al.
, 2015). The EU-funded Lifewatch infrastructure for biodiversity and ecosystem research is promoting the data mining and upload of a large amount of biological, morphological, evolutionary, ecological, taxonomic and human defined characteristics of virtually all taxa, including ostracods, to the module "traits" of Aphia, e. g. , body size, feeding type, life cycle, invasive species, threatened species, etc. (  Vandepitte et al. , 2015). Aphia provides data to other databases (e. g. , GBID, OBIS, CoL, ITIS, several museums, scientific institutions and individual scientists) and provides links to them in the specific taxa pages, in order to, for example, avoid duplication of work  (Cuvelier et al. , 2006; Vandepitte et al. , 2015). Within the scope of the AquaRES (Aquatic Species Register Exchange and Services) project, Aphia exchanges data with the Freshwater Animal Diversity Assessment (FADA).
The AquaRES project aims at managing the data of aquatic groups occurring in both freshwater and marine ecosystems in one system  (Vandepitte et al. , 2015). The FADA database, led by Koen Martens from the Royal Belgian Institute of Natural Sciences, provides taxonomic checklists and distribution information of many freshwater animals, including ostracods  (Balian et al. , 2008; Martens et al. , 2013). Georeferenced datasets can be made available via the Freshwater Information Platform which integrates FADA through the Freshwater Biodiversity Data Portal. In an output of FADA, nonmarine ostracods are grouped into eight biogeographic regions: Antarctic (3 species), Australasian (262 species), Afrotropical (453 species), Nearctic (300 species), Neotropical (290 species), Oriental/Indomalaya (222 species), Pacific/Oceania (57 species) and Palaearctic (749 species)  (Martens et al.
, 2013). The distribution of each taxon is thus limited to its presence anywhere within a named biogeographical region, rather than single occurrences identified by coordinates and other data (e. g. , latitude, longitude, altitude, date of sampling). The taxonomic classification of each taxon is provided, but not the taxonomic history or original description. The World Ostracoda Database (WOD) is one of the global species registers housed in Aphia. Its aims are to compile a wide range of data types on recent and fossil Ostracoda, including taxonomy, classification, synonymy, description, bibliography, type specimens' information, geographical and stratigraphical occurrences, illustrations, biological and ecological attributes (e. g. , feeding type, body size, functional group, development, life cycle, habitat).
WOD originated in 2008, when the chair of the WoRMS, Geoff Boxshall invited Simone N. Brandão to check a spreadsheet with approximately 8,000 ostracod taxa compiled from publications on Recent marine Ostracoda. In 2013, a grant from Life-Watch enabled a large input of data on Ostracoda, including tens of thousands of taxa and bibliographic references on marine, non-marine, extant, and extinct ostracods. WOD has kept expanding since then and has information now on more than 54,449 taxa: 45,294 species, of which 32,140 are accepted, and 3,676 genera, of which 3,446 are accepted. WOD, WoRMS and the remaining registers in Aphia aim to record the entire taxonomic history of a taxon, and thus unaccepted taxa are kept in the database with an "unaccepted" label. In most cases these unaccepted taxa are invalid generic combinations at the species level, but other unaccepted taxa are subjective synonyms (i.
Arctic Ostracode Database The Arctic Ostracode Database (AOD) is dedicated to census data of benthic marine ostracods collected from a variety of surface and late Quaternary sediment samples from the Arctic area (Fig. 2 ). The samples came from international sampling cruises to the Arctic since 1933 (Fig. 2B ). The census data provide numbers of specimens per species in each sample. It also provides taxonomic information of Arctic ostracods, which all the contributors agreed on. Therefore, taxonomic names are thoroughly harmonized in the AOD. Age information at finer resolution than "modern to late Quaternary" is unavailable in the AOD but might be indicated by papers based on the same samples elsewhere. The development of the AOD has been led by Thomas M. Cronin and Laura Gemery in the United States Geological Survey (USGS).
The home repository of the AOD is NOAA's National Centers for Environmental Information. It started as the Modern Arctic Podocopid Ostracode Database  (Cronin et al. , 1991)  and had several major updates, including Arctic Ostracode Database  (Cronin et al. , 1995) , Modern Arctic Ostracode Database  (Cronin et al. , 2010) , Arctic Ostracode Database-2015  (Gemery et al. , 2017) , and Arctic Ostracode Database-2020  (Cronin et al. , 2021)  (Fig. 2B ). The online USGS version of the Arctic Ostracode Database was contributed by Thomas M. Cronin, Thomas R. Holtz, Elisabeth M. Brouwers, William M. Briggs, Robin C. Whatley and Adrian Wood  (Cronin et al. , 1995). Some of the datasets in the AOD are also present in other databases, such as PANGAEA and OBIS. Through the Integrated Publishing Toolkit, OBIS (OBIS Secretariat, 2021) also harvested the Modern Arctic Ostracode Database  (Cronin et al.
Ocean Biogeographic Information System The Ocean Biogeographic Information System (OBIS) is dedicated to occurrence records, event records, and measurements/facts of modern marine life. It started as one initiative of the Census of Marine Life  (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010)  and had been adopted into the UNESCO's International Oceanographic Data and Information (IODE) program since 2010. OBIS gathered data through Integrated Publishing Toolkits from more than 20 OBIS regional/country/thematic nodes (e. g. , Arctic OBIS, OBIS Germany, Fish OBIS), which connect hundreds of institutional data publishers or data archives (e. g. , PANGAEA, NOAA's NCEI, USGS). The Integrated Publishing Toolkit, developed by GBIF, assists with formatting the data to valid Darwin Core terms and describing dataset metadata in Ecological Metadata Language.
This readily allows interoperability of datasets. OBIS reached 0. 5 million records in 2002, and over 63 million occurrence records in 2020 (obis. org), together with geographic and bathymetric distribution and environmental data (e. g. , salinity, temperature). To ensure the utility of a system such as OBIS, which integrates datasets from multiple sources that were originally compiled in a variety of circumstances and for different purposes, a certain amount of data and metadata standardization is essential  (OBIS, 2021). This may be achieved by having mandatory fields that must be completed for the dataset to be accepted. For example, biogeographical data in OBIS requires locations to be defined by latitude and longitude coordinates in decimal degrees to facilitate mapping of records, so inclusion of datasets that use a different coordinates system such as Universal Transverse Mercator (UTM) requires conversions.