dataesr/scientific-paragraphs-categorization huggingface dataset:
The areas of best coverage concentrate mostly in: (1) the northern hemisphere, and particularly the North Atlantic (versus the southern hemisphere and the Pacific Ocean; Fig. 3A);  (2) coastal regions (versus open ocean and deep ocean; Fig. 3B ). PANGAEA is an important contributor to the ostracod data in OBIS. Hosted by the Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research (AWI) and the Center for Marine Environmental Sciences (MARUM), PANGAEA is a mainstream data archive/repository for georeferenced data from earth system research, e. g. , Deep Sea Drilling Program  (DSDP, 1967 (DSDP, -1983)) , Ocean Drilling Program  (ODP, 1984 (ODP, -2002)) , Integrated Ocean Drilling Program  (IODP, 2003 (IODP, -2013)) , the International Ocean Discovery Program  (IODP, 2013 (IODP, -2023)) , and many other research projects of various scales.
Despite its focus on modern marine ecosystems, OBIS also harvested paleontological datasets from PANGAEA. Endorsed by the Scientific Committee on Antarctic Research (SCAR), the Antarctic Biodiversity Information Facility (ANTABIF) exchanges biogeographical data of marine species with the Antarctic Thematic Node of OBIS, the AntOBIS, and provides data ultimately to GBIF. ANTABIF is a complex platform focused on continental and marine research in/off Antarctica, and it houses a diverse collection of oceanographical, ecological, biological and geological datasets (e. g. , SCAR Southern Ocean Diet and Energetics Database), as well as providing online analysis tools for the scientific community (e. g. , interactive identification keys, R packages relevant to Antarctic and Southern Ocean science).
Concerning the biogeographical data exchanged with OBIS, currently ANTABIF hosts over 190 datasets of many taxonomic groups, including Southern Ocean Ostracoda (excluding Halocypridina)  (Brandão, 2012) , which focuses on benthic ostracods. These datasets can be accessed through the Antarctic Biodiversity Portal (biodiversity. aq, 2021), which integrates datasets compiled under the SCAR-MarBIN (SCAR-Marine Biodiversity Information Network) initiative with data from different sources, including the Australian Antarctic Division and other institutions. The Southern Ocean benthic Ostracoda dataset  (Brandão, 2012)  includes 888 occurrences of 113 taxa from 193 georeferenced locations. Planktonic Southern Ocean ostracods were covered by one atlas, which offer the taxonomy, geographical distribution (static occurrence maps), illustrations and measurements of key morphological features of species (mostly Halocypridina, but all known planktonic Cypridinida are also present; see the next section).
Marine planktonic ostracods Martin Angel, Kasia Blachowiak-Samolyk, and Vladimir Chavtur compiled the available information on marine planktonic ostracods from the Atlantic and Southern Oceans, and published the "Atlas of Atlantic Planktonic Ostracods"  (Angel et al. , 2008)  and "An Atlas of Southern ). Most records come from 0 to 500 m water depths. Most records (49. 4%) had identification resolution down to the species level, but many records (37. 6%) were just "Ostracoda". Ocean Planktonic Ostracods" (Blachowiak-Samolyk and  Angel, 2008). The Atlantic compilation  (Angel et al. , 2008)  includes data from before the Challenger expedition (1870s) up to 2007, while the Southern Ocean dataset (Blachowiak-Samolyk and  Angel, 2008)  include data from the Discovery Investigations (1930s) up to 2007.
Non-marine occurrence-based (paleo)biodiversity databases There are several regional databases focused on the ecology and distribution of living non-marine ostracods. Prominent among these are NODE (Non-marine Ostracod Distribution in Europe), NANODe (North American Non-marine Ostracode Database), DOAD (Delorme Ostracode Autecological Database), and EANODe (East Asia Non-marine Ostracod Database); key metadata and data from these and other regional databases are compiled in OMEGA (Ostracod Metadatabase of Environmental and Geographical Attributes). Datasets from DOAD and NANODe have been amalgamated into a North American Combined Ostracode Database (NACODe) as well as being made accessible through the Neotoma Paleoecology Database. Details of each of these are described briefly below. Distribution maps of all records from the above databases are in Fig.
Non-marine Ostracod Distribution in Europe The Non-marine Ostracod Distribution in Europe (NODE) database contains approximately 10,000 records of living ostracod species (plus about 2,000 Pleistocene and Holocene fossil records), representing more than 400 species and approximately 2,500 localities. It was initiated by six research teams in five countries to map the distribution of ostracod sex and parthenogenesis for the three-year  (1994) (1995) (1996)  EU Human Capital and Mobility Programme project Evolutionary ecology of reproductive modes in non-marine Ostracoda  (Horne et al. , 1998)  and subsequently developed further by David J. Horne as its Data Steward (i. e. , the person responsible for all aspects of database management including quality control and accessibility). Focused on Europe, its geographical coverage extends longitudinally from the Azores to east of the Black Sea and latitudinally from the Canary Islands to Svalbard (approx.
32 o W -45 • E and 25-80 o N). A few additional North American and Asian records are currently included in NODE for calibration purposes in connection with Quaternary paleoclimatic reconstruction (see discussion below); these may eventually be transferred to other databases. The records in NODE, compiled almost entirely from scientific literature published in the 19th, 20th and 21st centuries, are focused on occurrences of identified ostracod species but include (where possible) information such as water body type, date of collection, and whether males were found. (A) Geographical distribution of all the sites in the Ostracod Metadatabase of Environmental and Geographical Attributes (OMEGA), colour-coded according to the contributing databases: Australian Nonmarine Ostracode Database (AUNODe), Chinese Non-marine Ostracode Database (CHINODe), Delorme Ostracode Autecological Database (DOAD), East Asia Non-marine Ostracod Database (EANODe), North American Non-marine Ostracode Database (NANODe), Non-marine Ostracod Distribution in Europe (NODE) database, South African Non-marine Ostracod Database (SANODe).
North American Non-marine Ostracode Database The North American Non-marine Ostracode Database (NANODe) was initiated by Richard M. Forester at the U. S. Geological Survey. Field collection efforts were conducted primarily by  Forester et al. (2005) , and data subsequently managed by Alison J. Smith as Data Steward. The dataset (www. kent. edu/nanode) is composed of late 20th to early 21st century collections  (1979 through 2005)  and contains approximately 2,600 records comprising c. 100 species and c. 600 localities with accompanying major ion hydrochemical and field limnological data collected at the same time as the species collection  (Forester et al. , 2005). It provides a well-distributed coverage of the conterminous states of the USA from California in the west to New Hampshire in the east (approx.
124-70 o W and 29-49 o N) although the southeastern states (Florida to the Carolinas) are not yet represented. The distribution of each of the species in NANODe is shown in geographic maps and in solute graphs (www. kent. edu/nanode). The data are completely accessible through the multiproxy Neotoma Paleoecology Database (see below). The slide collection is housed in the Geology Department at Kent State University, Kent, Ohio (USA).
Delorme Ostracode Autecological Database The Delorme Ostracode Autecological Database (DOAD), based on primary collection by Denis Delorme during the 1960s and 1970s, includes over 30,000 records representing c. 130 species and more than 6,000 localities, together with extensive geographical, environmental, and climatic data for the waterbodies sampled. Both the database and a very substantial collection of voucher specimens (representing almost every record in the database) are now housed and curated by the Canadian Museum of Nature at its Natural Heritage Campus (Research and Collections Facility) in Gatineau, Canada, together with a collection of type and illustrated ostracod specimens (related to Delorme's publications) that was formerly kept at the Geological Survey of Canada in Ottawa.
East Asia Non-marine Ostracod Database The East Asia Non-marine Ostracod Database (EANODe), compiled and managed by Robin J. Smith as its Data Steward, contains approximately 1,700 records representing c. 150 species and c. 650 localities, of which the majority are in Japan but including South Korea, China and the Far Eastern Federal District of Russia (approx. 108-145 • E and 18-72 o N). The data are mainly from primary collections represented by specimens curated at the Lake Biwa Museum in Japan (c. 75%), the remainder being compiled from published literature (25%).
Ostracod Metadatabase of Environmental and Geographical Attributes A single global database of non-marine ostracod distribution would be of immense scientific value, but creating one would be a very challenging, long-term project. As a more pragmatic approach, with shortterm as well as long-term benefits, we initiated the OMEGA: Ostracod Metadatabase of Environmental and Geographical Attributes  (Horne et al. , 2011) , with the aim of compiling and maintaining a metadatabase of regional non-marine ostracod databases. It is important to understand that OMEGA is not a merging of databases to form a "super-database". A metadatabase contains data about databases, and in this sense OMEGA might simply be a database of existing databases that contain information on ostracod ecology and distribution in different parts of the world.
However, the most important data (taxonomic names and coordinates of records) are included as metadata, thus facilitating the mapping and searching of records from all of the contributing databases. Each record in OMEGA is attributed to a source database for which contact details will be supplied. It is hoped that, ultimately, links could be included to facilitate access to the regional databases; a pre-requisite for such a functionality, however, is that all contributing databases should be freely accessible online. The OMEGA metadatabase is therefore more than just a convenient way of locating and accessing other databases, it constitutes a major research tool in its own right, enabling the visualization and analysis of distributions on a global scale. At the time of writing, OMEGA includes metadata (approx.
49,000 records) from NODE, NANODe, DOAD and EANODe as well as other datasets representing southern Africa (supplied by Koen Martens), Australia (supplied by Chris Gouramanis) and China (supplied by Yangmin Qin). A partial dataset of c. 26,000 records compiled from NODE, DOAD and NANODe has been available for download since 2015, but data standards must be applied and very substantial taxonomic harmonization and validation of georeferenced localities remain to be completed before other data can be released  (Horne, 2014).
Neotoma and North American Combined Ostracode Database In 2009, a public access community-curated data resource became available, an international, collaborative database named Neotoma (named for packrats of the genus Neotoma)  (Grimm et al. , 2018; Williams et al. , 2018). Neotoma (www. neotomadb. org) was developed to house, and access independently, cohesive paleoecological datasets of Pliocene through Modern age. The need for such an international resource with data stewards linked to databases and collections was driven by the growing problem, for many researchers, of maintaining funding to sustain and grow independent regional databases. A range of biological data for multi-proxy analysis can be found in Neotoma, including data access to pollen, vertebrates, diatoms and many other proxies for past environments and climates.
These independent datasets retain their cohesiveness and are managed by data stewards associated with the datasets. The entire contents of NANODe and a large subset of DOAD are accessible in Neotoma. For DOAD, 4,053 georeferenced sites at which living ostracods were collected were ported into Neotoma, representing a subset of the 6,719 sites in DOAD (of which many recorded empty shells only). This allows a continental-scale biogeographic view of sites in which living ostracods paired with major ion hydrochemistry and limnologic data can be studied by examining the Canadian and U. S. datasets together. Additionally, numerous paleolimnologic ostracod records of Plio/Pleistocene and Holocene age are also housed in Neotoma. Amalgamated datasets from DOAD and NANODe, forming a North American Combined Ostracode Database (NACODe), were mapped and analyzed by  Curry et al.
Paleobiology Database The PBDB is an occurrence-based paleobiodiversity database, dedicated to fossil data of all time. PBDB collaborates closely with other important databases, e. g. , GBIF (see Section 8), the Neotoma Database (see Section 6. 6. ), iDigBio, Macrostrat, Earth Life Consortium, and ePANDDA API. The freely downloadable data types from PBDB include georeferenced occurrences, specimens and measurements, geological strata, collections, diversity over time, taxa, opinions, and bibliographic references. PBDB relies on its authorized data enterers to enter data that mainly come from the published literature. For example, the top enterers for ostracod data entries are Matthew E. Clapham and John Alroy at the time of writing. Its fossil representation is partially influenced by what taxonomic groups the enterers focus on.
g. , "original spelling", "recombination", "rank change", "misspelling") and name status (e. g. , "belongs to", "synonym of", "nomen nudum"). Thereafter, occurrence data are dynamically linked to the constantly growing taxonomy database, so the taxonomy can be instantly updated. Database users can apply various filters that deal with open nomenclature, taxonomic reidentification, and updates on the accepted names. The taxonomic treatment is fully archived and downloadable. Together with WoRMS and about 100 taxonomic databases, PBDB also supplies its checklist dataset to GBIF (Paleobiology Database, 2021). Collaborating with the GPlates software team  (Müller et al. , 2018) , PBDB has a default plate motion model for calculating the paleocoordinates for data that have present-day coordinates and geological ages.
The previous default model (until 2013) was provided by Christopher Scotese, and it is still available in the PBDB. Database users can toggle between Scotese's model and the current default model (since 2014), which is called the GPlates model  (Wright et al. , 2013)  and is considered preferable in terms of accuracy. PBDB has accumulated over 1. 4 million occurrence records since its foundation in 1998. There are in total over 26,000 records of ostracods (Fig. 5A ), the majority of which are marine ostracods. Ostracoda has fairly good number of occurrences with more than 100 genera in most geological periods but show decreasing numbers of data entries from the Paleozoic (63%) to the Mesozoic (20%) and the Cenozoic (17%) (Fig. 6 ). The most common levels of taxonomic resolution are genus (53%), species (39%), and class (5%).
GBIF GBIF is an intergovernmental collaboration between over 100 official country/economy/organization participants (represented by the "nodes" in GBIF) that coordinate their own institutions and databases (called the "publishers") to share biodiversity data. The publishers share data through Integrated Publishing Toolkits which ensures the application of metadata standards, including Darwin Core and Ecological Metadata Language (see Introduction), on their datasets. Depending on the dataset nature, the publisher can choose from four dataset classes in  GBIF: metadata-only dataset for resources that have not been digitalized, taxonomic checklist, occurrence dataset, and sampling event dataset for data collected in greater details and with some protocol. Ingesting all kinds of data from data publishers, GBIF is the world's largest biodiversity database in terms of partnership and amount of data.
Although GBIF is not designed for paleobiological data, it has ingested occurrence datasets of fossil specimens from databases and museums, e. g. , the Paleobiology Department in the Smithsonian Institution. These data are labeled as fossil specimens, but their geological ages have not been incorporated and their "year" column is blank in GBIF. GBIF has over 376,000 occurrence records of ostracods at the time of writing. Preserved specimens account for ~43% of these records, indicating that museums are the biggest data sources of ostracods in GBIF. Fossil specimens account for ~36% of these records, and the top contributors are PANGAEA, PBDB, Smithsonian National Museum of Natural History, and Natural History Museum London. The rest are mainly labeled as human observation or material sample.
Taxonomic identification and harmonization Regional datasets collected by one person or group may be internally consistent in terms of taxonomy and positional accuracy, but if they are to be utilized in a wider context in combination with other databases, then data standards must be established, and taxonomic harmonization is required. Geographically more extensive, literature-based datasets are likely to cover more of species' full distributions but, since they represent collections by many different people over many years, are more prone to inconsistencies in taxonomy as well as locational precision and accuracy. If publications include illustrations of the identified species, they can be checked and corrected where necessary, paying particular attention to synonyms and generic assignments; if unillustrated, assumptions must be made about the validity of the taxonomic names listed.
The use of open nomenclature, often inconsistently, needs to be dealt with by either new identifications to species level or applying uncertainty filters in the database. In the marine realm, AOD, OBIS, and PBDB display different approaches for taxonomic harmonization, corresponding to their different database scopes and architectures. Our investigation showed that AOD is one unique occurrence-based database that comes with high spatial coverage and fully harmonized taxonomy (albeit for a limited geographical region). This results from its focus on the Arctic ostracods and contribution from the same group of closely collaborated researchers. Taxonomic harmonization is more challenging for OBIS because it is a data harvester that recombines a vast amount of modern and Quaternary datasets from various data publishers at the global scale.
Because occurrence data themselves contain no systematics information, OBIS uses WoRMS as its taxonomic backbone. PBDB also faces a more challenging task in taxonomic quality control, hosting fossil records at a longer geological time scale. It has an internal taxonomy database that uses an objective algorithm to combine authoritative names and taxonomic opinions. For non-marine ostracod databases, the subjective global checklist of extant non-marine ostracod species published by  Meisch et al. (2019)  provides a standard against which all database records can be checked. Taxonomic harmonization efforts are currently focused on northern hemisphere (Holarctic) databases, supported at generic level by the recent publication of keys for the Nearctic  (Smith and Horne, 2016)  and Palaearctic  (Horne et al.
, 2019)  regions. Simple comparisons of species lists from DOAD, NANODe, NODE and EANODe suggest that at least 30 species are common to North America and Europe, and 10 of these are also common to East Asia. However, detailed investigations (in progress) show that while some are truly cosmopolitan, in many cases species listed under the same name turn out to be different species in different regions, while others are listed under different names that could be synonymized. Another good solution is consulting an authoritative taxonomic database for taxonomic identification, taxonomic harmonization, and resolving outdated taxonomy. There is no silver bullet for taxonomic identification, and we will always need specialist expertise to conduct high standard taxonomic identification of ostracods.
Nonetheless, a free, online database can strongly accelerate the traditionally slow work on taxonomic identification, and certainly coordinate updates in taxonomic opinions and consensus. Thanks to Kempf and many database contributors, valuable taxonomic resources have become available for current and future young scientists. The WOD is arguably the most promising platform for resolving the taxonomic challenges discussed above. WOD hosts freely available taxonomic information, descriptions, and illustrations for marine/non-marine and fossil/Recent ostracods. The collaboration between WoRMS and OBIS is an excellent example of how WOD can improve taxonomic quality in occurrence-based databases. Since all kinds of data in WOD are entered by experts, WOD needs more contributions from ostracodologists.
Validation of locality and sediment core section Before they are made more widely available, databases that contain occurrence records should be validated by checking taxonomic and locality data for errors and making corrections where necessary. Most late 20th and 21st century publications provide adequate locality information, often including coordinates, while older literature frequently has shortcomings in this respect. Abstracting occurrence data from European literature for NODE, for example, has encountered many challenges including historical revision of political boundaries and place names, waterbodies from which ostracods were collected in the 19th century that were subsequently drained and no longer exist, and imprecise locality information (such as records from large lakes that do not specify a site within the lake, or small ponds only located by reference to the nearest town or village).
Such issues can make compliance with data standards of integrative systems (e. g. , OBIS, GBIF, Neotoma) very challenging. In preparation for making non-marine ostracod datasets available via the Neotoma and GBIF portals, current efforts are focused mainly on northern hemisphere databases (as with taxonomic harmonization), aided greatly by the growth of internet resources, particularly Google Earth and the online availability of historical maps (e. g. , via Digimap in the UK); this work is time-consuming and for some records the confident assignment of precise coordinates may never be possible, but positional uncertainties of a few km may be considered acceptable when mapping distributions on large regional to global scales. A "traffic-light" system for indicating the validation status of species records, developed for NODE and OMEGA, might usefully be adopted by other database projects: green signifies accurate coordinates, amber denotes coordinates that are acceptable (as good as possible given limitations of the available data; comments may be added in justification, e.
Marine ostracod database and PBDB applications Georeferenced occurrence databases are increasingly utilized in the field of macroecology and biogeography (e. g. ,  Peters and McClennen, 2016; Williams et al. , 2018). OBIS is a promising platform for global marine diversity research. However, our results showed that its ostracod coverage is concentrated in northern hemisphere and coastal areas. It currently provides little help in advancing our understanding of largescale ecological patterns of ostracods. For example, latitudinal diversity gradients have only been recently explored in the North Atlantic, Arctic, and NW Pacific based on the AOD and individual datasets  (Yasuhara et al. , 2009; Yasuhara et al. , 2012; Jöst et al. , 2019; Chiu et al. , 2020). Global analysis of ostracod macroecology and biogeography remains difficult.