dataesr/scientific-paragraphs-categorization huggingface dataset:
Quality control procedure Records considered to be a primary time series for their respective sites (Sect. 4; Table  6 ) were quality-controlled to the highest degree possible, as described below. Primary time series were judged to be the one or two time series upon which the original authors based their main climatic interpretations. For archives such as corals and speleothems, the primary time series are typically a composite of multiple records from a site or the latest of a series of modified records from a site, whereas for other archives the primary time series is one deemed to have the most robust climatic signal (e. g. , for lake sediments, a biomarker of terrestrial vs. mixed terrestrial and aquatic origin). Non-primary time series were qualitycontrolled as much as possible and are included because they may contain valuable information for database users.
Both data and required metadata fields were screened for accuracy and completeness by one or more project members, with the initials of the project member performing the final quality control (QC) check included in the Iso2k_QC_certification metadata field. Metadata fields that required standardized or controlled vocabularies were double-checked to ensure those terms were adhered to (Sect. 4). During the quality control certification process, project members used a web-based data viewer (lipdverse. org) and other visualization tools to display the raw data and metadata. Each metadata field in the database (Tables  1 2 3 4 5 6 7 ) has a quality control certification "Level" from 1 to 3, defined as follows. -Level 1 fields are required metadata for inclusion in the Iso2k database. These fields are generalizable enough to be suitable for all archive types, and they are recommended as primary fields for filtering, sorting, and querying records in the database.
Level 1 required fields were subject to the highest QC standard. They follow standardized Iso2k vocabularies, where appropriate (Table  7 ); geographical data were checked against maps, and interpretation fields were checked against the original publication. Examples of Level 1 metadata include geographical  (ISO 19115)  and publication information (DOI), and the minimum required subset of isotope and proxy system interpretation metadata fields (see Sect. 4). -Level 2 fields are highly useful (but not required) metadata fields in the Iso2k database. They may be used as secondary fields for further filtering, sorting, and querying records in the database; these fields may be particularly useful for certain archives or to refine interpretations after an analysis has been performed. Examples of Level 2 fields include species name (marine and lake sediments and corals) and compound chain length for compound-specific δ 2 H measurements (lake sediments).
Terminology was standardized only where necessary and appropriate. In other cases, these fields contain freeform text with direct quotes from the original publications. During the QC certification process these fields were checked against the original publication for clarity and consistency. -Level 3 fields may be useful to some users of the Iso2k database but are not generally recommended as fields for filtering and sorting records in the database. Level 3 fields are not entered as standardized vocabularies and the information is sometimes not available in the original publications (thus, these fields are blank for many records). Examples of Level 3 fields include information pertaining to the integration time of a proxy sensor. -Automatic fields are the automatically generated fields that were computed directly from the data records following QC certification.
Archive types within the Iso2k database The Iso2k database contains data from a variety of geological and biological archives. Following proxy system terminology  (Evans et al. , 2013) , each archive has one or more sensors that directly sense and incorporate environmental signals, i. e. , the δ 18 O and δ 2 H of environmental waters, into their structures. Over time these sensors then form, are deposited into, or are otherwise imprinted upon an archive that is then subsampled and subjected to isotopic measurements or observations. In this section, we describe the key characteristics of the archives and sensors that are important for the https://doi. org/10. 5194/essd-12-2261-2020 Earth Syst. Sci. Data, 12, 2261 Data, 12, -2288 Data, 12, , 2020  interpretation of the paleohydrological signals that they preserve.
Corals, sclerosponges, and mollusks Corals, sclerosponges, and mollusks (predominantly bivalves and gastropods) form hard body parts of calcium carbonate (aragonite or calcite) that record the conditions of the aquatic environment in which they live (see  Black et al. , 2019; Corrège, 2006; Druffel, 1997; Evans et al. , 2013; Lough, 2010; Sadler et al. , 2014; Surge and Schöne, 2005). Further, except for sclerosponges (which are dated using U/Th geochronology), these aquatic carbonates contain annual banding structures, enabling precise chronology development. Reef-building corals represent the bulk of annually resolved marine archives included in the Iso2k database. These corals are distributed in warm shallow waters throughout the tropical oceans, whereas sclerosponges (i. e. , coralline sponges or Demospongiae) and mollusks are found worldwide, the latter in both estuarine and freshwater environments.
, 2012; Carré et al. , 2019). Coral δ 18 O and δ 13 C contain a vital effect and coral δ 18 O is offset from δ 18 O w , whereas mollusk and sclerosponge δ 18 O is generally precipitated in equilibrium with environmental water. Some coral δ 18 O records in the Iso2k database have had their mean δ 18 O removed by the original authors for comparison and cross-dating with other coral records, and this is noted in the metadata.
Glacier ice Climate records from glacier ice are found primarily at high latitudes (Antarctica, Arctic) and high elevations (e. g. , Andes, Himalayas)  (Eichler et al. , 2009; Meese et al. , 1994). Glacier ice is formed from the accumulation of snow, which over time compacts into a section of chronologically continuous layered ice. Cores drilled through layers of glacier ice preserve sub-annually to centennially resolved climate information, with resolution varying among records due to snow accumulation rates and laboratory sampling and analysis methods  (Rasmussen et al. , 2014). Ice cores are dated through a variety of methods; annual layer counting and alignment to volcanic horizons are the most common approaches for records spanning the CE  (Sigl et al. , 2014). This database contains records of δ 18 O, δ 2 H, and/or d-excess of glacier ice.
Description of Iso2k metadata fields The Iso2k database contains over 180 metadata fields. The 55 main fields are described in Tables 1-6; 23 of these were strictly quality-controlled following the Level 1 definition in Sect. 2. 4. Entries for some required metadata fields were standardized with controlled vocabulary to allow users to easily query the database for records based on archive type, isotope ratio (O or H), waters from which the isotope ratios are derived, materials on which the isotope ratios were measured, or the environmental parameter that controls isotopic variability (Fig. 1 ). Metadata fields describe the primary isotopic variable being inferred, i. e. , the "isotope interpretation" (e. g. , the δ 2 H of precipitation); the water from which it was inferred, i. e. , "inferred material" (e.
g. , soil water); the material that was actually measured, i. e. , "measured material" (e. g. , long-chain n-alkane components of leaf waxes); and information about the original climate interpretation. Distinctions between the archive type (Fig. 2 ), inferred material (Fig. 3 ), and the isotope interpretation (Fig. 4 ) allow for advanced analyses and straightforward data-model comparisons using the database. These metadata interpretation fields were derived from interpretations reported in the original publications. Below and in Tables 1-6, we describe key metadata fields in the database, including all Level 1 and Level 2 fields (see Sect. 2. 4 for a description of levels). Table 7 provides standardized vocabularies and common terminologies. Table  8  provides selected chronological control metadata.
Entity metadata The entity metadata fields provide basic information for each record, including the isotope measured, the archive type, location (longitude, latitude, and elevation), start and end dates of each record, and both the DOI and citation for the original publication. Entries for the archiveType, pale-oData_variableName, and paleoData_units metadata fields are standardized (Table  7 ) across all archive types to facilitate easy querying and analyses. Each record is assigned a unique LiPD identifier, and all isotope records are assigned a unique Iso2k identifier. The alphanumeric Iso2k identifiers contain 11 characters and digits as follows: archive type (2 char-  acters), year published (2 digits), first author's last name (2 characters), site name (2 characters), sample number (e.
g. , 00, 01, 02, 03. ) for different cores or core composites from the same site, and letter (A, B, C. ) for multiple time series derived from the same core. The paleoData_variableName indicates the variable measured for each archiveType, usually δ 18 O or δ 2 H. In some cases other paired geochemical measurements are included in the database to complement interpretation of the isotopic data (Sect. 2. 3. 4). A list and detailed description of key entity metadata fields is provided in Table  1.
Paleodata metadata The paleodata metadata fields provide information for each proxy record; a detailed description of key paleodata metadata fields is provided in Table  2. Measured and derived water isotope time series are identified using the paleo-Data_variableType and paleoData_description fields and should not be confused with the isotope interpretation metadata fields (Sect. 4. 3), which more broadly refer to the way each proxy record is interpreted (e. g. , speleothem carbonate interpreted as a proxy for the δ 18 O of precipitation). The variable description (paleoData_description) is the general category of material that was measured for its isotopic ratio (e. g. , carbonate or terrestrial biomarker). Further details.
Dataset DOI datasetDOI Digital object identifier for dataset assigned 3 by original authors if available. Dataset URL paleoData_WDSPaleoUrl URL linking back to records obtained from 3 the NOAA NCEI data repository are given by measurementMaterial, which is a more specific description of what was measured (e. g. , coral, glacier ice, lake sediment), and measurementMaterialDetail, which provides further specificity of the measurementMaterial, such as mineral, species, or compound. In contrast, the inferredMaterial field indicates the environmental source waters whose isotope variability is inferred (e. g. , precipitation, lake water, groundwater) (Fig. 1 ). The environmental source waters in the inferredMaterial field are not meant to be highly specific (e. g. , intracellular leaf water) but are instead broad pools of environmental waters that have direct analogs or counterparts in climate models.
All isotope interpretation fields in the database are prefaced by isotopeInterpretation. The iso-topeInterpretation1_variable field lists the primary driver of isotopic variability in the environmental source waters according to the original publications, for example air temperature or relative humidity (Table  7 ). For records where multiple variables can explain some fraction of the variability, the isotopeInterpretation2 and isotopeInterpretation3 fields are also populated. The isotopeInterpretation1_direction is a field that gives the sign (positive or negative) of the relationhttps://doi. org/10. 5194/essd-12-2261-2020 Earth Syst. Sci. Data, 12, 2261 Data, 12, -2288 Data, 12, , 2020  ship between the isotope measurements and the environmental variable. The isotopeInterpretation1_variableGroup field is a simplified super-grouping of terms in the isotopeInterpreta-tion1_variable field in order to facilitate comparisons across different archives and realms, with three options (temperature; isotopic composition of precipitation, i.
e. , "P_isotope"; or effective moisture). Controlled vocabulary for metadata fields isotopeInterpretation1_variable and isotopeInterpre-tation1_variableGroup are standardized across all archive types (Table  7 ). The isotope interpretation metadata fields reflect the isotope systematics of the environmental source waters and as such are distinct from the climatic inferences that one can make from a proxy record (Sect. 4. 4). In some publications, this distinction is explicitly spelled out. For example, the cave drip water that becomes incorporated into the δ 18 O of speleothem carbonate in Borneo reflects the δ 18 O of water mixed throughout an aquifer system over many months, which ultimately reflects a smoothed version of precipitation δ 18 O  (Moerman et al. , 2014). In that case, the inferred-Material is soil and groundwater and the isotopeInterpreta-tion1_variable is δ 18 O precipitation ("P_isotope").
Climate interpretation metadata In contrast to the isotope interpretation (Table  3 ), climate interpretation metadata (Table  4 ) represent the original authors' expert judgment about the primary climatic controls on the isotope ratios at their study site. Climate interpretation metadata specify either climatic variables (e. g. , temperature, precipitation amount) or processes (e. g. , the Pacific Decadal Oscillation, Asian monsoon intensity) that the authors interpreted to influence the isotopic composition of the proxy record, and as such they are neither standardized nor quality-controlled. These metadata are included as useful background information but should not serve as a primary filter for users of the Iso2k database. A user might filter records based on the isotope interpretation field, then check the climate interpretation field for a qualitative understanding of which climatic processes may be important for the filtered set of records.
Queryable and standardized metadata To make the database more user-friendly and queryable, some metadata fields contain logical flags (e. g. , 0 or 1, true or false), cross-links (e. g. , to a corresponding record ID in another PAGES 2k database), or geographic labels (e. g. , continent or ocean basin) that allow for easy sorting (Table  6 ). For example, if a record was included in the PAGES 2k temperature database and reconstructions  (Abram et al. , 2016; Kaufman, 2014; PAGES 2k Consortium, 2017; Stenni et al. , 2017; Tierney et al. , 2015) , that record is cross-linked to its associated PAGES 2k ID wherever possible, permitting easy database query and analysis of records in only one database and those common to both databases. Approximately 15 % of the records in the Iso2k database were also incorporated into other PAGES 2k compilations, with the most overlap occurring in coral records and high-latitude ice cores.
Fraction isotopeinterpretation1_fraction Fraction of variance explained by 2 given climate variable. an age model and the average temporal resolution for each isotope record. For non-annually banded records, age-depth models and radiometric dating information (Table  8 ) are included where available to facilitate independent age modeling. This information is stored in "chronData" tables that are linked to the measured data ("paleoData") tables. If a record has raw chronology data in the database (e. g. , radiometric age determinations), hasChron is set to 1; otherwise this parameter is 0. Similarly, if sample depth data are available (e. g. , core depth), hasPaleoDepth is set to 1. To support the information implicit within each record's age-depth model, chronological metadata are provided for all individual age constraints (when available) and these metadata are summarized in Table  8.
Where applicable, we provide the https://doi. org/10. 5194/essd-12-2261-2020 Earth Syst. Sci. Data, 12, 2261-2288, 2020 isotope activity and the activityUncertainty. For 210 Pb measurements, the supportedActivity field is Y if the activity is supported by 210 Pb production in the surrounding matrix and N if the activity is not supported. The x210PbModel describes the type of model used to determine the age based on the radiogenic isotope measurements. For carbonate systems such as speleothems and corals, U/Th dating is often used. Where available, chronological tables in the database contain information about the 238 U and 232 Th content (U238, Th232), the 230 Th/ 238 U activity ratio (Th230_U238activity), δ 234 U(d234U), and their uncertainties (U_Thactivity_error and d234U_error). Fields such as the initial 234 U/ 238 U (dU234intial) and 230 Th/ 232 Th activity ratios (Th230_Th232ratio) are also included for correcting ages for the initial 234 U/ 238 U activity and detrital thorium contamination, respectively.
Spatial, temporal, archival, and isotopic characteristics of data coverage The Iso2k database contains 759 stable isotope (δ 18 O, δ 2 H, d-excess) records from 506 unique sites. There are 10 archive types, including 143 records from annually banded skeletal carbonate marine archives, i. e. , corals (n = 137), sclerosponges (n = 4), and mollusks (n = 2); 210 from glacier ice (n = 206) and ground ice (n = 4); 158 from lake or terrestrial sediments; 99 from marine sediments; 68 from speleothems; and 81 from wood (Fig. 2a ). A total of 87 % of the 759 stable isotope records in the database are δ 18 O, and 13 % are δ 2 H, with 12 sites (∼ 2 %) having records of both isotope systems (derived from the same sensor in ice cores or different sensors in lake sediments). In addition to the 759 stable isotope records, the database contains 255 records containing ancillary data (e.
g. , δ 13 C, Mg/Ca, Sr/Ca). Of the 759 records, 606 are considered "primary" δ 18 O, δ 2 H, d-excess time series (Fig. 2 , Table  S1  in the Supplement, and Sect. 2. 4), including 101 records from annually banded skeletal carbonate marine archives, i. e. , corals (n = 95), sclerosponges (n = 4), and mollusks (n = 2); 170 from glacier ice (n = 166) and ground ice (n = 4); 114 from lake or terrestrial sediments; 95 from marine sediments; 47 from speleothems; and 79 from wood. Spatial coverage of the sites in the database is global, but most sites are from low latitudes and Northern Hemisphere midlatitudes (Figs. 2a  and 4b ). Data availability is low for most of the Southern Hemisphere, with the exception of glacier ice records from Antarctica (Fig. 4b ). The temporal coverage increases from about 250 proxy time series near the year 0 CE to more than 400 time series at the beginning of the 20th century (Fig.
These lower-resolution time series almost exclusively make up the records in the database prior to ∼ 1700 CE, preventing the characteristic drop in coverage in older time periods observed in and described by other PAGES 2k compilations  (PAGES 2k Consortium, 2013). The records in the Iso2k Database capture many aspects of hydroclimate (Fig. 4 ). The first-order interpretation (iso-topeInterpretation1_variable) for 44 % of the δ 18 O and δ 2 H records in the database is "P_isotope", meaning that δ 18 O and δ 2 H of the inferred material (ice, soil water, seawater, etc. ) is primarily driven by the δ 18 O and δ 2 H of precipitation. The first-order interpretation for 26% of the records in the database is "T_water" or "T_air", meaning that the temperature of water or air is the primary driver of δ 18 O and δ 2 H of the inferred material.
Finally, 24 % of records in the database are primarily driven by some aspect of evaporation or evapotranspiration, collectively referred to as "effective moisture" in the isotopeInterpretation1_variableGroup category. This category includes "d18O_seawater" (driven by ocean circulation and by precipitation/evaporation at the sea surface), "ET" (evapotranspiration), "I_E" (infiltration / evaporation), and "P_E" (precipitation / evaporation) entries for isotopein-terpretation1_variable.
Validation There is currently no existing observational dataset of isotope ratios in all major pools of the water cycle that can serve as a true validation of the Iso2k database. However, the vast majority of ice records in the Iso2k database have an inferred material of "precipitation" and a first-order isotope interpretation of "P_isotope". For these records, the δ 18 O averaged for the 20th century (all data points after 1900 CE) provides a reasonable match with the observed annual average δ 18 O of precipitation from the Global Network of Isotopes in Precipitation (GNIP)  (Terzer et al. , 2013)  (Fig. 5 ). This provides confidence that the isotopic data contained in the Iso2k database can reasonably be used for analyses such as the calculation of latitudinal gradients in δ 18 O over the CE, even   before accounting for seasonal biases and other transformations within the proxy system.
We note that while other proxy data types such as speleothems and leaf wax biomarkers are sensitive to P_isotope (and isotopeinterpretation1_variable for many of these records is listed as "P_isotope"; Fig. 4 ), their most direct inferred materials are meteoric waters such as soil water or groundwater rather than precipitation; further, water isotope values are fractionated by proxy sensors, such that they are not as directly comparable to the GNIP database. 6 Usage notes.
General applications The Iso2k database is the most comprehensive database of paleo-water isotope records to date for the CE. For the first time, this database allows for the investigation of spatial and temporal hydroclimate variability from regional to global scales across multiple proxy systems. Using the "inferred material" metadata, the database can be directly compared with the output of climate models, allowing investigation of the water cycle in far greater depth than was previously possible. Alongside the data itself, the detailed "isotope interpretation" metadata fields are the foundation of this database. These fields allow users to understand the processes reflected in the isotope data and filter the database according to particular scientific questions. For example, a user may be interested in the temporal variability of isotope records driven primarily by changes in effective moisture, and the Iso2k standardized vocabulary means that it is straightforward to filter for these records.
Example workflow for filtering and querying data records Records in the Iso2k database are provided as published (i. e. , not recalibrated or validated). This preserves the large amount of information contained within water isotope proxy measurements that would be lost if condensed to reconstruct discrete variables. Rather, we leave it to the database users to filter and assess records as needed. The MATLAB and R serializations contain three variables: "D", "TS", and "sTS". The variable D includes sitelevel data for each dataset structured in the LiPD format. Datasets in D often contain multiple variables (e. g. , stable isotope, ancillary, and chronological data), and represent how LiPD data appear when loaded into the initial environment. For most users, however, a "flattened" version of the database is more useful.
We have provided this as the TS variable, where each entry contains an individual time series and its associated metadata. A slightly modified version of TS is included with R and MATLAB, called sTS, which is identical to TS except that the interpretation fields are split by scope ("isotope" or "climate") in order to simplify querying, which may be preferable for some users. The Python serialization contains only D and TS because tools to split by scope were unavailable. For initial querying of the database, in nearly all cases, we recommend first filtering by the following variables: 1. variableName = "d18O" or "d2H" (excludes any nonisotopic data); 2. paleoData_units = "permil" (excludes records published as z scores or anomalies); 3. paleoData_iso2kPrimaryTimeseries = "TRUE" (includes only primary time series for each site).