Radiocarbon measurements on core tops from the Ontong-Java plateau confirm a previous finding by Berger and Killingley [1982] that at any given water depth, cores taken on the equator have higher accumulation rates and younger core top ages than their off-equator counterparts. Further, these new results fortify the conclusion by Broecker et al. [1991] that the increase in core top radiocarbon age with water depth rules out homogeneous dissolution within the pore waters as the dominant mechanism. Either most of the dissolution must occur prior to burial or it must occur during the first pass through the respiration-CO2-rich upper pore waters after which the calcite grains become armored against further dissolution. A puzzling aspect of this new data set is that despite the sizable difference in accumulation rate, the extent of dissolution as measured by either the CaCO3 content or the ratio of CaCO3 in the >150-µm size fraction to that in the < 63-µm fraction is no different off than on the equator. In order to reconcile the results of this study with those obtained by Hales and Emerson [1996] using in situ electrodes, it is necessary to call upon calcite armoring.

No description is available. Visit https://dataone.org/datasets/113a06b5516f29f80ae35630bc5772ef for complete metadata about this dataset.

No description is available. Visit https://dataone.org/datasets/863fd58383f799c99c8cac490ac49b21 for complete metadata about this dataset.

This is a dataset about the usage of properties and datatypes in the Web Data Commons RDFa, Microdata, Embedded JSON-LD, and Microformats Data Sets (October 2016) based on the Common Crawl October 2016 archive. The dataset has been produced using the RDF Property and Datatype Usage Scanner v2.1.1, which is based on the Apache Jena framework. Only RDFa and embedded JSON-LD data were considered, as Microdata and Microformats do not incorporate explicit datatypes.

Dataset Properties

• Size: 17.4 MiB compressed, 351.1 MiB uncompressed, 1 612 479 rows plus 1 head line determined using gunzip -c measurements.csv.gz | wc -l
• Parsing Failures: The scanner failed to parse 28 326 152 triples (~0.69 %) of the source dataset (containing 4 097 655 302 triples).
• Content:
  • CATEGORY: The category (html-embedded-jsonld or html-rdfa) of the Web Data Commons file that has been measured.
  • FILE_URL: The URL of the Web Data Commons file that has been measured.
  • MEASUREMENT: The applied measurement with specific conditions, one of:
    • UnpreciseRepresentableInDouble: The number of lexicals that are in the lexical space but not in the value space of xsd:double.
    • UnpreciseRepresentableInFloat: The number of lexicals that are in the lexical space but not in the value space of xsd:float.
    • UsedAsDatatype: The total number of literals with the datatype.
    • UsedAsPropertyRange: The number of statements that specify the datatype as range of the property.
    • ValidDateNotation: The number of lexicals that are in the lexical space of xsd:date.
    • ValidDateTimeNotation: The number of lexicals that are in the lexical space of xsd:dateTime.
    • ValidDecimalNotation: The number of lexicals that represent a number with decimal notation and whose lexical representation is thereby in the lexical space of xsd:decimal, xsd:float, and xsd:double.
    • ValidExponentialNotation: The number of lexicals that represent a number with exponential notation and whose lexical representation is thereby in the lexical space of xsd:float, and xsd:double.
    • ValidInfOrNaNNotation: The number of lexicals that equals either INF, +INF, -INF or NaN and whose lexical representation is thereby in the lexical space of xsd:float, and xsd:double.
    • ValidIntegerNotation: The number of lexicals that represent an integer number and whose lexical representation is thereby in the lexical space of xsd:integer, xsd:decimal, xsd:float, and xsd:double.
    • ValidTimeNotation: The number of lexicals that are in the lexical space of xsd:time.
    • ValidTrueOrFalseNotation: The number of lexicals that equal either true or false and whose lexical representation is thereby in the lexical space of xsd:boolean.
    • ValidZeroOrOneNotation: The number of lexicals that equal either 0 or 1 and whose lexical representation is thereby in the lexical space of xsd:boolean, and xsd:integer, xsd:decimal, xsd:float, and xsd:double.
    Note: Lexical representation of xsd:double values in embedded JSON-LD got normalized to always use exponential notation with up to 16 fractional digits (see related code). Be careful by drawing conclusions from according Valid… and Unprecise… measures.
  • PROPERTY: The property that has been measured.
  • DATATYPE: The datatype that has been measured.
  • QUANTITY: The count of statements that fulfill the condition specified by the measurement per file, property and datatype.

Preview

"CATEGORY","FILE_URL","MEASUREMENT","PROPERTY","DATATYPE","QUANTITY"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://schema.org/aggregateRating","http://www.w3.org/2001/XMLSchema#string","36"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://opengraphprotocol.org/schema/longitude","http://www.w3.org/2001/XMLSchema#string","1137"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://ogp.me/ns#title","http://www.w3.org/2001/XMLSchema#string","3"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://ogp.me/nslongitude","http://www.w3.org/2001/XMLSchema#string","1"
"html-rdfa","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-rdfa.nq-00000.gz","UnpreciseRepresentableInDouble","http://ogp.me/ns#latitude","http://www.w3.org/2001/XMLSchema#string","884"
[…]
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-embedded-jsonld.nq-00294.gz","ValidZeroOrOneNotation","http://schema.org/minPrice","http://www.w3.org/2001/XMLSchema#integer","12"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-embedded-jsonld.nq-00294.gz","ValidZeroOrOneNotation","http://schema.org/highPrice","http://www.w3.org/2001/XMLSchema#integer","1"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-embedded-jsonld.nq-00294.gz","ValidZeroOrOneNotation","http://schema.org/numberOfItems","http://www.w3.org/2001/XMLSchema#integer","44"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-embedded-jsonld.nq-00294.gz","ValidZeroOrOneNotation","http://schema.org/ratingValue","http://www.w3.org/2001/XMLSchema#integer","139"
"html-embedded-jsonld","http://data.dws.informatik.uni-mannheim.de/structureddata/2016-10/quads/dpef.html-embedded-jsonld.nq-00294.gz","ValidZeroOrOneNotation","http://schema.org/width","http://www.w3.org/2001/XMLSchema#integer","76"

Note: The data contain malformed IRIs, like "xsd:dateTime" (instead of probably "http://www.w3.org/2001/XMLSchema#dateTime"), which are caused by missing namespace definitions in the original source website.

Reproduce

To reproduce this dataset checkout the RDF Property and Datatype Usage Scanner v2.1.1 and execute:

mvn clean package
java -jar target/Scanner.jar --category html-rdfa --list http://webdatacommons.org/structureddata/2016-10/files/rdfa.list October2016
java -jar target/Scanner.jar --category html-embedded-jsonld --list http://webdatacommons.org/structureddata/2016-10/files/html-embedded-jsonld.list October2016
./measure.sh October2016
# Wait until the scan has completed. This will take a few days
java -jar target/Scanner.jar --results ./October2016/measurements.csv.gz October2016

Overview

These datasets contain the results from a performance comparison between Java and OpenCL/CPU implementations of the PPHPC model.

The datasets are used in the following study:

Fachada, N. and Rosa, A.C., Assessing the feasibility of OpenCL CPU implementations for agent-based simulations. IWOCL 2017: Proceedings of the 5th International Workshop on OpenCL, Article No. 4, 2017, https://doi.org/10.1145/3078155.3078174

Experiment reproducibility

The datasets were generated with the java.sh and cpu_l1.sh scripts under the following versions of the supporting software:

• cf4ocl v2.1.0
• cl_ops v0.2.0
• PPHPC, branch opencl, commit c17705882418 (release build, profiling off)
• OpenCL:
  • Intel (CPU): OpenCL Runtime 16.1.1 for Intel(R) Core(TM) and Intel(R) Xeon(TM) Processors for Ubuntu (64-bit) reported driver version: 1.2.0.25)
  • AMD (CPU): APP SDK 3.0 for 64-bit Linux (reported driver version: 1800.8)

Hardware and operating system:

• Intel Xeon CPU E5-2650 v3 @ 2.30GHz (ten cores, two logical processors per core), 64GB RAM
• Ubuntu 16.04.1 LTS

Licenses

The datasets are made available under a CC-BY 4.0 license (see LICENSE_DATA.txt).

The shell scripts and performance/statistical analysis scripts are made available under the MIT license (see LICENSE_SCRIPTS.txt).

List of topics extracted by the Python implementation of the LDA algorithm. The list of files is as follows:android-gpuimage => 51.datansj_seg => 52.datarrow => 53.datatmosphere => 54.datautorest => 55.datblurkit-android => 56.datbytecode-viewer => 57.datcglib => 58.datdagger => 59.datExpectAnim => 60.datgraal => 61.datgraphql-java => 62.dathalo => 63.datHikariCP => 64.dathttp-request => 65.datinterviews => 66.datjava-learning => 67.datJava-WebSocket => 68.datjeecg-boot => 69.datjeesite => 70.datJFoenix => 71.datjna => 72.datjoda-time => 73.datjodd => 74.datJsonPath => 75.datjunit4 => 76.datlibrec => 77.datlight-task-scheduler => 78.datmal => 79.datmall => 80.datmosby => 81.datmybatis-plus => 82.datnanohttpd => 83.datNullAway => 84.datparceler => 85.datPermissionsDispatcher => 86.datPhoenix => 87.datquasar => 88.datrequery => 89.datretrofit => 90.datretrolambda => 91.datSentinel => 92.datsimplify => 93.datswagger-core => 94.dattcc-transaction => 95.datsymphony => 96.dattestcontainers-java => 97.datUltimateRecyclerView => 98.datweixin-java-tools => 99.datwire => 100.dat

The paleoceanographic potential of coccolithophores was used to decipher the paleoproductivity changes in the eastern Indian Ocean during the past 300,000 years. Core SO139-74KL was taken at the seaward limit of a fore-arc basin of the Indonesian continental shelf located beneath the Java upwelling system. Coccolithophores occur in all samples, and total coccolith concentration exhibit distinct variations over the entire section. Peak abundances occur every 20,000 to 25,000 years with the highest peak at isotope stage 7. Abundances increase during the glacials but peak abundances also occur during interglacials. The preservation of coccoliths is good to moderate in most of the samples. The most abundant species is Florisphaera profunda with a mean relative abundance of 41.5% followed by Gephyrocapsa ericsonii and Emiliania huxleyi (EhuxGeric) and Gephyrocapsa oceanica. These four taxa dominate the assemblage throughout the core, forming on average 90.5% of the total assemblage. The species composition suggests that warm tropical conditions prevailed throughout the investigated time period indicating that temperature was not the driving force for the assemblage variations at this site. The geologic record for present-day and Holocene oceanographic conditions seemed to be predominantly characterised by high productivities in combination with an unstable water column. Indications for oligotrophic open ocean conditions were sparse. However, during most of the year oligotrophic conditions prevail and upwelling recurs only for a short time period but upwelling indicating proxies dominate the geological record. A contrasting fully oligotrophic scenario characterised by peaks in the abundances of total coccolithophores, Umbellosphaera irregularis, and in the percentage ratio of EhuxGeric to G. oceanica can be seen with a periodical recurrence every 20,000 to 25,000 years. Synchronously the records of the high productivity indicators total organic carbon and G. oceanica are characterised by distinct minima. We believe that upwelling was totally cut off during these times and oligotrophic conditions with a pronounced water column stratification prevailed throughout all seasons. An obvious correspondence between the shut down times of upwelling and insolation minima suggests that surface water conditions were driven by orbital forcing.

No description is available. Visit https://dataone.org/datasets/2945d7725b6f44a38788993a29751465 for complete metadata about this dataset.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoceanography. The data include parameters of paleoceanography with a geographic location of Western Pacific Ocean. The time period coverage is from 5180 to 2760 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

EBSDinterp is a GUI-based Matlab program to perform microstructurally constrained interpolation of electron backscatter diffraction (EBSD) datasets. The dataset in this collection comprises ASCII Channel Text Files (.ctf) of the raw and processed datasets used in the publication describing EBSDinterp. The dataset contains EBSD data of a twinned plagioclase grain that has been deformed under greenschist facies conditions. Also included are the logfiles written out by EBSDinterp on completion of the data interpolation that describes the parameters used in the interpolation of the dataset. Lineage: Data were collected using a Philips XL30 W-filament SEM using HKL Channel 5 Flamenco software. Imported into EBSDinterp and processed with the parameters described in the corresponding logfiles. Datasets were exported from Channel 5 as ASCII Channel text files (.ctf) for archiving.

The XBT/CTD pairs dataset (Version 1) is the dataset used to calculate the historical XBT fall rate and temperature corrections presented in Cowley, R., Wijffels, S., Cheng, L., Boyer, T., and Kizu, S. (2013). Biases in Expendable Bathythermograph Data: A New View Based on Historical Side-by-Side Comparisons. Journal of Atmospheric and Oceanic Technology, 30, 1195–1225, doi:10.1175/JTECH-D-12-00127.1.
http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-12-00127.1

4,115 pairs from 114 datasets were used to derive the fall rate and temperature corrections. Each dataset contains the scientifically quality controlled version and (where available) the originator's data. The XBT/CTD pairs are identified in the document 'XBT_CTDpairs_metadata_V1.csv'. Note that future versions of the XBT/CTD pairs database may supersede this version. Please check more recent versions for updates to individual datasets. Lineage: Data is sourced from the World Ocean Database, NOAA, CSIRO Marine and Atmospheric Research, Bundesamt für Seeschifffahrt und Hydrographie (BSH), Hamburg, Germany, Australian Antarctic Division. Original and raw data files are included where available. Quality controlled datasets follow the procedure of Bailey, R., Gronell, A., Phillips, H., Tanner, E., and Meyers, G. (1994). Quality control cookbook for XBT data, Version 1.1. CSIRO Marine Laboratories Reports, 221. Quality controlled data is in the 'MQNC' format used at CSIRO Marine and Atmospheric Research. The MQNC format is described in the document 'XBT_CTDpairs_descriptionV1.pdf'. Note that future versions of the XBT/CTD pairs database may supersede this version. Please check more recent versions for updates to individual datasets.

Indonesia Consumer Price Index (CPI): West Java: Education: Basic and Early Age Education data was reported at 126.730 2018=100 in Dec 2023. This stayed constant from the previous number of 126.730 2018=100 for Nov 2023. Indonesia Consumer Price Index (CPI): West Java: Education: Basic and Early Age Education data is updated monthly, averaging 121.700 2018=100 from Dec 2019 (Median) to Dec 2023, with 49 observations. The data reached an all-time high of 126.730 2018=100 in Dec 2023 and a record low of 114.180 2018=100 in Dec 2019. Indonesia Consumer Price Index (CPI): West Java: Education: Basic and Early Age Education data remains active status in CEIC and is reported by Statistics of Jawa Barat Province. The data is categorized under Indonesia Premium Database’s Inflation – Table ID.IB012: Consumer Price Index: by Province: West Java.

This dataset comprises data created during research on AI-generated code, with a focus on software engineering use-cases. The purpose of the research was to investigate how AI should be integrated into university software engineering curricula. The seven core areas of the research include: An analysis of AI and student-written Java code, an analysis of AI and human-written Python code, the results of predictions made “by eye” to distinguish between AI and student-written code, experiments to determine the capabilities of ChatGPT, individual students' feedback on experiences with ChatGPT, a set of guidelines and detailed experiences with AI tools, and the results of a survey of students regarding the use of AI tools.

Core data elements of the AIH and APAC datasets.

This lab focusses on introducing the fundamentals needed to use the GEE API. This lab introduces fundamental terms in GEE and provides guidance through several basic tasks. At the end of this lab you will be able to use GEE to perform the following tasks: • Run basic Java commands. • Display and clip image and vector. • Composite and mosaic images. • Explore image collections and their metadata. • Filter image collections. • Perform simple image band calculations. • Explore and construct functions and map these functions over an image collection. • Import and export raster and vector. • Construct simple graphs based on a set of images e.g. change in vegetation index over time.

We present a reconstruction of deep-water carbonate saturation state (Delta [CO3]2-) in the western equatorial Pacific for the Last Glacial Maximum (LGM) and deglaciation based on changes in the Mg/Ca ratio of planktic foraminifers with increased water depth. Our data suggest there have been changes in bottom waterDelta [CO3]2- over the past 25,000 years at water depths as shallow as 1.6 km. The Delta [CO3]2- reconstruction for the LGM suggests Delta [CO3]2- was similar or slightly higher than modern values between 1.6 and 2.0 km, shifting sharply to lower values (an average ~30 µmol/kg lower) below 2.5 km. The shift in chemistry between 2.0 and 2.5 km supports a hypothesis that Pacific overturning circulation occurred deeper during the LGM with a slightly more ventilated water mass above 2.0 km. The data are not consistent with enhanced preservation in this region of the deep Pacific at depths greater than 2.5 km, suggesting that the long-held view of better preservation throughout the glacial deep Pacific must be reevaluated. For the deglaciation, we have evidence of a Delta [CO3]2- maximum that suggests enhanced deglacial preservation between 1.6 and 4.0 km in comparison to the Holocene and the LGM. The deglacial Delta [CO3]2- was as much as 28 µmol/kg higher than modern between 1.6 and 4.0 km. Results suggest carbonate burial rates were 1.5 times greater during the deglacial than the over the past 5 kyr. Measured on Globigerinoides sacculifer. The radiocarbon age was converted to calendar age by first adjusting ages for the estimated reservoir age for this region (256 years) and then converting to calendar age using the online calibration tool located at http://radiocarbon.ldeo.columbia.edu/research/radcarbcal.htm (Fairbanks et al, 2005).

Indonesia Gross Domestic Product (GDP): SNA 2008: Annual: Central Java: Manufacturing Industry: Basic Metals data was reported at 3,408.000 IDR bn in 2018. This records an increase from the previous number of 3,346.000 IDR bn for 2017. Indonesia Gross Domestic Product (GDP): SNA 2008: Annual: Central Java: Manufacturing Industry: Basic Metals data is updated yearly, averaging 3,125.000 IDR bn from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 3,408.000 IDR bn in 2018 and a record low of 1,981.446 IDR bn in 2010. Indonesia Gross Domestic Product (GDP): SNA 2008: Annual: Central Java: Manufacturing Industry: Basic Metals data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s National Accounts – Table ID.AF014: Gross Domestic Product: By Industry: Central Java.

In 1977 the R.V. Valdivia carried out a survey between Scott Plateau and the Java Trench, during which 1700 km of 24-channel seismic data, and 2550 km of bathymetric, gravity and magnetic data, were recorded; and 31 bottom samples were obtained, in water depths ranging from 2000 m to 5800 m. The Scott Plateau trends NNE and is bounded to the west by the Argo Abyssal Plain and to the north by the Roti Basin. The plateau is a foundered continental block, and lies at an average depth of 2000-3000 m. On the plateau the dominant fault direction is NW to WNW, an ancient strike direction on the Australian continent. The western margin probably formed as a series of NE-trending rifts and NW-trending transforms during Late Jurassic breakup. Canyons cut the western margin, and some of these appear to be fault-bounded. One such fault forms the northern margin of a major NW-trending feature, the Wilson Spur. This appears to be a transform fault and perhaps extends across the abyssal plain as far as the eastern end of the Java Trench. Valdivia seismic profiles suggest that, at the trench, it separates thrust-faulted continental crust to the east from oceanic crust to the west. This could explain the eastern termination of the deep part of the trench. The bathymetric depression of the Roti Basin, which lies southeast of the Java Trench, links the trench to the Timor Trough. The Argo Abyssal Plain slopes gently southward, with water depths ranging from 5000 m near the Java Trench to 5730 m in the south. Oceanic basement varies from smooth to hummocky and irregular, and is overlain by about 400 m of acoustically semi-transparent Late Jurassic and Cretaceous sediments, that is in turn unconformably overlain by 200 m of layered Tertiary sediment. Bottom samples taken by R.V. Valdivia from the outer Scott Plateau have provided new information about seismic sequences. They show that Callovian breakup was preceded by a period of basic volcanism and shallow marine sedimentation, that restricted shallow marine conditions followed in the Late Jurassic, and that bathyal carbonate sedimentation prevailed by the Late Cretaceous (Campanian). Quaternary marls cored on the northern Scott Plateau straddled the Pleistocene-Holocene boundary, and siliceous oozes cored on the southern slope of the Java Trench contain nannofossils which, below a few decimetres, are older than late Pleistocene. The Java Trench cores indicate that the calcite compensation depth was apparently between 5420 and 5700 m in the early or middle Pleistocene, and is above 4950 m now. The Scott Plateau cores indicate that the present calcite compensation depth in the region lies below 3290 m. On the Scott Plateau Holocene sedimentation rates are about 5 cm/I000 years, but in the Java Trench they are much lower. Manganese oxide crusts and nodules were recovered from the Scott Plateau, but their content of valuable metals was low.

You can also purchase hard copies of Geoscience Australia data and other products at http://www.ga.gov.au/products-services/how-to-order-products/sales-centre.html

We provide a reconstruction of atmospheric CO2 from deep-sea sediments, for the past 625000 years (Milankovitch chron). Our database consists of a Milankovitch template of sea-level variation in combination with a unique data set for the deep-sea record for Ontong Java plateau in the western equatorial Pacific. We redate the Vostok ice-core data of Barnola et al. (1987, doi:10.1038/329408a0). To make the reconstructions we employ multiple regression between deep-sea data, on one hand, and ice-core CO2 data in Antarctica, on the other. The patterns of correlation suggest that the main factors controlling atmospheric CO2 can be described as a combination of sea-level state and sea-level change. For best results squared values of state and change are used. The square-of-sea-level rule agrees with the concept that shelf processes are important modulators of atmospheric CO2 (e.g., budgets of shelf organic carbon and shelf carbonate, nitrate reduction). The square-of-change rule implies that, on short timescales, any major disturbance of the system results in a temporary rise in atmospheric CO2.