cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/wdcc/mb_kwf_1953-2011
title: Glacier Mass Balance of Kesselwandferner, Oetztal Alps, Austria, from 1952/53-2010/11

description: Project: Glacier monitoring data of Austria - Glaciers are the most visible indicators of global change. Mass balance data allow the calculation of the past and current contributions of land ice to the sea level change. Additionally, glaciological data are used to reconstruct former climate states and complement other climate proxies for the holocene. Since the instrumental climate data are biased towards low altitudes, glacier data offer an archive of high mountain climate that is subject to strong gradients and improve our knowledge on climate to remote regions during the instrumental period. For the development of forward and inverse models, the understanding of the glacier-climate relation is essential. Thus the relationships between different types of glaciological data measured worldwide must be studied on benchmark glaciers, where all kinds of glacier and climate data are available. In Austria, glacier mass balance is measured at Goldbergkees, Hallstaetter Gletscher, Hintereisferner, Jamtalferner Kesselwandferner, Kleinfleisskees, Mullwitzkees, Pasterzenkees, Stubacher Sonnblickkees, Vernagtferner, and Wurtenkees. Records on glacier length are available from 1891, currently more than 100 glaciers are surveyed. Glacier inventory data is available for 1969, and 1998. The project homepages are located at e.g. http://imgi.uibk.ac.at and http://www.zamg.ac.at . Political ideas: European and Austrian laws include the obligation for the authorities to survey the hydrological parameters. Project funders for mass balanace Hintereisferner, Kesselwandferner, Jamtalferner, Hallstaetter Gletscher and Mullwitzkees and glacier length changes: Amt der Oberoesterreichischen Landesregierung Austrian Alpine Club Energie AG Hydrographischer Dienst der Abteilung Wasserwirtschaft des Amtes der Tiroler Landesregierung Nationalpark Hohe Tauern Kommission fuer Geophysikalische Forschungen der Oesterreichischen Akademie der Wissenschaften Summary: The data represent annual values of the glacier mass balance measured with the direct glaciological method. The mass balance is calculated from ablation of ice and accumulation of snow measured at about 10 to 20 stakes for the mass balance year from 1 October to 30 September of the following year. The data comprises the glacier area, the net mass balance for the total glacier area as well as specified for the ablation and accumulation area, the altitude of the equilibrium line (ELA) and the specific mass balance.
DOI: 10.17632/3d4yg89rtr.1
title: TOM2024

description: The TOM2024 dataset is a valuable resource for agricultural research, comprising 25,844 raw images and 12,227 labeled images of tomato, onion, and maize crops. These images are categorized into 30 classes, facilitating precise identification of pests and diseases, which is crucial for improving crop management and food security. The dataset supports sustainable agriculture by promoting early and accurate pest and disease detection, reducing reliance on pesticides. Its accessibility allows researchers and institutions to develop advanced digital solutions, enhancing the effectiveness of pest and disease management. Additionally, the dataset's versatility—searchable by region, crop type, and other criteria—makes it suitable for model development, education, and agricultural extension services. With high-resolution images captured under diverse environmental conditions, TOM2024 offers a robust foundation for training AI models, ultimately contributing to the advancement of precision agriculture.
DOI: 10.17632/5djpm5r4r8.1
title: Results from Data Carrier Analysis for Circular Construction Supply Chains

description: This anonymized data is a result from an experiment testing three data carriers (QR Codes, NFC Chips, and Direct Product Marking) for Circular Construction Supply Chains. Using a quantitative experimental design, the study evaluates these technologies based on speed, SUS user experience, and error rates. The task was to use the data carriers on 12 components and count how many components were older than 25 years old. The participants were timed, any errors in the final result was counted, and they subsequently filled out a System User Scale for the data carrier used. There were three stated hypotheses explored: 1) Higher levels of data carrier device digitization are expected to lead to a decrease in reading time. 2) Higher levels of device digitization are anticipated to result in a decrease in the number of errors. 3) Higher levels of device digitization are anticipated to result in higher SUS scores. The findings reveal that the use of QR codes and NFC chips significantly improves efficiency and user satisfaction compared to DPM. The Location had no statistically significant impact on results, and there was no shown difference for the Errors.
DOI: 10.21227/vek7-e690
title: Global News 60K

description: Text classification systems have become increasingly important in recent years due to the explosion of online documents and the need to sort them for specific services. One of the most critical issues in text classification is the limited availability and diversity of datasets, which can lead to overfitting and poor generalization. In this context, we present a new dataset named Global News 60K (GN60K), which consists of 60,000 news articles from different sources from different parts of the world, covering 10 topics. The dataset provides a rich vocabulary, avoids overfitting problems, and creates better-generalized models.The topics included in the dataset are Politics, Sports, Entertainment, Science and Technology, Business, Health, Environment, Education, Arts and Culture, and Crime. We selected these topics because they cover a wide range of interests and are commonly used in text classification applications. To further increase the dataset's diversity, we considered articles from different parts of the world, including North America, Europe, Asia, Africa, and South America.The articles were selected based on their publication dates, which range from 2022 and 2023.  We believe that our dataset will be valuable for researchers and practitioners working on text/topic classification tasks. The GN60K dataset provides a diverse and well-labelled set of documents that can be used for training and testing various machine learning models. Additionally, the dataset can be used to develop new algorithms for topic classification, and related tasks. We hope that our dataset will contribute to the advancement of the text classification field and foster new research ideas.
DOI: 10.3334/cdiac/00001_2010
title: Global, Regional, and National Fossil-Fuel CO2 Emissions, 1751 - 2007 (Version 2010)

description: Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2009), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2009) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
DOI: 10.3334/cdiac/00001_v2012
title: Global, Regional, and National Fossil-Fuel CO2 Emissions (1751 - 2009) (V. 2012)

description: Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2012), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2011) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
DOI: 10.3334/cdiac/00001_v2013
title: Global, Regional, and National Fossil-Fuel CO2 Emissions (1751 - 2010) (V. 2013)

description: Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2013), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2012) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
DOI: 10.3334/cdiac/atg.009
title: Historical Carbon Dioxide Record from the Vostok Ice Core (417,160 - 2,342 years BP)

description: In January 1998, the collaborative ice-drilling project between Russia, the United States, and France at the Russian Vostok station in East Antarctica yielded the deepest ice core ever recovered, reaching a depth of 3,623 m (Petit et al. 1997, 1999). Ice cores are unique with their entrapped air inclusions enabling direct records of past changes in atmospheric trace-gas composition. Preliminary data indicate the Vostok ice-core record extends through four climate cycles, with ice slightly older than 400 kyr (Petit et al. 1997, 1999). Because air bubbles do not close at the surface of the ice sheet but only near the firn-ice transition (that is, at ~90 m below the surface at Vostok), the air extracted from the ice is younger than the surrounding ice (Barnola et al. 1991). Using semiempirical models of densification applied to past Vostok climate conditions, Barnola et al. (1991) reported that the age difference between air and ice may be ~6000 years during the coldest periods instead of ~4000 years, as previously assumed. Ice samples were cut with a bandsaw in a cold room (at about -15°C) as close as possible to the center of the core in order to avoid surface contamination (Barnola et al. 1983). Gas extraction and measurements were performed with the "Grenoble analytical setup," which involved crushing the ice sample (~40 g) under vacuum in a stainless steel container without melting it, expanding the gas released during the crushing in a pre-evacuated sampling loop, and analyzing the CO2 concentrations by gas chromatography (Barnola et al. 1983). The analytical system, except for the stainless steel container in which the ice was crushed, was calibrated for each ice sample measurement with a standard mixture of CO2 in nitrogen and oxygen. For further details on the experimental procedures and the dating of the successive ice layers at Vostok, see Barnola et al. (1987, 1991), Lorius et al. (1985), and Petit et al. (1999).
DOI: 10.3334/cdiac/atg.029
title: Atmospheric Delta14C Record from Wellington  (1954-1993)

description: Trays containing ~2 L of 5 normal NaOH carbonate-free solution are typically exposed for intervals of 1-2 weeks, and the atmospheric CO<sub>2</sub> absorbed during that time is recovered by acid evolution. Considerable fractionation occurs during absorption into the NaOH solution, and the standard fractionation correction (Stuiver and Polach 1977) is used to determine a δ 14C value corrected to δ 13C = -25 per mil. Some samples reported here were taken using BaOH solution or with extended tray exposure times. These variations in procedure do not appear to affect the results (Manning et al. 1990). A few early measurements were made by bubbling air through columns of NaOH for several hours. These samples have higher δ 13C values. Greater details on the sampling methods are provided in Manning et al. (1990) and Rafter and Fergusson (1959).
DOI: 10.3334/cdiac/lue.ndp017
title: Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database (NDP-017) (2001 version of original 1985 data)

description: In 1980, this data base and the corresponding map were completed after more than 20 years of field investigations, consultations, and analyses of published literature. They characterize the use and vegetative cover of the Earth's land surface with a 0.5° × 0.5° grid. This world-ecosystem-complex data set and the accompanying map provide a current reference base for interpreting the role of vegetation in the global cycling of CO2 and other gases and a basis for improved estimates of vegetation and soil carbon, of natural exchanges of CO2, and of net historic shifts of carbon between the biosphere and the atmosphere.
DOI: 10.3334/cdiac/otg.cdiac_158
title: Carbon Dioxide Information Analysis Center
DOI: 10.3334/cdiac/otg.ndp088
title: Global Ocean Surface Water Partial Pressure of CO2 Database: Measurements Performed During 1968 - 2007 (Version 2007)
DOI: 10.3334/cdiac/otg.ndp088r
title: Global Ocean Surface Water Partial Pressure of CO2 Database: Measurements Performed During 1968-2008 (Version 2008)
DOI: 10.5067/aura/omi/data2024
title: OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km
DOI: 10.5281/zenodo.3538890
title: Data from: Predictive mapping of the global power system using open data

description: Four primary global data outputs from the research: <strong>grid.gpkg:</strong> Vectorized predicted distribution and transmission line network, with existing OpenStreetMap lines tagged in the 'source' column <strong>targets.tif:</strong> Binary aster showing locations predicted to be connected to distribution grid. <strong>lv.tif:</strong> Raster of predicted low-voltage infrastructure in kilometres per cell. This data was created with code in the following three repositories: https://github.com/carderne/gridfinder https://github.com/carderne/energy-infra https://github.com/carderne/accessestimator Full steps to reproduce are contained in this file: https://github.com/carderne/energy-infra/blob/master/README.md The data can be visualized at the following location: https://gridfinder.org
DOI: 10.5281/zenodo.6364594
title: Global map of Local Climate Zones

description: A global 100 m spatial resolution Local Climate Zone (LCZ) map, derived from multiple earth observation datasets and expert LCZ class labels. The LCZ map is based on the LCZ typology (Stewart and Oke, 2012) that distinguish urban surfaces accounting for their typical combination of micro-scale land-covers and associated physical properties. The LCZ scheme is distinguished from other land use / land cover schemes by its focus on urban and rural landscape types, which can be described by any of the 17 classes in the LCZ scheme. Out of the 17 LCZ classes, 10 reflect the 'built' environment, and each LCZ type is associated with generic numerical descriptions of key urban canopy parameters critical to model atmospheric responses to urbanisation. In addition, since LCZs were originally designed as a new framework for urban heat island studies (Stewart and Oke, 2012), they also contain a limited set (7) of 'natural' land-cover classes that can be used as 'control' or 'natural reference' areas. As these seven natural classes in the LCZ scheme can not capture the heterogeneity of the world’s existing natural ecosystems, we advise users - if required - to combine the built LCZ classes with any other land-cover product that provides a wider range of natural land-cover classes. <em>Stewart ID, Oke TR. (2012). Local Climate Zones for Urban Temperature Studies. Bull Am Meteorol Soc. 93(12):1879-1900. doi:10.1175/BAMS-D-11-00019.1</em>
description: See readme.txt for additional information
DOI: 10.5281/zenodo.7523032
title: SDG Knowledge Hub Dataset of SDG-labeled News Articles

description: Dataset of articles published on the IISD SDG Knowledge Hub (sdg.iisd.org). The SDG Knowledge Hub is an online resource publishing news and commentary regarding the implementation of the United Nations’ 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs). Labels assigned by the authors and validated by SDG Knowledge Hub editors indicate which of the 17 SDGs an article addresses.

The data set was generated for the following publications. Please consider citing the publication if you use the data. 

Wulff, D. U., Meier, D. S., & Mata, R. (2023). Using novel data and ensemble models to improve automated labeling of Sustainable Development Goals. arXiv preprint arXiv:2301.11353.

The data contain 9,172 articles downloaded on September 15th, 2021, and are shared with permission from the SDG Knowledge Hub.

The comma-separated data file includes the following columns:

url - URL of the article.

title - Title of the article.

type - Type of article. Either "News", "Policy briefs", "Guest articles", or "Generation 30". 

text - Text of the article. 

date - Publishing date of article.

sdgs - SDG labels assigned by authors and editors. 

SDG-01 to SDG-17 - SDG indicators extracted from the author and editor label.
DOI: 10.5281/zenodo.7535814
title: CottonWeedDet12:  a 12-class weed dataset of cotton production systems for benchmarking AI models for weed detection

description: The dataset CottonWeedDet12 consists of 5648 RGB images of 12-class weeds that are common in cotton fields in the southern U.S. states, with a total of 9370 bounding boxes. These images were acquired by either smartphones or hand-held digital cameras, under natural field light condition and throughout June to September of 2021. The images were manually labeled by qualified personnel for weed identification, and the labeling process was done using the VGG Image Annotator (version 2.10).

The dataset, at the time of publication, is the largest publicly available multi-class dataset dedicated to weed detection. It expects to facilitate communicate efforts to exploit state-of-the-art deep learning method to push weed recognition to the next level. With the WeedDet12 dataset, a performance benchmark of a suite of YOLO object detectors has been built for weed detection. Detailed documentation of the dataset, model benchmarking and performance results is given in an accompanying journal paper: Dang, F., Chen, D., Lu, Y., Li, Z., 2023. YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems. Computers and Electronics in Agriculture 205, 107655. https://doi.org/10.1016/j.compag.2023.107655 

If you use the dataset on a published publication, please cite the dataset or the journal article above.