cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7xs5sw0
title: Automated Reference Toolset (ART)Data

description: These environmental raster covariate, geospatial vector data, and tabular data were compiled as input data for the Automated Reference Toolset (ART) algorithm. These data are a subset of all the environmetal raster covariate data used in the ART algorithm. Users are advised to read the mansuscript, associated with these data and identified as the larger work citation. It is recommended that data users contact the data set author if they have any questions about the development, processing, contribution, and use of these data in the Automated Reference Toolset. The purpose of these data are to validate the Automated Reference Toolset process. These data are associated with the journal manuscript: Nauman, T.W., and Duniway, M.C. 2016, The Automated Reference Toolset: A Soil-Geomorphic Ecological Potential Matching Algorithm, Soil Science Society of America Journal (online), http://dx.doi.org/10.2136/sssaj2016.05.0151.
DOI: 10.18739/a2gx0t
title: Extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP-x), 1982-Present
DOI: 10.5281/zenodo.574881
title: དབའ་བཞེད་ collated with རྦ་བཞེད : version 1.0

description: Collation of DBA’ (2000) and RBA (2011.1): version 1.0 [with some translation notes inserted as a guide]
description: Sources used: [1] དབའ་བཞེད་ Vienna 2000 This is the oldest known and complete version of the text to date. It was first published in Pasang Wangdu and Hildegard Diemberger, dBa' bzhed: The Royal Narrative Concerning the Bringing of the Buddha's Doctrine to Tibet (Vienna: Österreichischen Akademie der Wissenschaften, 2000). The text, casually but correctly written in a cursive hand, was reproduced photographically in that book. The same manuscript was reproduced again as a photo-lithograph facsimile in volume 36 of Bod gyi lo rgyus rnam thar phyogs bsgrigs gnyis pa published from Ziling in 2011 (see TBRC W1PD153537). This will be referred to as DBA' (2000). [2] རྦ་བཞེད་ Ziling 2011 This version was reproduced as a photo-lithograph facsimile in volume 36 of Bod gyi lo rgyus rnam thar phyogs bsgrigs gnyis pa, published from Ziling in 2011 (see TBRC W1PD153537). This text is closely related to DBA' (2000) in its palaeography and the narrative also corresponds up to folio 4v, after which the text breaks off and turns to events in the life of the Buddha. This manuscript represents an early version that was redacted subseqent to DBA' (2000); this will be referred to as RBA (2011.1).
DOI: 10.18739/a2c391
title: Climate Data Record of Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP), 1982-Present
DOI: 10.15139/s3/dos6tz
title: Replication Data for: A Squire Index Update

description: The measure of legislative professionalization I developed was first published a quarter century ago. Since then updates have appeared periodically. In this note I briefly document the measure’s usefulness in academic research and then calculate it for 2015. For reasons I detail, the updated measure is corrected for a misestimate of days in session for some states.
DOI: 10.15787/vtt1/lomwbb
title: Explore Surrogate Measures of Safety Using SHRP2 Naturalistic Driving Data

description: Project Description This dataset was part of a pilot effort to identify surrogate events that are statistically associated with crash risk and use crash census data contained in the Highway Safety Information System (HSIS) data to confirm the frequency and location of crashes. Ultimately, the findings of this research were intended to facilitate the development and use of enhanced analytical techniques for improved safety. Data Request Scope The dataset contains video and time series data from the SHRP2 Naturalistic Driving Program. Four separate trips containing a crash are included. Portions of the trips near the origin are not included, nor are coordinates for the crash locations. The trips end shortly after the crash occurs. Both forward and rear videos are included. The events are all single vehicle roadway departure crashes, obtained across all the different study sites. These events include those that were available in the database before the end of March, 2013. Data Specification For each of the 4 crashes, the dataset contains three files: a forward video, a rear video, and a csv file containing the time series data. An xlsx file with event detail table information for each of the crashes is also included. A data dictionary describing the videos and the columns in the csv files is included with this citation.
DOI: 10.18739/a23q23
title: Ice core vanillic acid and para-hydroxybenzoic acid concentrations, Akademii Nauk, Severnaya Zemlya archipelago, Russia, 2013-2015
DOI: 10.18739/a27d5c
title: Ice core vanillic acid and para-hydroxybenzoic acid concentrations, Akademii Nauk, Severnaya Zemlya archipelago, Russia, 2013-2015
DOI: 10.15787/vtt1/ygjwob
title: Assessing the Prevalence and Impact of Road Rage on Driver Performance and Crash Risk

description: Project Description This dataset was created to help determine whether aggressive driving leads to increased risk of Safety Critical Events (SCEs), and which driver characteristics and driving conditions, in combination with aggressive driving, ultimately increase the chance of SCEs. Data Request Scope The dataset includes vehicle, participant, and trip characteristics for crashes, near-crashes, and baselines data in the SHRP 2 NDS dataset. A total of 38,837 events are included in the table. Data Specification The dataset contains one file in xlsx format. The following variables are included in that file: eventID displayTripID anonymousParticipantID ageGroup sex eventSeverity1 eventSeverity2 frontSeatPassengers rearSeatPassengers contigTravelLanes throughTravelLanes trafficDensity distanceinKM driverBehavior1 driverBehavior2 driverBehavior3 driverImpairments durationTotalInMS numViol numCrash classification The definitions and specifications for these variables can be found on the InSight data dictionary.
DOI: 10.5281/zenodo.579679
title: dhlab-epfl/LinkedBooksReferenceParsing: 1.1

description: A dataset of annotated references (in both reference lists and footnotes) from journal issues and monographs on the history of Venice, created in the context of the LinkedBooks project (http://dhlab.epfl.ch/page-127959-en.html). The dataset contains annotated reference lists of monographs and annotated references from the footnotes of journal issues from the following journals (mostly, but not exclusively in Italian): Ateneo Veneto, Archvio Veneto, Studi Veneziani. This dataset was digitized, OCRed (using ABBYY FineReader) and annotated (using Brat ADD) from 2014 to 2016. Along the dataset of annotations, a framework to train your own parsers is provided, based on Conditional Random Fields. Feel free to use it to build your own parser, and if you improve on our results, please let us know!
DOI: 10.5066/f71n7zkb
title: Agricultural Pesticide Use Estimates for Selected Watersheds of the Surface Water Trends Project, 1992-2014, National Water Quality Program

description: The U.S. Geological Survey (USGS) National Water Quality Program (NWQP) provides an understanding of water-quality conditions; whether conditions are getting better or worse over time; and how natural features and human activities affect those conditions. The Surface Water Trends (SWT) project of NWQP evaluates the directions, periods, and statistical significance of trends in water quality in streams and rivers. This data release was generated for SWT and provides annual agricultural pesticide use (1992-2014) for selected watersheds where long-term water quality is measured and where subsequent trend analysis will be conducted. County-level pesticide use estimates for 33 compounds were allocated to agricultural land for 70 SWT watersheds.
DOI: 10.5066/f7h70czs
title: Standardization and Application of an Index of Community Integrity for Waterbirds in the Chesapeake Bay

description: In recent decades, there has been increasing interest in the application of ecological indices to assess ecosystem condition in response to anthropogenic activities. DeLuca et al. (2008) developed an Index of Waterbird Community Integrity (IWCI) to evaluate breeding waterbird response to anthropogenic activities in the Chesapeake Bay, USA. As we attempted to apply this index to a study in the same region, we discovered the need to add more species; however, the scoring criteria were not defined well enough to do so. This study explicitly standardizes the scoring criteria and definitions and provides index scores for all waterbirds of the Chesapeake Bay. In addition, an alternative approach to estimate avian abundance is described, which allows for greater areal coverage compared to transect surveys. The utility of the modified index is then demonstrated with recent survey data of breeding and migratory waterbirds in Chesapeake Bay across a disturbance gradient. This explicitly-defined scoring system will facilitate application to new species in the Bay or new areas beyond this region. By providing these updates and analysis tools, this approach will be more accessible to new studies and regions, and provides a consistent methodology which can be applied across studies.This index when combined with other community integrity indices could provide a more powerful tool for estuarine managers.
DOI: 10.5281/zenodo.573852
title: TweetsKB (Part 1, Jan 2013 - Feb 2014)

description: <strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (2013 - 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: https://data.gesis.org/tweetskb/. <em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em>
DOI: 10.5281/zenodo.577572
title: TweetsKB (Part 2, Mar 2014 - Dec 2014)

description: <strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (2013 - 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: https://data.gesis.org/tweetskb/. <em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em>
DOI: 10.5281/zenodo.579597
title: TweetsKB (Part 3, Jan 2015 - Oct 2015)

description: <strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (2013 - 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: https://data.gesis.org/tweetskb/. <em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em>
DOI: 10.5281/zenodo.579601
title: TweetsKB (Part 4, Nov 2015 - Aug 2016)

description: <strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (2013 - 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: https://data.gesis.org/tweetskb/. <em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em>
DOI: 10.5066/f7gf0rqz
title: A Reservoir Morphology Database for the Conterminous United States

description: The U.S. Geological Survey, in cooperation with the Reservoir Fisheries Habitat Partnership, combined multiple national databases for the purpose of calculating new morphological metrics not included in the original databases for 3,828 reservoirs. These new metrics include, but are not limited to, shoreline development index, index of basin permanence, and development of volume and other descriptive metrics based on established morphometric formulas. The new database also contains modeled chemical and physical metrics. Because of the nature of the existing databases used to compile the Reservoir Morphology Database and the inherent missing data, some metrics were not populated when data was missing. The Reservoir Morphology Database will assist reservoir managers in characterizing reservoirs throughout the continental United States.
DOI: 10.5281/zenodo.580095
title: Phenotypic microevolution in plant quantitative traits.

description: This database included studies that provide data of changes in quantitative traits of angiosperms within a known temporal framework (&lt;300 years). The search was performed by Scopus (www.scopus.com), up to 22 December 2015 (search strings in Gorné and Díaz 2017). The database includes studies that measured intraspecific change in a quantitative trait and which report the elapsed time when the phenotypic change occurred. The studies recorded a single population before and after a change in the environment or compared two (or more) populations by measuring a quantitative trait across two situations, where one of them was a new condition of known age. Both, by measuring change directly in the field or by performing common condition experiments (e.g. common garden experiments or reciprocal transplants). Studies reporting results from artificial selection or interspecific hybridization were excluded. The environmental changes included expansions of distributional range, soil or air pollution, exposure to herbicides, changes in salinity, pH, climate, disturbance or irrigation regime, and addition or loss of species in the local community. All data available in each study were recorded, including several observations of the same species.

All data points were categorized according to biological properties of the study system (lifespan, growth form, trait type) and methodological ones. The amount and rate of phenotypic change is expresed as the standardized mean difference Hedges g (Hedges 1981, 1982), a rate of change which is the Hedges g over the elapsed time in years, and the log-transformation of both of them. The standardized mean difference is equal to the haldane numerator, which is a standard rate of evolution (Haldane 1949; Gingerich 1993).
DOI: 10.5066/f7ff3qkk
title: Relative seismic velocity variations correlate with deformation at Kilauea volcano, Hawaii

description: The dataset includes tiltmeter data at a sample rate of 1 sample per minute from a downhole tiltmeter at Uwekahuna Vault (UWE). Location is -155.291162, 19.420972 (NAD83), elevation 1257 m. Data has two orientations for each time sample (north and east). Each file contains a year of data. The original datasource removes the mean, so the ends of subsequent files will not align. The absolute value of tilt has little value, so the user should manually shift the records by a constant if alignment is required between year files.
DOI: 10.14469/hpc/2568
title: chlorobenzene

description: Gaussian Calculation
DOI: 10.14469/hpc/2569
title: MR-186 chloroform, conformation 2, lowest systematic MM

description: Gaussian Calculation
DOI: 10.14469/hpc/2576
title: 2-((2-methylbutyl)amino)-1-(1-phenyl-3,4-dihydroisoquinolin-2(1H)-yl)ethan-1-one

description: NMR Dataset
DOI: 10.14469/hpc/2577
title: dsdsds
DOI: 10.5066/f7zc812f
title: Data for Trap Net Captured Juvenile Lost River and Shortnose Suckers from Upper Klamath Lake, Oregon

description: Data included in this data set are for trap net captured juvenile suckers from Upper Klamath Lake, Oregon starting in 2001. Data were collected on fishing effort, the number of suckers captured, sucker length, and sucker species. There are two levels of data. Net level data contains 14,838 records and the data file is 2,069 KB and fish level data contains 25,236 records and the data file is 1,543 KB. The two files can be linked on SampleID and DatePulled, which is unique to each net set. Data files are comma delimited.
DOI: 10.5281/zenodo.580319
title: SIDDHAṂ : metadata version 1.0

description: SIDDHAṂ : metadata version 1.0. Working version of object and inscription list.
DOI: 10.14469/hpc/2570
title: MR-186 chloroform, conformation 2, lowest systematic MM

description: Gaussian Calculation
DOI: 10.14469/hpc/2571
title: MR-180 chloroform, conformation 2; lowest systematic MM

description: Gaussian Calculation
DOI: 10.18739/a2zx05
title: Arctic Science, Engineering and Education for Sustainability-Land Cover Land Use Change Prudhoe Bay Alaska Airport Site road effects, Summer 2015
DOI: 10.4119/unibi/2911345
title: Supplementary Materials for "Exploring Particle Trajectory Sonification's Real-Time Interactivity with Parallel Computing"

description: In this paper, we revisit, explore and extend the Particle Trajectory Sonification (PTS) model, which supports cluster analysis of high-dimensional data by probing a model space with virtual particles which are `gravitationally' attracted to a mode of the dataset's potential function. The particles' kinetic energy progression of as function of time adds directly to a signal which constitutes the sonification. The exponential increase in computation power since its conception in 1999 enables now for the first time to investigate real-time interactivity in such complex interweaved dynamic sonification models. We speeded up the computation of the PTS model with (i) data optimization via vector quantization, and (ii) parallel computing via OpenCL. We investigated the performance of sonifying high-dimensional complex data under different approaches. The results show a substantial increase in speed when applying vector quantization and parallelism with CPU. GPU parallelism provided a substantial speedup for very large number of particles comparing to using CPU but did not show enough benefit for a low number of particles due to copying overhead. A hybrid OpenCL implementation is presented to maximize the benefits of both worlds.
DOI: 10.5281/zenodo.571179
title: Occurrence data on Beauvericin and Enniatins in food

description: Beauvericin and enniatins are mycotoxins produced by various <em>Fusarium</em> species that invade and grow on crops, and may produce them under moist and cool conditions. They are predominantly found in cereal grains and their products. The datasets contain occurrence data submitted to the European Food Safety Authority (EFSA) by two European countries (Italy and Finland) following a call for data and supplemented with data from some European research groups. The samples have been taken in years 2002 and 2012, with majority of data collected in 2012. The analytical method used is LC-MS. This data has been used to inform the preparation of the Scientific Opinion on the risks to human and animal health related to the presence of beauvericin and enniatins in food and feed adopted by EFSA in 2014.
description: EU; XLSX; data.collection@efsa.europa.eu
DOI: 10.4119/unibi/2698054
title: Supplementary Material for "Growing Neural Gas Sonification Model for Interactive Surfaces"

description: In this paper we present our reimplementation of the Growing Neural Gas Sonification for interactive surfaces such as our t-Desk or touch-capable tablet PCs. Growing Neural Gas (GNG) is an undirected learning algorithm that incrementally 'grows' a network graph into data distributions, revealing the data distributions' intrinsic dimensionality and aspects of its structure. The GNG Sonification (GNGS) provides a method to interactively explore the GNG during the growing process, utilizing a Model- Based Sonification (MBS) to convey audible information about the data distribution in addition to the visualization. The goal of our reimplementation was to be able to rapidly grasp the structure of the sonified and visualized data, to give the user the ability to conduct direct A/B comparisons between different (or similar) clusters within a data distribution. The direct bi-manual interaction as well as a simplified full-screen touchable user interface helps to focus on the exploration of the GNG rather than the interaction itself. We present and discuss different interaction metaphors for the excitation of the model setup in this MBS. #### Quiz #### Snake #### Three Cluster #### Video Example 1 #### Video Example 2 #### Video Example 3
DOI: 10.5281/zenodo.581238
title: Regional Weights Table by Sector

description: This paper is an intermediate result from the work for "Estimating Economic Damage from Climate Change in the United States". This tables contains the set of "weights" used to aggregated impacts across regions. These weights are roughly equivalent to the baseline quantity available to be affected in each sector, during the baseline period, 2000 - 2010. The file contains a row for the national weights, rows for each NCA region, and for each state. Each column is a sector as named in the first header row, with units defined in the second header row. Additional sector-specific notes are below: Crime:<br> <br> We assumed that crime rates in unobserved counties were equal to the average of crime rates in observed counties.<br> <br> Mortality: Mortality weights are the age-specific populations. The population counts for age-based mortality and the total mortality weights won't add up, because they are from different years. Age-based population is from an average of 1999 - 2010, from the same dataset as the age-based mortality rates. On the other hand, total mortality weights use 2010 census data. We assumed that the portion of population in each age cohort for unobserved counties is the same as the average of observed counties. <em>This data is provided for non-commercial research and educational purposes.</em>