cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23719/1395339
title: County-Level Human Well-Being Index and Domain Scores (2000-2010) plus EQI data set (2000-2005)

description: The HWBI_Draft_1 is an internal map service being prepared for public release (early FY18). This map services contains mean county-level HWBI, domain, indicators and service scores related to research efforts completed in 2014. The EQI map service is a publically accessible map services that contains average county-level results for 2000-2005.
DOI: 10.23719/1390160
title: Cardiopulmonary changes in humans with coronary artery disease associated with exposure to ambient concentrations of ozone.

description: The dataset contains a list of cardiac and vascular biomarkers that were obtained on each day a participant visited the EPA Human Studies Facility.  It also contains ozone concentrations on those days, which are publicly available on the EPA AirNow website.
DOI: 10.23719/1364360
title: U.S. Geological Survey: Surface-Water Historical Instantaneous Data for the Nation: Build Time Series

description: The USGS historical data base contains historical surface water discharge volume data for all 16,658 surface water sites that have current conditions.
DOI: 10.23719/1404721
title: Kaushal et al. 2017 (Applied Geochemistry) Human-accelerated weathering increases salinization, major ions, and alkalinization in fresh water across land use

description: •Base cations increased in drinking water over ∼50 years coinciding with urbanization.
•DIC, cations, Si, SO42- and pH in streams increased with impervious surface cover.
•Road salts and weathering of impervious surfaces were major sources of ions.
•Base cations and pH contributed to alkalinization from headwaters to coastal waters.
•Increased ions impact drinking water, infrastructure, and coastal alkalinization.
DOI: 10.23719/1366491
title: GoldenHeather_A-jhb9

description: No data are associated with this review/overview article.
DOI: 10.23719/1374550
title: Levels of pyrethroids/degradates in Ex-R food samples

description: Levels of pyrethroid insecticides and pyrethroid degradates in Ex-R food samples
DOI: 10.23719/1407002
title: Minimal_Set_of_In_Vitro_ER_Agonist_Assays_Selection_RegToxPharm_Data

description: A dataset for the manuscript which demonstrates that it is possible to achieve levels of performance equivalent to the full 16 assay ER agonist model against both in vitro and in vivo reference chemical sets, using only 4 assays in the simplest “subset” ER agonist model.
DOI: 10.23719/1419007
title: Global Mercury Observatory System Land-based Monitoring Data Portal

description: Global Mercury Observation System On-line Data Portal
DOI: 10.23719/1407006
title: Predicting_Systemic_Toxicity_Effects_ArchTox_2017_Data

description: In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4382 in vivo studies for 1201 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. In order to address the complexity problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using Random Forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 20% of the variance reducing the root mean squared error (RMSE) from 0.96 log10 mg/kg/day to 0.85 log10 mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 38% of the variance with an RMSE of 0.76 log10 mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log10 mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.1 to 0.8 log10 mg/kg/day. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we have generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for thousands of chemicals.
DOI: 10.23719/1407541
title: Aerosol direct effects on ozone - China case study

description: Model output from the 2-way coupled WRF-CMAQ modeling system applied to China.
DOI: 10.23719/1431308
title: Construction and Demolition Debris 2014 US Final Disposition Estimates Using the CDDPath Method

description: Estimates of the final amount and final disposition of materials generated in the Construction and Demolition waste stream measured in total mass of each material. Traditional C&D materials included are concrete, asphalt pavement, asphalt shingles, bricks and clay, metal, wood, and gypsum drywall. Non-traditional materials in this stream include cardboard, organics, carpet, glass, plastic, and fines. The estimates are based on generation amounts described in the EPA SMM Facts and Figures reports. The method used to estimate final disposition is called CDDpath.
DOI: 10.23719/1420061
title: Aaron Journal article datasets

description: All figures used in the journal article are in netCDF format.
DOI: 10.25340/r4/slt8o7
title: Related Data for: Applied linguistics journal editor perspectives: Research ethics and academic publishing

description: Concern for research integrity and ethics has been a part of scholarly publishing since the earliest scientific journals were published. At the same time, scholarly publishing is big business. Thus, journal editors must manage publication interests as well as research integrity and ethical issues. As ethics and integrity are deeply embedded in the research process, not only in terms of treatment of human subjects or methods for collecting, analyzing, and presenting but also in all aspects of publishing, we investigate the role of journal editors in scholarly publishing for applied linguistics. Specifically, we examine the issues/challenges applied linguistics journal editors face in relation to research integrity and ethics, their knowledge, beliefs and practices, through an anonymous online survey. Results show that the most serious issue identified by the editors was finding sufficient expert reviewers. Other issues included plagiarism, redundant publications and inappropriate citations. However, in general, editors did not feel most of the listed ethical issues were serious problems (e.g. interference in editorial decisions, inappropriate image manipulation) or they did not know if the issues were a problem (e.g. unacknowledged writers, inappropriate acknowledgements). We conclude by offering recommendations for ways forward and by suggesting further research, including studies with a more dialogic approach which would allow editors to voice their perspectives and investigations of local communities of practice which might supersede universality assumptions of research integrity and ethics.
DOI: 10.23719/1423890
title: 2018_extent_CI_data

description: Full resolution (300m), weekly MERIS data were obtained over the contiguous United States for 2008 through 2011. Seven day composite images were created by retaining the maximum value detected for each pixel within the time period and then the monthly mean of the maximums was calculated. A spatial mosaic composed of 54 individual scenes was generated for each week resulting in a total of 208 CONUS images from 2008 to 2011. Weekly OLCI data were also retrieved from January 2017 through December 2017. MERIS and OLCI data were processed by the NASA OBPG, using the SeaWiFS Data Analysis System, SRTM static land mask, and a transformation to Albers Equal Area with an area-weighted interpolation to match the projections of the National Hydrography Dataset High Resolution. The SRTM land mask and SeaDAS processing is static in relation to waterbody size and did not account for periods of drought nor flood during the study period. Any water pixel adjacent to the SRTM static land mask was automatically flagged and excluded from analysis to reduce potential for mixed land-water pixels and land adjacency effects. To avoid pixel misclassification due to artifacts such as bridges, catchment facilities, and islands, “valid” water pixels were determined by examining the ESRI World Imagery Basemap. This manual operator pixel selection process lowered the potential that land pixels were not misclassified as water or vice versa.
Each 300m satellite pixel in a weekly CONUS map represents a provisional maximum Cyanobacteria Index (CI) value retrieved in the specific time period. The provisional CI was calculated using a spectral shape (SS) algorithm detailed and validated elsewhere. 

Conventional methods to distinguish between ice and water often fail due to high ice reflectance as well as the possibility of cyanobacterial biomass formation under the ice. Therefore, weekly MERIS data were masked for the presence of ice and snow using Interative Multisensor Snow and Ice Mapping System (IMS) Northern Hemisphere Snow and Ice Analysis data (Version 1, 4km). Daily snow and ice data were obtained from the National Snow and Ice Data Center then cropped to the extent of CONUS. Snow and ice data were temporally binned into maximum weekly time composites to match the MERIS data and then converted from raster to shapefile format. If MERIS or OLCI CI values were within the spatial area of the snow and ice mask, they were removed from further analysis.
DOI: 10.23719/1420304
title: Relating soil geochemical properties to arsenic bioaccessibility

description: soil element total concentration, soil pH and arsenic bioaccessibility values
DOI: 10.23719/1433316
title: Soil As and Pb Levels and Plant Uptake in Three Gardens in Puerto Rico

description: Total and bioaccessible arsenic and lead levels and plant uptake in garden plants from Puerto Rico
DOI: 10.23719/1407685
title: Relationship Between Total and Biaccessible Lead on Children's Blood Lead Levles in Urban Residential Philadelphia Soils.

description: Relationship Between Total and Biaccessible Lead on Children's Blood Lead Levles in Urban Residential Philadelphia Soils.
DOI: 10.23719/1420302
title: Comparison of mouse and swine bioassays for determination of soil arsenic relative bioavailability

description: Soil samples provided by EPA Regional offices to NERL for methods development based on the agreement that the sample identifiers never be released.
DOI: 10.23719/1420307
title: ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF)

description: Ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF).
DOI: 10.23719/1390164
title: Greenspaces and biomarkers of allostatic load

description: Residential greenness, biomarkers of stress and allostatic load, demographic and health characteristics from 300 subjets
DOI: 10.23719/1375932
title: NEEAR Water Study

description: Epidemiological data from the NEEAR Water Study
DOI: 10.23719/1435629
title: Data

description: the data set contains a summary of all measurements that were collected at the cottage grove reservoir over the time period of the study.
DOI: 10.23719/1434490
title: Bioactive Contaminants of Emerging Concern in National Park Waters of the Northern Colorado Plateau, USA

description: Water and sediment was collected to assess the occurrence of contaminants of emerging concern (CECs) in National Park waters of the northern Colorado Plateau, USA. CEC presence in water and sediment is reported for 21 sites in eight U.S. national parks in the northern Colorado Plateau region. From 2012 to 2016, at least one PPCP and/or WWI was detected at most sites on over half of sampling visits, indicating that CECs are not uncommon even in isolated areas. Maximum concentrations in this study were generally below available water quality benchmarks, sediment quality guidelines, and concentrations known to induce biological activity in vitro. C occurrence patterns and similarities between continuous and isolated flow locations suggest that direct contamination from individual visitors may also occur. While the data indicate there is little aquatic health risk associated with CECs at our sites, results demonstrate the ubiquity of CECs on the landscape and a continued need for public outreach concerning resource-use ethics and the potential effects of upstream development.
DOI: 10.6084/m9.figshare.23950044
title: Data set of a research paper titled "Relationship between anteroposterior limits of stability while standing and foot and ankle functions in adolescents and young adults with bilateral spastic cerebral palsy"

description: Dataset of a research paper titled "Relationship between anteroposterior limits of stability while standing and foot and ankle functions in adolescents and young adults with bilateral spastic cerebral palsy".
DOI: 10.6084/m9.figshare.23950044.v2
title: Data set of a research paper titled "Relationship between anteroposterior limits of stability while standing and foot and ankle functions in adolescents and young adults with bilateral spastic cerebral palsy"

description: Dataset of a research paper titled "Relationship between anteroposterior limits of stability while standing and foot and ankle functions in adolescents and young adults with bilateral spastic cerebral palsy".
DOI: 10.6084/m9.figshare.23950044.v1
title: Research data.xlsx

description: Dataset of a research paper titled "Relationship between anteroposterior limits of stability while standing and foot and ankle functions in adolescents and young adults with bilateral spastic cerebral palsy".
DOI: 10.23719/1411959
title: Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA

description: To better understand the transport of neonicotinoid insecticides into the Great Lakes, monthly samples (October 2015-September 2016) were collected from 10 tributaries to the Great Lakes, USA. At least one neonicotinoid was detected in 74% of the monthly samples with up to three neonicotinoids detected in an individual sample (10% of all samples). The most frequently detected neonicotinoid was imidacloprid (53%) followed by clothianidin (44%), thiamethoxam (22%), acetamiprid (2%), and dinotefuran (1%). Thiacloprid was not detected in any samples. More spatially intensive samples from were collected in an agriculturally dominated area (Maumee River, Ohio) twice during spring 2016. Three neonicotinoids were ubiquitously detected (clothiandin, imidacloprid, thiamethoxam) in all water samples collected within this basin.
DOI: 10.23719/1419012
title: Social media data for Great Lakes AOCs

description: This data is an Excel file that has links to downloaded photographs posted to social media sites.  There is a sheet with metadata in the file.
DOI: 10.23719/1407611
title: See appendices K-N in report at http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693

description: See report at: http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693
DOI: 10.23719/1407008
title: Predict_Organ_Toxicity_ChemResTox_Data

description: We use a supervised machine learning strategy to systematically investigate the relative importance of study type, machine learning algorithm, and type of descriptor on predicting in vivo repeat-dose toxicity at the organ-level.   A total of 985 compounds were represented using chemical structural descriptors, ToxPrint chemotype descriptors, and bioactivity descriptors from ToxCast in vitro high-throughput screening assays.  Using ToxRefDB, a total of 35 target organ outcomes were identified that contained at least 100 chemicals (50 positive and 50 negative). Supervised machine learning was performed using Na&iuml;ve Bayes, k-nearest neighbor, random forest, classification and regression trees, and support vector classification approaches. Model performnce was assessed based on F1 scores using five-fold cross-validation with balanced bootstrap replicates.  Fixed effects modeling showed the variance in F1 scores was explained mostly by target organ outcome, followed by descriptor type, machine learning algorithm, and interactions between these three factors.  A combination of bioactivity and chemical structure or chemotype descriptors were the most predictive. Model performance improved with more chemicals (up to a maximum of 24%) and these gains were correlated (&rho;= 0.92) with the number of chemicals.
DOI: 10.23719/1407531
title: Aircraft emission impacts on air quality

description: Data sets include information on emissions of air pollutants, description of 3-D meteorological state of the atmosphere, and output from the CMAQ model over the northern hemisphere and contiguous U.S.
DOI: 10.23719/1407613
title: StreamCat

description: The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA.
DOI: 10.23719/1435024
title: Hong and Purucker sensitivity analysis code and data

description: Code and data associated with Hong T, Purucker ST, 2018. Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil, Environmental Modelling and Software, 105: 24-38, https://doi.org/10.1016/j.envsoft.2018.03.018.
DOI: 10.23719/1500884
title: LakeCat

description: The LakeCat Dataset provides summaries of watershed features for 378,088 lakes within the conterminous USA and provides several hundred watershed-level metrics that summarize both natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization,
agriculture, and mines) features.
DOI: 10.23719/1407588
title: in vitro and microsome experiment data

description: exposure_experiment.csv: 
time: length of time that amphibian was exposed to that pesticide in hours.  
parent: is the active ingredient that the amphibian was exposed to.  
analyte: either the main parent compound or the metabolite that was quantified.  
matrix: the sample that was analyzed either the amphibian or soil.  
conc: is the concentration for that specific analyte in that matrix for that specific species in microg/g
replicate: is the individual amphibian or soil exposed to that pesticide.

microsome_experiment3.csv:  
time: is the length of time that the microsomes were exposed before being quenched in minutes.  
parent: is the active ingredient that the amphibian was exposed to.  
analyte: either the main parent compound or the metabolite that was quantified.  
matrix: the sample that was analyzed microsomes.  
conc: is the concentration for that specific analyte in that matrix for that specific species.  in micromolar (uM)
replicate: is the individual microsome exposed to that pesticide. 
microMexp: is the concentration in micromolar (uM) that the microsomes were exposed to for that pesticide.
DOI: 10.23719/1500437
title: Environmental Monitoring and Assessment Program (1990-1998), National Coastal Assessment (2000-2006), National Aquatic Resource Surveys (2000-2015)

description: These data are from EPA's national coastal monitoring programs and include data from the water column, sediments, and biota, 1990-2015
DOI: 10.23719/1407003
title: 2017_Prediction_of_H295R_steroidogenesis_Pathway_Perturbation

description: The objectives of this work were to: 1) develop an integrated analysis of chemical-mediated effects on steroidogenesis in the HT-H295R assay; and, 2) evaluate whether the HT-H295R assay predicts estrogen and androgen production specifically via comparison with the OECD-validated H295R assay.
DOI: 10.23719/1407005
title: Read_Across_Prediction_of_Estrogenicity_for_Hindered_Phenols_2017_Data

description: Read-across is an important data gap filling technique used within category and analog approaches for regulatory hazard identification and risk assessment. Although much technical guidance is available that describes how to develop category/analog approaches, practical principles to evaluate and substantiate analog validity (suitability) are still lacking. This case study uses hindered phenols as an example chemical class to determine: (1) the capability of three structure fingerprint/descriptor methods (PubChem, ToxPrints and MoSS MCSS) to identify analogs for read-across to predict Estrogen Receptor (ER) binding activity and, (2) the utility of data confidence measures, physicochemical properties, and chemical R-group properties as filters to improve ER binding predictions. The training dataset comprised 462 hindered phenols and 257 non- hindered phenols. For each chemical of interest (target), source analogs were identified from two datasets (hindered and non-hindered phenols) that had been characterized by a fingerprint/descriptor method and by two cut-offs: (1) minimum similarity distance (range: 0.1 - 0.9) and, (2) N closest analogs (range: 1 - 10). Analogs were then filtered using: (1) physicochemical properties of the phenol (termed global filtering) and, (2) physicochemical properties of the R-groups neighboring the active hydroxyl group (termed local filtering). A read-across prediction was made for each target chemical on the basis of a majority vote of the N closest analogs. The results demonstrate that: (1) concordance in ER activity increases with structural similarity, regardless of the structure fingerprint/descriptor method, (2) increased data confidence significantly improves read-across predictions, and (3) filtering analogs using global and local properties can help identify more suitable analogs. This case study illustrates that the quality of the underlying experimental data and use of endpoint relevant chemical descriptors to evaluate source analogs are critical to achieving robust read-across predictions.
DOI: 10.23719/1407009
title: Chromatographic_Retention_Time_Prediction_Models_TALANTA_Data

description: This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM logP predictions; (2) a commercially available ACD/ChromGenius model; and, (3) a newly developed Quantitative Structure Retention Relationship model called OPERA-RT.