Datasets

A 30 year record of the vegetation in sample plots in a woodland in the Chicago area. The changes in these plots over time show how ecological restoration can yield dramatic results.

Supporting information for "Urinary Phthalate Metabolite Concentrations and Hot Flashes in Pre- and Perimenopausal Women from the Midlife Women’s Health Study." This file contains tables of the results of stratified analyses of the associations of hot flash outcomes with urinary phthalates metabolites by menopause status, race/ethnicity, body mass index, and depressive status. This file also contains supplementary HPLC methods for the analysis of phthalate metabolites.

The data file contains a list of included studies with their detailed metadata, taken from Cochrane reviews which were used in a project associated with the manuscript "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

The data file contains detailed information of the Cochrane reviews that were used in a project associated with the manuscript (working title) "Evaluation of an automated probabilistic RCT Tagger applied to published Cochrane reviews".

Data on permanent plots at Fortuna and the Panama Canal Watershed, Republic of Panama, containing counts and percent of trees with one or more multiple stems >10cm diameter, with and without palms. Accompanying environmental data includes elevation, precipitation, soil type and soil chemical variables (pH, total N, NO3, NO4, resin P, mehlich Ca, K and Mg.

Data in this spreadsheet presents basic information on Cahokia, Mound 72 shell artifacts. This includes taxonomic identifications, provenience, and bead measurements. There are five tabs: 1. Raw data; 2. Disk bead measurements; 3. Columella bead measurements; 4. Data on cups and pendants; and, 5. Information on whole shell beads.

Raw gas exchange data for photosynthetic induction in 6 rice accession flag leaves. Photosynthetic induction and point measurements were made at ambient [CO2]. Two accessions (AUS 278 and IR64) were selected to screen in greater detail in which photosynthetic induction was measured at six [CO2].

This repository contains the datasets and corresponding results for the paper "MAGUS: Multiple Sequence Alignment using Graph Clustering". The Datasets.zip archive contains the ROSE, balibase, Gutell, and RNASim datasets used in our experiments. The Results.zip archive contains the outputs of running our methods against these datasets. Datasets used: ROSE: 10 simulated nucleotide model conditions from the SATe paper, each with 20 replicates, and with 1000 sequences per replicate. The ROSE datasets were originally taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/sate-i">https://sites.google.com/eng.ucsd.edu/datasets/alignment/sate-i</a> RNASim: This is a collection of simulated nucleotide datasets that were generated under a model of evolution that reflects selection due to RNA structural constraints. We sampled 20 subsets of 1000 sequences each, as well as 10 subsets of 10000 each, by randomly sampling from the original million-sequence RNASim dataset. Gutell: 16S.M, 16S.3, 16S.T, 16S.B.ALL: Four biological nucleotide datasets from the Comparative Ribosomal Website (CRW) with cleaned reference alignments from SATe. Since PASTA is restricted to datasets without sequence length heterogeneity, these were modified to remove sequences that deviate by more than 20% from the median length. The scrubbed datasets range from 740 to 24,246 sequences. The pre-screened 16S datasets were taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/16s23s">https://sites.google.com/eng.ucsd.edu/datasets/alignment/16s23s</a> BAliBASE: We use eight BAliBASE amino acid datasets used in the PASTA paper. As above, we remove outlier sequences, which leaves us with sizes ranging from 195 to 732 sequences. The pre-screened Balibase datasets were taken from <a href="https://sites.google.com/eng.ucsd.edu/datasets/alignment/pastaupp">https://sites.google.com/eng.ucsd.edu/datasets/alignment/pastaupp</a>

Data extracted from Text, Tables and Figures of publications in summarizing crop responses to Free-Air CO2 Elevation (FACE)

Data are from a long-term fire manipulation experiment in the Missouri Ozarks, USA. Data include the raw, annual ring-width increment (rwl), basal area increment (BAI), population-level annual growth resistance (Drs) and resilience (Drl) to drought, intrinsic water use efficiency values (WUEi) and oxygen isotopic composition of individual radial growth rings (δ18O) from southern red oak (Quercus falcata) and post oak (Q. stellata) trees. ---------------------- TITLE: Data for "Sixty-five years of fire manipulation reveals climate and fire interact to determine growth rates of Quercus spp." ---------------------- FILE OVERVIEW: This dataset contains four (4) CSV files as described below: Refsland_et_al_ECS20-0465_BAI.csv: annual basal area increment between 1948-2015 for trees across the fire manipulation experiment Refsland_et_al_ECS20-0465_DroughtIndices.csv: population-level drought resistance and resilience of trees during each target drought period Refsland_et_al_ECS20-0465_WUEi.csv: carbon isotope indicators of drought stress for trees across the fire manipulation experiment Refsland_et_al_ECS20-0465_d18Or.csv: oxygen isotope indicators of drought stress for trees across the fire manipulation experiment ---------------------- VARIABLE EXPLANATION: All the variables in those four files are explained as below: treeID: unique character string that identifies subject tree block: integer (1, 2) that identifies the study block plot: integer (1-12) that identifies the plot nested within each study block trt: character string (Annual, Control, Periodic) that identifies the fire treatment of a given plot species: character string (Quercus falcata, Quercus stellata) that identifies species of subject tree year: integer (1948-2015) that identifies the dated year of each tree ring rwl_mm: numerical value representing the annual tree ring-width, in mm bai_cm2: numerical value representing the annual basal area increment, in cm2 timeperiod: integer value (1953, 1964, 2007, 2012) representing the periods encompassing target dry and wet years Drs_2yr: numerical value representing the drought resistance, defined as the population-level annual growth of trees during drought years relative to pre-drought years for a given time period Drl_2yr: numerical value representing the drought resilience, defined as the population-level annual growth of trees following drought years relative to pre-drought years for a given time period stand_ba_m2ha: numerical value representing the total basal area of a given plot, in m2 per ha stand_density_stems_ha: numerical value representing the total stem density of a given plot, in stems per ha pool: numerical value (1-40) identifying the set of tree ring samples pooled for analysis. Samples were pooled by block, plot, year and species period: integer value (1953, 1964, 1980, 2007, 2012) representing the periods encompassing target dry and wet years type: character string (Dry, Wet) indicating the water availability of a given year d13C: numerical value representing the carbon isotopic composition of radial growth rings within a given sample pool, in per mil WUEi: numerical value representing the annual intrinsic water use efficiency of radial growth rings within a given sample pool d18O: numerical value representing the oxygen isotopic composition of radial growth rings within a given sample pool, in per mil

These are text files downloaded from the Web of Science for the bibliographic analyses found in Zinnen et al. (2020) in Applied Vegetation Science. They represent the papers and reference lists from six expert-based indicator systems: Floristic Quality Assessment, hemeroby, naturalness indicator values (& social behaviors), Ellenberg indicator values, grassland utilization values, and urbanity indicator values. To examine data, download VOSviewer and see instructrions from van Eck & Waltman (2019) for how to upload data. Although we used bibliographic coupling, there are a number of other interesting bibliographic analyses you can use with these data (e.g., visualizing citations between journals from this set of documents). Note: There are two caveats to note about these data and Supplements 1 & 2 associated with our paper. First, there are some overlapping papers in these text files (i.e., raw data). When added individually, the papers sum to more than the numbers we give. However, when combined VOSviewer recognizes these as repeats, and matches the numbers we list in S1 and the manuscript. Second, we labelled the downloaded papers in S2 with their respective systems. In some cases, the labels do not completely match our counts listed in S1 and raw data. This is because some of these papers use another system, but were not captured in our systematic literature search (e.g., a paper may have used hemeroby, but was not picked up by WoS, so this paper is not listed as one of the 52 hemeroby papers).

This data set includes information used to determine patterns of mixing at three small confluences in East Central Illinois based on differences in the temperature or turbidity of the two confluent flows.

This file contains 13 unique case studies that were created for the One health: Infectious diseases course offered at the University of Illinois at Urbana-Champaign campus. The case studies are being made available as educational resources for other One health courses. Each case study is focused on a theme/topic which is associated with One health. These case studies were created using publicly available information and references have been provided for each case study.

These data are from an observational study and small experiment investigating reproductive biology and hybridization between two plants, Celastrus scandens L. and Celastrus orbiculatus Thunb. (Celastraceae). These data were collected during the 2008 growing season from the Indiana Dunes National Park (formerly Indiana Dunes National Lakeshore), just east of the municipality of Ogden Dunes, Indiana, USA. The five data files provide information on floral output of the two species, fertilization rate, fruit set rate, hybridization rate at two scales (individual flowers in both species, individual maternal plants in C. scandens), and the results of a hand-pollination experiment that exchanged pollen between the two species. There are six data files associated with this submission, five data files in comma-separated values format and one text file (‘readme.txt’) that includes detailed explanations of the data files.

This is a network of 14 systematic reviews on the salt controversy and their included studies. Each edge in the network represents an inclusion from one systematic review to an article. Systematic reviews were collected from Trinquart (Trinquart, L., Johns, D. M., & Galea, S. (2016). Why do we think we know what we know? A metaknowledge analysis of the salt controversy. International Journal of Epidemiology, 45(1), 251–260. https://doi.org/10.1093/ije/dyv184 ). <b>FILE FORMATS</b> 1) Article_list.csv - Unicode CSV 2) Article_attr.csv - Unicode CSV 3) inclusion_net_edges.csv - Unicode CSV 4) potential_inclusion_link.csv - Unicode CSV 5) systematic_review_inclusion_criteria.csv - Unicode CSV 6) Supplementary Reference List.pdf - PDF <b>ROW EXPLANATIONS</b> 1) Article_list.csv - Each row describes a systematic review or included article. 2) Article_attr.csv - Each row is the attributes of a systematic review/included article. 3) inclusion_net_edges.csv - Each row represents an inclusion from a systematic review to an article. 4) potential_inclusion_link.csv - Each row shows the available evidence base of a systematic review. 5) systematic_review_inclusion_criteria.csv - Each row is the inclusion criteria of a systematic review. 6) Supplementary Reference List.pdf - Each item is a bibliographic record of a systematic review/included paper. <b>COLUMN HEADER EXPLANATIONS</b> <b>1) Article_list.csv:</b> ID - Numeric ID of a paper paper assigned ID - ID of the paper from Trinquart et al. (2016) Type - Systematic review / primary study report Study Groupings - Groupings for related primary study reports from the same report, from Trinquart et al. (2016) (if applicable, otherwise blank) Title - Title of the paper year - Publication year of the paper Attitude - Scientific opinion about the salt controversy from Trinquart et al. (2016) Doi - DOIs of the paper. (if applicable, otherwise blank) Retracted (Y/N) - Whether the paper was retracted or withdrawn (Y). Blank if not retracted or withdrawn. <b>2) Article_attr.csv:</b> ID - Numeric ID of a paper year - Publication year Attitude - Scientific opinion about the salt controversy from Trinquart et al. (2016) Type - Systematic review/ primary study report <b>3) inclusion_net_edges.csv:</b> citing_ID - The numeric ID of a systematic review cited_ID - The numeric ID of the included articles <b>4) potential_inclusion_link.csv:</b> This data was translated from the Sankey diagram given in Trinquart et al. (2016) as Web Figure 4. Each row indicates a systematic review and each column indicates a primary study. In the matrix, "p" indicates that a given primary study had been published as of the search date of a given systematic review. <b>5)systematic_review_inclusion_criteria.csv:</b> ID - The numeric IDs of systematic reviews paper assigned ID - ID of the paper from Trinquart et al. (2016) attitude - Its scientific opinion about the salt controversy from Trinquart et al. (2016) No. of studies included - Number of articles included in the systematic review Study design - Study designs to include, per inclusion criteria population - Populations to include, per inclusion criteria Exposure/Intervention - Exposures/Interventions to include, per inclusion criteria outcome - Study outcomes required for inclusion, per inclusion criteria Language restriction - Report languages to include, per inclusion criteria follow-up period - Follow-up period required for inclusion, per inclusion criteria

This dataset contains experimental measurements used in the paper, "Ultra-sensitivity of Numerical Landscape Evolution Models to their Initial Conditions." (to be submitted). The data is taken from experimental runs in a miniature landscape model named the eXperimental Landscape Evolution (XLE) facility. In this facility, we complete five >24hr runs at 5 minute temporal resolution. Every five minutes, an planform image was capture, and a digital elevation model (DEM) was generated. For each run, images and a corresponding animation of images are documented. In addition,ASCII formatted DEMs along with color hillshade maps were generated. The hillshade map images were also made into an animation. This dataset is associated with the following publication: https://doi.org/10.1029/2019GL083305

Original leaf gas exchange and absorptance data used in the Collison et al. (2020) Light, Not Age, Underlies the Q9 Maladaptation of Maize and Miscanthus Photosynthesis to Self-Shading - Frontiers in Plant Science doi: 10.3389/fpls.2020.00783

This dataset is a snapshot of the presence and structure of entrepreneurship education in U.S. four-year colleges and universities in 2015, including co-curricular activities and related infrastructure. Public, private not-for-profit and for-profit institutions are included, as are specialized four-year institutions. The dataset provides insight into the presence of entrepreneurship education both within business units and in other units of college campuses. Entrepreneurship is defined broadly, to include small business management and related career-focused options.

This data has tweets collected in paper Shubhanshu Mishra, Sneha Agarwal, Jinlong Guo, Kirstin Phelps, Johna Picco, and Jana Diesner. 2014. Enthusiasm and support: alternative sentiment classification for social movements on social media. In Proceedings of the 2014 ACM conference on Web science (WebSci '14). ACM, New York, NY, USA, 261-262. DOI: https://doi.org/10.1145/2615569.2615667 The data only contains tweet IDs and the corresponding enthusiasm and support labels by two different annotators.

Terrorism is among the most pressing challenges to democratic governance around the world. The Responsible Terrorism Coverage (or ResTeCo) project aims to address a fundamental dilemma facing 21st century societies: how to give citizens the information they need without giving terrorists the kind of attention they want. The ResTeCo hopes to inform best practices by using extreme-scale text analytic methods to extract information from more than 70 years of terrorism-related media coverage from around the world and across 5 languages. Our goal is to expand the available data on media responses to terrorism and enable the development of empirically-validated models for socially responsible, effective news organizations. This particular dataset contains information extracted from terrorism-related stories in the New York Times published between 1945 and 2018. It includes variables that measure the relative share of terrorism-related topics, the valence and intensity of emotional language, as well as the people, places, and organizations mentioned. This dataset contains 3 files: 1. <i>"ResTeCo Project NYT Dataset Variable Descriptions.pdf"</i> <ul> <li>A detailed codebook containing a summary of the Responsible Terrorism Coverage (ResTeCo) Project New York Times (NYT) Dataset and descriptions of all variables. </li> </ul> 2. <i>"resteco-nyt.csv"</i> <ul><li>This file contains the data extracted from terrorism-related media coverage in the New York Times between 1945 and 2018. It includes variables that measure the relative share of topics, sentiment, and emotion present in this coverage. There are also variables that contain metadata and list the people, places, and organizations mentioned in these articles. There are 53 variables and 438,373 observations. The variable "id" uniquely identifies each observation. Each observation represents a single news article. </li> <li> <b>Please note</b> that care should be taken when using "respect-nyt.csv". The file may not be suitable to use in a spreadsheet program like Excel as some of the values get to be quite large. Excel cannot handle some of these large values, which may cause the data to appear corrupted within the software. It is encouraged that a user of this data use a statistical package such as Stata, R, or Python to ensure the structure and quality of the data remains preserved.</li> </ul> 3. <i>"README.md"</i> <ul><li>This file contains useful information for the user about the dataset. It is a text file written in mark down language</li> </ul> <b>Citation Guidelines</b> 1) To cite this codebook please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project New York Times (NYT) Dataset Variable Descriptions. Responsible Terrorism Coverage (ResTeCo) Project New York Times Dataset. Cline Center for Advanced Social Research. May 13. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-4638196_V1 2) To cite the data please use the following citation: Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project New York Times Dataset. Cline Center for Advanced Social Research. May 13. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-4638196_V1

Automatic and manual counts of black flies captured in Illinois.

Nest survival and Fledgling production data for Bell's Vireo and Willow Flycatcher nests.

Raw measurement data for umbilical remnants (umbilical vein, umbilical arteries and urachus) in support of Equine Veterinary Journal publication "Normal Regression of the Internal Umbilical Remnant Structures in Standardbred Foals."