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Datasets
published: 2020-11-05
Miller, Andrew; Raudabaugh, Daniel (2020): Data from Species Distribution, Phylogenetic Structure, and Functional Roles of Detritius Inhabiting Fungi Across Contrasting Aquatic Environments.. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6862941_V2
This version 2 dataset contains 34 files in total with one (1) additional file, called "Culture-dependent Isolate table with taxonomic determination and sequence data.csv". The remaining files (33) are identical to version 1. The following is the information about the new file and its variables: <b>Culture-dependent Isolate table with taxonomic determination and sequence data.csv</b>: Culture table with assigned taxonomy from NCBI. Single direction sequence for each isolate is include if one could be obtained. Sequence is derived from ITS1F-ITS4 PCR amplicons, with Sanger sequencing in one direction using ITS5. The files contains 20 variables with explanation as below: IsolateNumber : unique number identify each isolate cultured Time: season in which the sample was collected Location: the specific name of the location Habitat: type of habitat : either stream or peatland State: state in the USA in which the specific location is located Incubation_pH ID: pH of the medium during isolation of fungal cultures Genus: phylogenetic genus of the fungal isolates (determined by sequence similarity) Sequence_quality: base call quality of the entire sequence used for blast analysis, if known %_coverage: sequence coverage reported from GenBank %_ID: sequence similarity reported from GenBank Life_style : ecological life style if known Phylum: phylogenetic phylum as indicated by Index Fungorum Subphylum: phylogenetic subphylum as indicated by Index Fungorum Class: phylogenetic class as indicated by Index Fungorum Subclass: phylogenetic subclass as indicated by Index Fungorum Order: phylogenetic order as indicated by Index Fungorum Family: phylogenetic Family as indicated by Index Fungorum ITS5_Sequence: single direction sequence used for sequence similarity match using blastn. Primer ITS5 Fasta: sequence with nomenclature in a fasta format for easy cut and paste into phylogenetic software Note: blank cells mean no data is available or unknown.
keywords:
ITS1 forward reads; Illumina; peatlands; streams; bogs; fens
published: 2020-07-15
Molloy, Erin K. (2020): Data from: Supertree-like methods for genome-scale species tree estimation. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4004605_V1
This repository includes scripts and datasets for Chapter 6 of my PhD dissertation, " Supertree-like methods for genome-scale species tree estimation," that had not been published previously. This chapter is based on the article: Molloy, E.K. and Warnow, T. "FastMulRFS: Fast and accurate species tree estimation under generic gene duplication and loss models." Bioinformatics, In press. https://doi.org/10.1093/bioinformatics/btaa444. The results presented in my PhD dissertation differ from those in the Bioinformatics article, because I re-estimated species trees using FastMulRF and MulRF on the same datasets in the original repository (https://doi.org/10.13012/B2IDB-5721322_V1). To re-estimate species trees, (1) a seed was specified when running MulRF, and (2) a different script (specifically preprocess_multrees_v3.py from https://github.com/ekmolloy/fastmulrfs/releases/tag/v1.2.0) was used for preprocessing gene trees (which were then given as input to MulRF and FastMulRFS). Note that this preprocessing script is a re-implementation of the original algorithm for improved speed (a bug fix also was implemented). Finally, it was brought to my attention that the simulation in the Bioinformatics article differs from prior studies, because I scaled the species tree by 10 generations per year (instead of 0.9 years per generation, which is ~1.1 generations per year). I re-simulated datasets (true-trees-with-one-gen-per-year-psize-10000000.tar.gz and true-trees-with-one-gen-per-year-psize-50000000.tar.gz) using 0.9 years per generation to quantify the impact of this parameter change (see my PhD dissertation or the supplementary materials of Bioinformatics article for discussion).
keywords:
Species tree estimation; gene duplication and loss; statistical consistency; MulRF, FastRFS
published: 2020-08-01
Horna Munoz, Daniel; Constantinescu, George; Rhoads, Bruce ; Lewis, Quinn; Sukhodolov, Alexander (2020): Confluence Density Effects Simulation Database. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6257171_V1
This data set shows how density effects have an important influence on mixing at a small river confluence. The data consist of results of simulations using a detached eddy simulation model.
keywords:
confluence; flow dynamics; density effects
published: 2020-08-25
Allan, Brian; Fredericks, Lisa (2020): AllanLab fluidigm pipeline test dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0095812_V1
The Allan Lab has published a Fluidigm pipeline online. This is the url: https://github.com/HPCBio/allan-fluidigm-pipeline. This url includes a tutorial for running the pipeline. However it does not have test datasets yet. This tarball hosted at the Illinois Data Bank is the dataset that completes the github tutorial. It includes inputs (custom database of tick pathogens and fluidigm raw reads) and output files (tables of samples with taxonomic classifications).
keywords:
custom database of tick pathogens; fluidigm pipeline; fluidigm paired reads; fluidigm tutorial
published: 2020-08-31
Chen, Luoye; Khanna, Madhu; Debnath, Deepayan; Zhong, Jia; Ferin, Kelsie; VanLoocke, Andy (2020): BEPAM Model Code and CABBI Simulation Results for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9851670_V1
This dataset contains BEPAM model code and input data to replicate the outcomes for "The Economic and Environmental Costs and Benefits of the Renewable Fuel Standard". The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output.gms. (BEPAM-Social cost model-ERL.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.
keywords:
Social Cost of Carbon; Social Cost of Nitrogen; Cost-Benefit Analysis; Indirect Land-Use Change
published: 2020-10-11
Narang, Kanika; Sundaram, Hari; Chung, Austin; Chaturvedi, Snigdha (2020): Academic Dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0454350_V1
This dataset contains the publication record of 6429 computer science researchers collected from the Microsoft Academic dataset provided through their Knowledge Service API (http://bit.ly/microsoft-data).
published: 2020-11-01
Packard, Stephen; Spyreas, Greg (2020): Dramatic long-term restoration of an oak woodland due to multiple, sustained management treatments. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0887518_V1
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.
keywords:
woodland; ecological restoration; floristic quality; vegetation; plant ecology; ecological management
published: 2020-10-30
Warner, Genoa R; Pacyga, Diana; Strakovsky, Rita; Smith, Rebecca; James-Todd, Tamarra; Williams, Paige; Hauser, Russ; Meling, Daryl; Li, Lucas; Flaws, Jodi (2020): Phthalates and Hot Flashes SI. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9238850_V1
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.
keywords:
Hot flashes; menopause; phthalates; women
published: 2020-10-27
Kansara, Yogeshwar; Hoang, Linh (2020): Included Articles from Cochrane Reviews. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8212056_V2
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".
keywords:
Cochrane reviews; automation; randomized controlled trial; RCT; systematic review
published: 2020-10-27
Kansara, Yogeshwar; Hoang, Linh; Dong, Xiaoru; Xie, Jingyi; Schneider, Jodi (2020): Sampled Cochrane Reviews Included RCTs Only. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3285089_V2
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".
keywords:
Cochrane reviews; systematic reviews; randomized control trial; RCT; automation
published: 2020-10-27
Lundstrom, Craig (2020): Experimental data from K-Na-Al-Si-H oxides systems. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7110302_V1
keywords:
Phase equilibria; Granite; Quartz; Feldspar
published: 2020-10-16
Jones, Todd M.; Benson, Thomas J.; Ward, Michael P. (2020): Partial predation of a songbird nest by an Eastern Box Turtle (Terrapene carolina carolina) . University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0684398_V1
Video footage of an Eastern Box Turtle (Terrapene carolina carolina) partially predating a Field Sparrow nest (Spizella pusilla) at 0845 h on the 31 of May 2020. Please note that the date on the video footage is incorrect due to user error, but the time is correct.
keywords:
nest predation; turtle; songbird; nest camera; Terrapene carolina carolina; Spizella pusilla;
published: 2020-10-15
Khanna, Madhu; Wang, Weiwei; Wang, Michael (2020): BEPAM Model Code and CABBI Simulation Results for "Assessing the Additional Carbon Savings with Biofuel". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4272529_V1
This dataset consists of various input data that are used in the GAMS model. All the data are in the format of .inc which can be read within GAMS or Notepad. Main data sources include: acreage data (acre), crop budget data ($/acre), crop yield data (e.g. bushel/acre), Soil carbon sequestration data (KgCO2/ha/yr). Model details can be found in the "Assessing the Additional Carbon Savings with Biofuel" and GAMS model package. ## File Description (1) GAMS Model.zip: This includes all the input files and scripts for running the model (2) Table*.csv: These files include the data from the tables in the manuscript (3) Figure2_3_4.csv: This contains the data used to create the figures in the manuscript (4) BaselineResults.csv: This includes a summary of the model results. (5) SensitivityResults_*.csv: Model results from the various sensitivity analyses performed (6) LUC_emission.csv: land use change emissions by crop reporting district for changes of pasturelands to annual crops.
keywords:
Biogenic carbon intensity; Corn ethanol; Economic model; Dynamic optimization; Anticipated baseline approach; Life cycle carbon intenisty
published: 2020-10-14
Dalling, James W.; Heineman, Katherine D. (2020): Multiple stem and environmental variables dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4045402_V1
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.
keywords:
multiple stems; resprouting; Panama Canal Watershed; Fortuna Forest Reserve
published: 2020-10-13
Kozuch, Laura (2020): Cahokia, Mound 72 Shell Artifacts. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0946771_V1
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.
keywords:
Cahokia; Mound 72; Lightning whelk; Bead crafting
published: 2020-10-01
Acevedo-Siaca, Liana; Long, Stephen (2020): Photosynthetic Induction of Rice Flag Leaves. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3596430_V1
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].
published: 2020-09-25
Smirnov, Vladimir (2020): Data and results for: MAGUS: Multiple Sequence Alignment using Graph Clustering. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2643961_V1
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>
published: 2020-09-27
Long, Stephen (2020): Data used to construct Table1 and Figs. 2 and 4 in Ainsworth & Long (2020) 30 Years of Free Air Carbon Dioxide Enrichment (FACE): What Have We Learned About Future Crop Productivity and the Potential for Adaptation? Global Change Biology. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2432396_V1
Data extracted from Text, Tables and Figures of publications in summarizing crop responses to Free-Air CO2 Elevation (FACE)
keywords:
Free Air CO2 Elevation; FACE; wheat, rice, soybean, cassava;
published: 2020-09-27
Vandewalle, Rebecca; Barley, William; Padmanabhan, Anand; Katz, Daniel S.; Wang, Shaowen (2020): Figure code for Understanding the multifaceted geospatial software ecosystem: a survey approach. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6834324_V1
This dataset contains R codes used to produce the figures submitted in the manuscript titled "Understanding the multifaceted geospatial software ecosystem: a survey approach". The raw survey data used to populate these charts cannot be shared due to the survey consent agreement.
keywords:
R; figures; geospatial software
published: 2020-09-18
Clark, Lindsay; Njuguna, Joyce; Jin, Xiaoli; Petersen, Karen; Anzoua, Kossanou G.; Bagmet, Larissa; Chebukin, Pavel; Deuter, Martin; Dzyubenko, Elena; Dzyubenko, Nicolay; Heo, Kweon; Johnson, Douglas A.; Jørgensen, Uffe; Kjeldsen, Jens B.; Nagano, Hironori; Peng, Junhua; Sabitov, Andrey; Yamada, Toshihiko; Yoo, Ji Hye; Yu, Chang Yeon; Long, Stephen P.; Sacks, Erik (2020): RAD-seq genotypes for a Miscanthus sacchariflorus diversity panel. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8170405_V1
Restriction site-associated DNA sequencing (RAD-seq) data from 643 Miscanthus accessions from a diversity panel, including 613 Miscanthus sacchariflorus, three M. sinensis, and 27 M. xgiganteus. DNA was digested with PstI and MspI, and single-end Illumina sequencing was performed adjacent to the PstI site. Variant and genotype calling was performed with TASSEL-GBSv2, using the Miscanthus sinensis v7.1 reference genome from Phytozome 12 (https://phytozome.jgi.doe.gov). Additional ploidy-aware genotype calling was performed by polyRAD v1.1.
keywords:
variant call format (VCF); genotyping-by-sequencing (GBS); single nucleotide polymorphism (SNP); grass; genetic diversity; biomass
published: 2020-09-17
Refsland, Tyler; Knapp, Benjamin; Stephan, Kirsten; Fraterrigo, Jennifer (2020): Data for "Sixty-five years of fire manipulation reveals climate and fire interact to determine growth rates of Quercus spp". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6771049_V1
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
keywords:
climate change adaptation; drought; fire; nitrogen availability; oak-hickory; radial growth; resilience; resistance; stand density; temperate broadleaf forest; water stress
published: 2020-09-07
Chen, Luoye; Blanc-Betes, Elena; Hudiburg, Tara; Hellerstein, Daniel; Wallander, Steven; DeLucia, Evan; Khanna, Madhu (2020): BEPAM Model Code and CABBI Simulation Results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2224392_V2
This dataset contains BEPAM model code and input data to the replicate the results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land." The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output_0213-2020_Complete_daycent-agversion-[rental payment level]%_[biomass price].gms. (BEPAM-CRP model-Sep2020.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.
keywords:
Miscanthus; Switchgrass; soil carbon sequestration; greenhouse gas savings; rental payments; biomass price
published: 2020-08-19
Jetti, Yaswanth Sai; Dunn, Alison C. (2020): The matrix of influence coefficients due to pyramidal distribution on an overlapping hexagonal grid. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0925335_V1
This data set is a matrix of values. The element in the row "i" and the column "j" denotes the influence of hexagonal pyramidal distribution at node "i" on the node "j". The size of the matrix is 16641x16641. This matrix corresponds to a 129x129 grid. Influence coefficient matrix on a smaller grid can be obtained by appropriately choosing the elements from the bigger matrix.
keywords:
Influence coefficients
published: 2020-08-18
Althaus, Scott; Berenbaum, May; Jordan, Jenna; Shalmon, Dan (2020): Replication Data for "No buzz for bees: Media coverage of pollinator decline". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4237085_V1
These data and code enable replication of the findings and robustness checks in "No buzz for bees: Media coverage of pollinator decline," published in Proceedings of the National Academy of Sciences of the United States of America (2020)". In this paper, we find that although widespread declines in insect biomass and diversity are increasing concern within the scientific community, it remains unclear whether attention to pollinator declines has also increased within information sources serving the general public. Examining patterns of journalistic attention to the pollinator population crisis can also inform efforts to raise awareness about the importance of declines of insect species providing ecosystem services beyond pollination. We used the Global News Index developed by the Cline Center for Advanced Social Research at the University of Illinois at Urbana-Champaign to track news attention to pollinator topics in nearly 25 million news items published by two American national newspapers and four international wire services over the past four decades. We provide a link to documentation of the Global News Index in the "relationships with articles, code, o. We found vanishingly low levels of attention to pollinator population topics relative to coverage of climate change, which we use as a comparison topic. In the most recent subset of ~10 million stories published from 2007 to 2019, 1.39% (137,086 stories) refer to climate change/global warming, while only 0.02% (1,780) refer to pollinator populations in all contexts and just 0.007% (679) refer to pollinator declines. Substantial increases in news attention were detectable only in U.S. national newspapers. We also find that while climate change stories appear primarily in newspaper “front sections”, pollinator population stories remain largely marginalized in “science” and “back section” reports. At the same time, news reports about pollinator populations increasingly link the issue to climate change, which might ultimately help raise public awareness to effect needed policy changes.
keywords:
News Coverage; Text Analytics; Insects; Pollinator; Cline Center; Cline Center for Advanced Social Research; political; social; political science; Global News Index; Archer; news; mass communication; journalism
published: 2020-08-10
Zinnen, Jack; Spyreas, Greg; Erdős, László; Berg, Christian; Matthews, Jeffrey (2020): Expert-based measures of human impact to vegetation- Bibliographic analysis. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9374105_V1
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).
keywords:
Web of Science; bibliographic analyses; vegetation; VOSviewer