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  • Data for "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model"

    Work
    Creator: Fries, Kevin J
    Description: This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings. For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site. For the IFIS gages, each tab delimited file is for a single site for the period of record.
  • S'Urachi Site-Based Archaeological Survey 2015

    Work
    Creator: Gosner, Linda R. and Smith, Alexander J.
    Description: Included here are 1) a detailed description of each of the dataset's components, 2) a database of all finds from the 2015 survey, 3) a database of faunal bone compiled by specialist Damià Ramis, 4) a description of the finds by category to accompany these databases, 5) a PDF of notes taken in the field, 6) field photographs of survey units, 7) object photographs of all finds, and 8) drawings of diagnostic ceramics by time period.
  • Computer Data from Ross Thesis

    Work
    Creator: Mathews, Elizabeth and Verhoff, Frank
    Description: Each pdf is an electronic version of the paper output for each experiment. Each text file is the electronic version of the data on the computer cards for each experiment. These text files are directly readable by Excel. Once in Excel, the data can be manipulated as desired. Additional information is in the theses.
  • Input files for the Global Ionosphere Thermosphere Model for 2010

    Work
    Creator: Ridley, Aaron
    Description: These files (2010_gitm_input_files.tgz) were used to run GITM for 2010 for each month. GITM paper is here: (10.1016/j.jastp.2006.01.008 <http://dx.doi.org/10.1016/j.jastp.2006.01.008>) GITM code is in file gitm_170809.tgz
  • Neighborhood effects : Health Status

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    Creator: Veinot,Tiffany,C., Data Driven Detroit, and Okullo, Dolorence
    Description: Health status data includes data about the health of persons within a census tract in Metropolitan Detroit, measured at the census tract level. This includes data about 1) mortality by condition; 2) exposures to toxic substances; and 3) disability. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
  • Neighborhood effects : Housing

    Work
    Creator: Veinot, Tiffany, Yu, DeAhean, Data Driven Detroit, Okullo, Dolorence, Gomez-Lopez, Iris N., and Yan, Xiang (Jacob)
    Description: This dataset includes census tract-level data concerning housing in Metropolitan Detroit. The data includes: 1) Total housing units and total mortgages in the tract; 2) Land use; 3) Real estate information (foreclosures, sales transactions, and home values); 4) Vacant housing; 5) Housing age and available facilities; 6) Housing condition; and 7) Spatial measures of subsidized housing in the tract. Data coverage should say 2006 to 2015.
  • Centimeter-Scale Electron Diffusion in Photoactive Organic Heterostructures

    Work
    Creator: Forrest, Stephen R., Panda, Anurag, Qu, Yue, Che, Xiaozhou, Coburn, Caleb, and Burlingame, Quinn
    Description: Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier. Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1
  • Crop rotations for increased soil carbon: perenniality as a guiding principle

    Work
    Creator: Blesh, Jennifer and King, Alison E.
    Description: This dataset contains three data files used in: King, A.E. and J. Blesh, 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecological Applications. There are also three corresponding metadata files. The file “CRMA 2017 Main.csv” contains data for the control and treatment rotations used to construct pairwise comparisons for meta-analysis, response ratios calculated for soil organic carbon concentration, and change in carbon input. The dataset also includes management, soil, and other environmental characteristics for each site. The file “CRMA 2017 Diversity x Nitrogen.csv” contains data used to test whether N fertilizer inputs mediated the effect of functional diversity on SOC concentrations. The file “CRMA Annual grain.csv” contains data used to test for effects of crop rotation species diversity (one vs. two species, or two vs. three species) on SOC concentrations and C input (i.e., for the “grain-only” rotations). The dataset also includes management, soil, and other environmental characteristics for each site. The corresponding metadata files: “CRMA 2017 Main_metadata.csv”, “CRMA 2017 Diversity x Nitrogen_metadata.csv”, and “CRMA Annual grain _metadata.csv” provide a detailed description of all variables in each dataset. Note: On Jan 12, 2018 the following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
  • WRF-Chem Central US - Hygroscopicity tests

    Work
    Creator: Steiner, Allison and Kawecki, Stacey
    Description: WRF-Chem model
  • Discovering History: An Analysis of Secondary Literature Cited in the American Historical Review, 2010-2015

    Work
    Creator: Pearce, Alexa L.
    Description: This dataset accompanies a study that seeks to contribute to a clearer understanding of the discovery ecosystem in academic research libraries. Using historical literature as a case study, extensive citation analysis is employed to both reveal characteristics of secondary historical literature as well as to test a broad disciplinary discovery environment that includes six specific search platforms. By enhancing our understanding of where and how specific types of resources are –or are not—discoverable, as the case may be, this study can provide evidence to better inform the appropriate role and placement of various search platforms in a user’s process. This citation analysis drew upon all secondary literature that was cited in the American Historical Review (AHR) during a six-year period, from 2010 through 2015. The AHR is the official publication of the American Historical Association (AHA) and, as stated on its website, has served as “the journal of record for the historical profession in the United States since 1895.” Additionally, the AHR represents all subfields of history in its research articles and reviews of new scholarship. For this study, the author gathered citations from research articles only, excluding reviews. For the purposes of testing the library discovery environment, the author aimed to include citations that a researcher would be likely to identify by using library research tools, as opposed to archival finding aids. Recognizing that some tools included in this study, such as JSTOR and Historical Abstracts, do not index archival sources, the author decided to focus on published and secondary materials. All citations to archival sources, government information, and other unpublished manuscript materials were excluded. Additionally, citations to newspaper and general or popular press articles published prior to 1900 were excluded. Citations to entire periodicals, as opposed to articles, were also excluded. Books from all date ranges were included. Citations to non-scholarly newspaper and magazine articles published after 1900 were included. Citations to published primary sources were also included in the population of citations, as one may reasonably expect to locate them in a research library setting. The resulting population comprised 22,572 citations. After separating out duplicate citations, the total number was 19,937. Using a random number generator, the de-duplicated list of citations was re-ordered in order to select a random sample of 400, which affords a confidence level of 95% and a confidence interval of 5. The first step in analysis was to characterize each citation according to format, publication date, and language. Secondly, the author searched for all citations in the sample in the 6 different search platforms listed above. The primary question for each database included in the study was how comprehensively it represented the population of AHR citations, as represented by the random sample selected for this study. In order for a given citation to count as present in a particular database, it had to be represented in the format in which it was cited. For example, if a search for a cited book turned up only a dissertation, with the same author and very similar title, the analysis found that the citation was not present. For book chapters cited with authors and titles, it was not necessary for chapters to have their own records in order to be counted as present but it was necessary for them to be discernible among search results as chapters, such as in a table of contents listing. In order to expedite the search process, the author searched Historical Abstracts and America: History and Life simultaneously on the EBSCO platform. For all of the platforms except Google Scholar, the author performed advanced searches, entering both title and author information for each citation. All searching took place between February and May of 2017. The results presented here reflect the content available to search in each platform at the time of investigation.