Browsing by Type "Dataset"

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    18th century English pediatric hospital care
    (2014-06-25) Williams, Andrew N.; Sharma, Raman M.
    Until recently, physician-historians of pediatrics have generally assumed that “pediatrics as a specialized branch of medicine had no real existence before the middle of the nineteenth century” (Abt Garrison. History of Pediatrics, WB Saunders: London; 1965. p.1). This may be true if we equate pediatrics with professional organizations and specialized children’s hospitals (Cone TE. History of American Pediatrics, Boston: 1979; Mahnke CB. ‘The growth and Development of a Specialty: The History of Pediatrics’. Clinical Pediatrics. 2000; 12: 705-714). But as a body of knowledge and practices addressing the sick child, pediatrics has a much longer history (Newton H. The Sick Child in Early Modern England, 1580-1720. Oxford University Press, United Kingdom 2012; Levene A. Childhood and Adolescence In Jackson M. (ed) The Oxford Handbook of the History of Medicine. Oxford University Press. United Kingdom 2012 DOI: 10.1093/oxfordhb/9780199546497.013.0018). Reconstructing the history of what might be called “pediatrics before pediatricians” requires going beyond the rare books and treatises that were long the traditional sources for medical historians. This dataset, compiled from 18th century English hospital admission records, is the first of its kind in this area.
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    2000 NHGRI e-mail request for HGP sequencing center information, and corresponding aggregate data from NHGRI, compiled by Kris Wetterstrand
    (2016-08-31)
    Email exchange in 2013 between Kathryn Maxson (Duke) and Kris Wetterstrand (NHGRI), regarding country funding and other data for the HGP sequencing centers. Also includes the email request for such information, from NHGRI to the centers, in 2000, and the aggregate data collected.
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    Exploring lemur olfactory communication
    (2015-11-30) Smyth, Kendra; Greene, Lydia
    In Fall 2015, we (Kendra Smyth & Lydia Greene) led a Data Expeditions (DE) workshop in Advanced Research in Evolutionary Anthropology, a senior-level class on the research process. The goal of the workshop was to get students familiar with the R language and introduce them to a range of statistical techniques that might be useful for analyzing their own senior thesis data. In the workshop, we used a lemur scent-marking dataset compiled by Greene during her undergraduate honors thesis at Duke. By using these data, we aimed to make statistics seem both accessible and relatable to these students. Although teaching students the specific commands in R is undeniably valuable, the true reward from the Data Expeditions came from seeing students understand key concepts in statistics and from giving them the tools to begin the process of analyzing their own data.
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    Jarāʾid: A chronology of Arabic periodicals (1800-1929)
    (2020-12-28) Mestyan, Adam; Grallert, Till
    Bibliographical data set for all periodicals published globally in Arabic (or Arabic plus additional languages) between 1800 and 1929.
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    Major League Baseball and National Basketball Association regular season data by team
    (2014) Futoma, Joseph; McAlinn, Kenichiro
    With the rise of sports statistics, especially sabermetrics in baseball, statistics have proven crucial not only for managing teams and assessing player value, but also for forecasting team and individual performance. In this data expedition, we provided undergraduates with detailed information about each team from every NBA and MLB game during the 2010-2011 and 2013 seasons, respectively. For baseball, for each of the 2430 games we have 23 batting stats (e.g. hits, runs batted in, homeruns) and 23 pitching stats (e.g. strikeouts, runs allowed). For basketball, we have 20 stats (e.g. field goals, free throws, rebounds), for each of the 1230 games.
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    Math 412: Music + Topology
    (2014) Tralie, Christopher
    In this mini assignment you will explore an application of "sliding windows and persistence" on time series data (see Jose Perea's paper for more theory). Specifically, you will look at how to transform musical audio data into a high dimension point cloud/curve which can be probed with TDA methods. You will make use of a visualization program called LoopDitty to gain some intuition about what points in various persistence diagrams might mean. Please follow the directions below and submit an electronic writeup to chris.tralie@gmail.com with the answers to all of the questions and any observations you have. Enjoy!
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    North Carolina Traffic Stops
    (2014) OwensOas, Derek
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    Signal, noise, and bias in yeast MNase-seq data
    (2014) MacAlpine, David Michael
    This is an optional challenge for students interested in applying what we have learned in class to a real computational genomics research problem; practicing the skills of using Python or R (or any other tool you wish) to visualize, analyze, model, and interpret real genomic data; and exploring the science linking chromatin structure and transcriptional regulation. Since this problem represents an open challenge for the genomics community, you are free to choose the approaches you use to analyze the data, as well as the questions you explore.