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- 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 All citations to archival sources, government information, and other unpublished manuscript materials were excluded.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.
- Keyword:
- discovery, history, secondary literature, information retrieval, reference analysis, citation analysis, library science, university libraries, and research libraries
- Citation to related publication:
- Pearce, A. (2019). Discovery and the Disciplines: An Inquiry into the Role of Subject Databases through Citation Analysis. College & Research Libraries, 80(2), 195. doi: https://doi.org/10.5860/crl.80.2.195
- Discipline:
- Social Sciences
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- Creator:
- Steiner, Allison and Li, Yang
- Description:
- Case 2 of Li et al. (2016) LES simulations for the DISCOVER-AQ 11 campaign, including three different grid resolutions (96, 197 and 320 grid cell resolutions), plus simulations at the 192 grid resolution with and without aqueous chemistry
- Citation to related publication:
- Li, Y., M. C. Barth, E.G. Patton and A.L. Steiner, Impact of in-cloud aqueous processes on the chemistry and transport of biogenic volatile organic compounds, Journal of Geophysical Research – Atmospheres, 2017. https://doi.org/10.1002/2017JD026688
- Discipline:
- Science
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- Creator:
- Steiner, Allison and Li, Yang
- Description:
- Case 1: A fair weather condition; Case 2: A convective event; Case 3: A polluted event with high temperature and convection
- Keyword:
- LES, boundary layer, turbulence, and BVOC Chemistry
- Citation to related publication:
- Li, Y., M. C. Barth, G. Chen, E. G. Patton, S.-W. Kim, A. Wisthaler, T. Mikoviny, A. Fried, R. Clark, and A. L. Steiner (2016), Large-eddy simulation of biogenic VOC chemistry during the DISCOVER-AQ 2011 campaign, J. Geophys. Res. Atmos., 121, 8083–8105. https://doi.org/10.1002/2016JD024942
- Discipline:
- Science
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- Creator:
- Engel, Daniel D. , Evans, Mary Anne, Low, Bobbi S., and Schaeffer, Jeff
- Description:
- This dataset was compiled as an attempt to understand how natural resource managers and research ecologists in the Great Lakes region integrate the ecosystem services (ES) paradigm into their work. The following text is the adapted abstract from a thesis associated with this data. Ecosystem services, or the benefits people obtain from ecosystems, have gained much momentum in natural resource management in recent decades as a relatively comprehensive approach to provide quantitative tools for improving decision-making and policy design. However, to date we know little about whether and how natural resource practitioners, from natural resource managers to research ecologists (hereafter managers and ecologists respectively), have adopted the ES paradigm into their respective work. Here, we addressed this knowledge gap by asking managers and ecologists about whether and how they have adopted the ES paradigm into their respective work. First, we surveyed federal, state, provincial and tribal managers in the Great Lakes region about their perception and use of ES as well as the relevance of specific services to their work. Although results indicate that fewer than 31% of the managers said they currently consider economic values of ES, 79% of managers said they would use economic information on ES if they had access to it. Additionally, managers reported that ES-related information was generally inadequate for their resource management needs. We also assessed managers by dividing them into identifiable groups (e.g. managers working in different types of government agencies or administrative levels) to evaluate differential ES integration. Overall, results suggest a desire among managers to transition from considering ES concepts in their management practices to quantifying economic metrics, indicating a need for practical and accessible valuation techniques. Due to a sample of opportunity at the USGS Great Lakes Science Center (GLSC), we also evaluated GLSC research ecologists’ integration of the ES paradigm because they play an important role by contributing requisite ecological knowledge for ES models. Managers and ecologists almost unanimously agreed that it was appropriate to consider ES in resource management and also showed convergence on the high priority ES. However, ecologists appeared to overestimate the adequacy of ES-related information they provide as managers reported the information was inadequate for their needs. This divergence may reflect an underrepresentation of ecological economists in this system who can aid in translating ecological models into estimates of human well-being. As a note, the dataset for the research ecologists has had some data removed as it could be considered personally identifiable information due to the small sample size in that population. The surveys associated with both datasets have also been included in PDF format. Curation Notes: Three files were added to the data set on Dec 21, 2017. Two csv files: "Ecosystem services and Research Ecologists - Data Index.csv" and "Ecosystem services and Research Managers - Data Index.csv" and one text file: "Ecosystem Services Adoption Readme.txt". The file names of the original four files were altered to replace an ampersand with the word "and".
- Keyword:
- Research Ecologist, Decision-Making, Ecosystem Services, Natural Resource Management, Paradigm Adoption, and Ecological Economics
- Citation to related publication:
- Engel, D.D., Evans, M.A., Low, B.S., Schaeffer, J. (2017) “Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists.” Journal of Great Lakes Research, 43(3), 169-179. https://doi.org/10.1016/j.jglr.2017.01.005
- Discipline:
- Science and Social Sciences
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- Creator:
- Beck, Jess
- Description:
- These data include skeletal and dental inventories, assessments of skeletal and dental pathology, and the age and sex of individuals buried at Necropolis 1, Necropolis 2, and Necropolis 4 at the Copper Age site of Marroquíes Bajos. They are shared here in accordance with the NSF Data Management Plan associated with Doctoral Dissertation Improvement Grant BCS-1440017.
- Keyword:
- Iberia, Archaeology, Copper Age, and Bioarchaeology
- Discipline:
- Social Sciences
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- Creator:
- Saini, Sameer D
- Description:
- See attached survey and codebook
- Discipline:
- Health Sciences
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- Creator:
- Blesh, Jennifer
- Description:
- This dataset contains three data files used in: Blesh, J. 2017. Functional traits in cover crop mixtures: biological nitrogen fixation and multifunctionality. Journal of Applied Ecology. There are also three corresponding metadata files. The file “Ecosystem_functions_soil_species.csv” contains data organized by farm, treatment, replicate block, and species combining the fall and spring sampling time points. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation for the plant species. The dataset also includes measured soil characteristics for each farm site. The file “Ecosystem_functions_soil_treatment.csv” contains data organized by farm, treatment, and replicate block for the fall and spring sampling time points combined. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation aggregated by treatment. The dataset also includes measured soil characteristics for each farm site. The file “Traits_unstandardized.csv” contains individual plant trait data, a subset of which were used to calculate an index of functional diversity after they were standardized to have zero mean and unit variance. These data are organized by farm, treatment, replicate block, and species. The corresponding metadata files: “Ecosystem_functions_soil_species_metadata.csv”, “Ecosystem_functions_soil_treatment_metadata.csv”, and “Traits_unstandardized_metadata.csv” provide a detailed description of all variables in each dataset and any abbreviations used. Note: On Dec 19th 2017, the format of the files was changed to csv to aid preservation. 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.
- Keyword:
- agroecology, biological nitrogen fixation, functional diversity, and cover crop
- Citation to related publication:
- Blesh J. Functional traits in cover crop mixtures: Biological nitrogen fixation and multifunctionality. J Appl Ecol. 2018;55:38–48. https://doi.org/10.1111/1365-2664.13011
- Discipline:
- Science
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- Creator:
- Moldwin, Mark B
- Description:
- Tab delimited file containing the records of all papers published in JGR-Space Physics in 2012. The records were pulled from Thomsen-Reuters ISI-Web-of-Science on June 3, 2016 including citations. Gender was identified independently by the creator of the file.
- Keyword:
- Gender and Nationality Bias, Space Physics, and Bibliometrics
- Citation to related publication:
- Moldwin, M. B., & Liemohn, M. W. (2018). High‐citation papers in space physics: examination of gender, country, and paper characteristics. Journal of Geophysical Research: Space Physics, 123. https://doi.org/10.1002/2018JA025291
- Discipline:
- Science
-
- Creator:
- Cheng, Hao Fei, Hecht, Brent , Wheeler, Earnest, Wang, Xinyi, Zhu, Haiyi, and Dillahunt, Tawanna R
- Description:
- The sharing economy has quickly become a very prominent subject of research in the broader computing literature and the in human–computer interaction (HCI) literature more specifically. When other computing research areas have experienced similarly rapid growth (e.g. human computation, eco-feedback technology), early stage literature reviews have proved useful and influential by identifying trends and gaps in the literature of interest and by providing key directions for short- and long-term future work. In this paper, we seek to provide the same benefits with respect to computing research on the sharing economy. Specifically, following the suggested approach of prior computing literature reviews, we conducted a systematic review of sharing economy articles published in the Association for Computing Machinery Digital Library to investigate the state of sharing economy research in computing. We performed this review with two simultaneous foci: a broad focus toward the computing literature more generally and a narrow focus specifically on HCI literature. We collected a total of 112 sharing economy articles published between 2008 and 2017 and through our analysis of these papers, we make two core contributions: (1) an understanding of the computing community’s contributions to our knowledge about the sharing economy, and specifically the role of the HCI community in these contributions (i.e. what has been done) and (2) a discussion of under-explored and unexplored aspects of the sharing economy that can serve as a partial research agenda moving forward (i.e. what is next to do).
- Keyword:
- Collaborative and social computing, Human-computer interaction interaction, and Human-centered computing
- Citation to related publication:
- Dillahunt, T. R., Wang, X., Wheeler, E., Cheng, H. F., Hecht, B., & Zhu, H. (2017). The Sharing Economy in Computing: A Systematic Literature Review. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW), 38:1-38:26. https://doi.org/10.1145/3134673
- Discipline:
- Other
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- Creator:
- Eby, David W and Molnar, Lisa J
- Description:
- Data are contained in an Excel spreadsheet formatted such that each row is a separate participant and each column is a separate question. This file is called: EbyEtAl-TransportCaregiver. A data dictionary that gives the text for each question and the response categories mappings is contained in another Excel Spreadsheet. This file is called: EbyEtAl-TransportCaregiverDictionary. The text of the survey, the development of weights, and response rate calculations can be found in the Deep Blue report discussed previously.
- Keyword:
- Caregiver Burden, Driving, and Automobile
- Citation to related publication:
- Eby, D.W., Molnar, L.J., Kostyniuk, L.P., St. Louis, R.M., & Zanier, N. (2011). Recommendations for Meeting the Needs of Michigan’s Aging Population. Report No. RC-1562. Lansing, MI: Michigan Department of Transportation. This report can be found on Deep Blue: https://deepblue.lib.umich.edu/handle/2027.42/90961
- Discipline:
- Social Sciences