1,725,611 research outputs found
Data supporting “Data Sharing Readiness in Academic Institutions” Version 1.0
No full textOne CSV datafile and a readme.txt explaining the columns used as well as the data collection methodology. Version 1.0 is the original data collected by the authors. Any subsequent versions may include corrections by repository owners, as invited by the related publication.To address how has the academic landscape for data repository and curation services changed we used website content analysis to better understand data repository services in academic research libraries, building on the 2017 ARL Spec Kit for Data Curation (Hudson-Vitale et al., 2017a). Of the 124 ARL institutions we chose to focus on academic institutions, and therefore excluded 10 civic libraries. For each of the remaining 114 ARL institutions we asked four research questions: Do they support data sharing via data repository services? How many datasets did they hold as of January 2020? What digital repository software platform was in use? How do our results compare with the 2017 ARL SPEC Kit data.Alfred P Sloan FoundationJohnston, Lisa R; Coburn, Liza. (2020). Data supporting “Data Sharing Readiness in Academic Institutions” Version 1.0. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/2evx-7a87
Level of curation self-reported by 100 CoreTrustSeal certified repositories (2017-2019)
No full textThis dataset extracts and makes machine-actionable the responses to the "Level of curation performed" component of the CoreTrustSeal application v01 (2017-2019). The author reviewed 100 applications in pdf file format and compiled the responses into one spreadsheet for further analysis. Additionally, the CTS application instructions for v01 were parsed in order to analyze the completed applications and included here in a spreadsheet.Alfred P Sloan FoundationJohnston, Lisa R. (2021). Level of curation self-reported by 100 CoreTrustSeal certified repositories (2017-2019). Retrieved from the University Digital Conservancy, https://doi.org/10.13020/w0z3-z709
Summary of the "Data Curation Handbook Steps" from Curating Research Data Volume Two: A Handbook of Current Practice
No full textAn excerpt from the Foreword chapter of Curating Research Data Volume Two: A Handbook of Current Practice by Lisa R Johnston for ACRL.Johnston, Lisa R. (2017). Summary of the "Data Curation Handbook Steps" from Curating Research Data Volume Two: A Handbook of Current Practice. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/183502
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
In Re Lisa R.? - Limiting the Scope of the Conclusive Presumption Doctrine
Full text linkThis Comment traces the development of the conclusive presumption doctrine, determine its relationship to traditional substantive and procedural due process analysis, and point out the inherent limitations of the doctrine which are recognized in In re Lisa R
Analyzed Data Management Plans (DMPs) from Successful University of Minnesota Grants from the National Science Foundation, 2011-2014
No full textThis data set consists of five files. The excel file (UMN_DMPReview_2011-2014_v2.xslx) represents the de-indentifed and analyzed data management plans (DMPs) from successful grants. These data are based on the review instrument, which is included both as a pdf and a png image file (UMN_DMPReviewInstrument). Included is also a text readme file (DMPReviewInstrument_Readme_v2) containing information about the study and data. Finally, there is a zipped archival copy of the excel data file that has been converted to two .csv files (Archival Version of Data).Federal funding agencies are asking principal investigators (PIs) to specify their plans for describing, storing, securing, sharing, and preserving their research data in Data Management Plans (DMPs) included with their grant proposal. This change in sponsored research is best exemplified by the National Science Foundation (NSF) which in 2010 announced that all grants submitted after January 18th, 2011 must include a one- to two-page DMP with all new proposals. In order to review the plans for how University of Minnesota researchers plan to manage, store, describe, protect, and share and preserve their data, a review instrument was created and implemented by the University Libraries in the summer of 2014. Our local study of DMPs in successful NSF grant applications from January 2011 - June 2014 was opt-in by U of M PIs and the libraries collected 182 data management plans for our study, accounting for 41% of the total number of plans solicited. The deidentified data used in our analysis and our survey instrument are presented here.Johnston, Lisa R; Bishoff, Carolyn; McGrory, John; Storino, Chris; Swendsrud, Anders. (2015). Analyzed Data Management Plans (DMPs) from Successful University of Minnesota Grants from the National Science Foundation, 2011-2014. Retrieved from the University Digital Conservancy, http://dx.doi.org/10.13020/D6TG6Z
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Developing a Data Curation Service: Step #1: Work With What You’ve Got
Full text linkJohnston, Lisa R. (2014). Developing a Data Curation Service: Step #1: Work With What You’ve Got. Retrieved from the University Digital Conservancy, 10.1002/bult.2014.1720400416
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