Index Catalog // Scholar@UC

Table 1 IDCC 2018 Institutional Repository Comparison

Type:: Dataset
Descripción/Resumen:: This table compares the major characteristics of the four sources repositories in in the metadata study
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 07/03/2018
Fecha modificada:: 07/03/2018
Fecha de creacion:
Licencia:: Open Data Commons Attribution License (ODC-By)

Table 3 IDCC2018 Detailed Metadata Comparison

Type:: Document
Descripción/Resumen:: This table compares metadata elements for data sets in four institutional repositories and includes the Dublin Core metadata elements they map to.
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 03/22/2018
Fecha modificada:: 05/31/2018
Fecha de creacion:: 2017-10-21
Licencia:: Attribution-NonCommercial-ShareAlike 4.0 International

Table 2 IDCC2018 Required and Optional Metadata Comparison

Type:: Document
Descripción/Resumen:: This figure compares optional and required metadata fields for data sets for four institutional repositories -UC, U Michigan, U Minnesota, and Oregon State
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 03/22/2018
Fecha modificada:: 05/15/2018
Fecha de creacion:: 2017-10-21
Licencia:: Attribution-NonCommercial-ShareAlike 4.0 International

Figure 1 IDCC 2018 Significance analysis metadata study four institutional repositories

Type:: Dataset
Descripción/Resumen:: This data set describes the Mann-Whitney U test statistical analysis of the completeness profile for data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/12/2018
Fecha modificada:: 05/15/2018
Fecha de creacion:: 2017-09
Licencia:: Open Data Commons Attribution License (ODC-By)

Figure 4 IDCC2018 Keywords data sets four institutional repositories

Type:: Dataset
Descripción/Resumen:: This data set measures the number of keywords associated with data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/12/2018
Fecha modificada:: 05/15/2018
Fecha de creacion:: 2017-09
Licencia:: Open Data Commons Attribution License (ODC-By)

Figure 3 IDCC 2018 Digital object identifiers for data sets in four institutional repositories

Type:: Dataset
Descripción/Resumen:: This data set measures whether data sets in four institutional repositories have digital object identifiers or not. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/12/2018
Fecha modificada:: 05/15/2018
Fecha de creacion:: 2017-09
Licencia:: Open Data Commons Attribution License (ODC-By)

Figure 2 IDCC2018 Documentation for data sets in four institutional repositories

Type:: Dataset
Descripción/Resumen:: This data set describes the type and number of documentation that accompany and describe data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/12/2018
Fecha modificada:: 05/15/2018
Fecha de creacion:: 2017-09
Licencia:: Open Data Commons Attribution License (ODC-By)

Figure 1 IDCC 2018 Percent Completeness of Data Set Metadata

Type:: Dataset
Descripción/Resumen:: This data set describes the percent completeness of metadata options for data sets in four institutional repositories. It is a derivative data set from the master data set entitled "Metadata of data sets from four institutional repositories" https://scholar.uc.edu/show/pn89d657h Please use the Citation: Koshoffer, A., Neeser, A., Johnston L.R., and Newman L.D., (2018) "Giving datasets context: a comparison study of institutional repositories that apply varying degrees of curation", International Digital Curation Conference, Barcelona, Spain. Digital Curation Centre.
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/12/2018
Fecha modificada:: 10/27/2018
Fecha de creacion:: 2017-09
Licencia:: Open Data Commons Attribution License (ODC-By)

Master Data set - Metadata of data sets from four institutional repositories

Type:: Dataset
Descripción/Resumen:: This data set is the raw data underlying the paper entitled "Giving datasets context: a comparison study of institutional repositories that apply varying degrees of curation" presented at the International Digital Curation Conference in Barcelona, Spain (Feb 2018). All figures and tables in the publication were based on the analysis of this data set. Please use the Citation: Koshoffer, A., Neeser, A., Johnston L.R., and Newman L.D., (2018) "Giving datasets context: a comparison study of institutional repositories that apply varying degrees of curation", International Digital Curation Conference, Barcelona, Spain. Digital Curation Centre.
Creador/Autor:: Koshoffer, Amy; Newman, Linda; Neeser, Amy, and Johnston, Lisa
Peticionario:: Amy Koshoffer
Fecha modificada:: 01/11/2018
Fecha modificada:: 10/27/2018
Fecha de creacion:: 2016-06 to 2017-10
Licencia:: Open Data Commons Attribution License (ODC-By)

De-identifying Data

Type:: Media
Descripción/Resumen:: This webinar aired on January 12, 2016 for members of the DataCure listserv. The webinar covered issues around sensitive data and how to establish a educational program to help researchers protect sensitive data while sharing results of their research. The presenters were Brett Harnett, Director of the UC Center for Health Informatics ( http://www.med.uc.edu/chi) and Jonathan Petters Ph.D. Data Management Consultant at Johns Hopkins University ( http://dmp.data.jhu.edu/). Presentation 1 - Brett Harnett- the process of de-identifying data especially data resulting from medical records, issues around de-identifying especially unstructured data, working with an IRB and future issues concerning data containing PHI. Presentation 2 - Jonathan Petters - training for de-identifying human subjects data for sharing and developing a viable library service.
Creador/Autor:: Koshoffer, Amy; Harnett, Brett, and Petters, Jonathan
Peticionario:: Amy Koshoffer
Fecha modificada:: 03/09/2016
Fecha modificada:: 11/18/2016
Fecha de creacion:: 2016-03-09
Licencia:: Attribution-NonCommercial-NoDerivs 4.0 International

Table 1 IDCC 2018 Institutional Repository Comparison

Table 3 IDCC2018 Detailed Metadata Comparison

Table 2 IDCC2018 Required and Optional Metadata Comparison

Figure 1 IDCC 2018 Significance analysis metadata study four institutional repositories

Figure 4 IDCC2018 Keywords data sets four institutional repositories

Figure 3 IDCC 2018 Digital object identifiers for data sets in four institutional repositories

Figure 2 IDCC2018 Documentation for data sets in four institutional repositories

Figure 1 IDCC 2018 Percent Completeness of Data Set Metadata

Master Data set - Metadata of data sets from four institutional repositories

De-identifying Data

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