TY  - RPRT
T1  - Making Confidential Data Part of Reproducible Research
Y1  - 2017
A1  - Lars Vilhuber
A1  - Carl Lagoze
PB  - Labor Dynamics Institute, Cornell University
UR  - http://digitalcommons.ilr.cornell.edu/ldi/41/
ER  - 

TY  - JOUR
T1  - Data Management of Confidential Data
JF  - International Journal of Digital Curation
Y1  - 2013
A1  - Carl Lagoze
A1  - William C. Block
A1  - Jeremy Williams
A1  - John M. Abowd
A1  - Lars Vilhuber
AB  - Social science researchers increasingly make use of data that is confidential because it contains linkages to the identities of people, corporations, etc. The value of this data lies in the ability to join the identifiable entities with external data such as genome data, geospatial information, and the like. However, the confidentiality of this data is a barrier to its utility and curation, making it difficult to fulfill US federal data management mandates and interfering with basic scholarly practices such as validation and reuse of existing results. We describe the complexity of the relationships among data that span a public and private divide. We then describe our work on the CED2AR prototype, a first step in providing researchers with a tool that spans this divide and makes it possible for them to search, access, and cite that data.
VL  - 8
N1  - Presented at 8th International Digital Curation Conference 2013, Amsterdam. See also http://hdl.handle.net/1813/30924
ER  - 

TY  - CONF
T1  - Encoding Provenance of Social Science Data: Integrating PROV with DDI
T2  - 5th Annual European DDI User Conference
Y1  - 2013
A1  - Carl Lagoze
A1  - William C. Block
A1  - Jeremy Williams
A1  - Lars Vilhuber
KW  - DDI
KW  - eSocial Science
KW  - Metadata
KW  - Provenance
AB  - Provenance is a key component of evaluating the integrity and reusability of data for scholarship. While recording and providing access provenance has always been important, it is even more critical in the web environment in which data from distributed sources and of varying integrity can be combined and derived. The PROV model, developed under the auspices of the W3C, is a foundation for semantically-rich, interoperable, and web-compatible provenance metadata. We report on the results of our experimentation with integrating the PROV model into the DDI metadata for a complex, but characteristic, example social science data. We also present some preliminary thinking on how to visualize those graphs in the user interface.
JF  - 5th Annual European DDI User Conference
ER  -