2024-03-28T13:45:04Zhttps://kuscholarworks.ku.edu/oai/requestoai:kuscholarworks.ku.edu:1808/274512020-10-12T14:41:15Zcom_1808_11004com_1808_54col_1808_12487
Wackerow, Joachim
Hoyle, Larry
2018-12-03T20:25:46Z
2018-12-03T20:25:46Z
2018-12-04
http://hdl.handle.net/1808/27451
https://orcid.org/0000-0002-8262-2393
Model based DDI4 lends itself to a representation in a language with object oriented structures. This presentation describes an ongoing project implementing the complete DDI4 model in R. We currently have the complete structure represented as R6 objects. Future work will focus on a graphical user interface for entering metadata and on capturing metadata about transformations. Import and export of DDI and a human readable codebook are also planned.
Each DDI4 class is modeled as an (object oriented) R6 class. This approach yields several useful capabilities. Properties and relationships of objects are validated as to correct datatype and cardinality as they are instantiated. Existence of DDI URNs is validated against an internal registry and via an XML catalog. The latter allows for validating the existence of an external object. DDI metadata are attached to existing R objects as attributes having DDI URNs as their values.
The DDI4R package, including documentation, is generated programmatically directly from the DDI4 model XMI file available on the DDI4 website.
Having metadata objects in R may also offer interesting future possibilities for operations directly on metadata. Sum and difference operators on Collections, for example might be useful in harmonization.
openAccess
DDI4 R
Implementing the DDI4 Model in the R Language
Presentation
oai:kuscholarworks.ku.edu:1808/157462019-04-12T14:36:30Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
Vardigan, Mary
Hume, Sam
Ionescu, Sanda
Greenfield, Jay
Iverson, Jeremy
Kunze, John
Radler, Barry
Weibel, Stuart
Witt, Michael C.
Thomas, Wendy
2014-11-13T17:38:36Z
2014-11-13T17:38:36Z
2014-11-17
http://hdl.handle.net/1808/15746
Work products from the the NSF1448107 sponsored group attending Dagstuhl event 14432 in October 2014. These include datasets, analysis programs, and a technical report.
en_US
openAccess
Data Citation
Data Documentation Initiative
Comprehensive Citation Across the Data Life Cycle Using DDI
Dataset
Technical Report
oai:kuscholarworks.ku.edu:1808/206822018-05-23T16:45:52Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
2016-04-18T14:50:17Z
2016-04-18T14:50:17Z
2016-04-08
http://hdl.handle.net/1808/20682
https://orcid.org/0000-0002-8262-2393
This closing plenary presentation from the 2016 North American Data Documentation Initiative conference (NADDI2016) traces the evolution of the Data Documentation Initiative DDI metadata standard from initial meetings in 1993 to the present (2016). Major themes are the development of the notion of reusable data and metadata in a data lifecycle context, the movement beyond a survey centric orientation, and the support for reproducible research.
openAccess
Data Documentation
DDI
DDI-C
DDI-L
DDI4
NADDI
Metadata
The Evolution of DDI, Concepts and Technology
Presentation
oai:kuscholarworks.ku.edu:1808/206812018-05-23T16:46:25Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
2016-04-18T14:37:18Z
2016-04-18T14:37:18Z
2016-04-07
http://hdl.handle.net/1808/20681
https://orcid.org/0000-0002-8262-2393
This presentation explores the current set of classes for describing qualitative data in the developing DDI4 model. The qualitative model is built on the work of DDI Moving Forward sprints, the DDI Qualitative Data Model Working Group, an NSF grant on enhanced citation, and an earlier metadata standard (Qudex). The current model includes the ability to describe the location of segments within objects; relationships between objects; relationships between segments within objects; and the attachment of memos, codes, and categories to segments. Discussion can include suggestions for further directions of the model.
openAccess
Data Documentation
DDI
DDI4
Qualitative
Qualitative Data in DDI Views (DDI4)
Presentation
oai:kuscholarworks.ku.edu:1808/124882019-04-12T14:14:26Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
2013-11-24T15:39:18Z
2013-12-05T13:10:03Z
2013-11-24
http://hdl.handle.net/1808/12488
All of the major data analysis software packages now allow some form of user defined extended attributes on variables and most also allow these attributes for the datasets themselves. In each case these attributes can be seen as a pair of strings (attribute name, attribute value). They can also be seen as a subject, predicate, object triple (variable, “has” attribute name, attribute value). This paper explores potential uses of these attributes and suggests directions for developing best practice guidelines for their use.
en_US
openAccess
Extended attributes
Metadata
DDI
Replication
Reuse
Using Extended Attributes in Data Analysis Software - Controlled Vocabularies, Tools and DDI
Presentation
oai:kuscholarworks.ku.edu:1808/199002019-04-12T14:18:05Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
Wackerow, Joachim
2016-02-07T17:34:19Z
2016-02-07T17:34:19Z
2016
Hoyle, Larry and Joachim Wackerow DDI as a Common Format for Export and Import for Statistical Packages. IASSIST Quarterly, Volume 39 Number 3 - 2015
http://hdl.handle.net/1808/19900
https://orcid.org/0000-0002-8262-2393
One of the roles the DDI standard can perform is to serve as a medium for the transfer of metadata and data across both space and time. A crucial component of this role is the ability to represent the data and metadata contained in common data analysis and management packages. This paper describes an experiment using the program Stat/Transfer to move datasets among five popular packages with DDI Lifecycle as an intermediary format.
We created a dataset in each of the five packages and then exported it to DDI Lifecycle via Stat/Transfer. We also created a DDI Lifecycle instance and an associated delimited dataset, containing as many of the metadata elements found in any of the five packages possible and then exported it to each of the packages. Success or failure to transfer was recorded for a set of generic metadata elements identified in an earlier paper. Using a commercial file transfer program helped identify which metadata elements were transferrable through a generally available machine actionable process. The experiment revealed some areas for potential improvements to DDI as well as suggestions for data analysis packages and research practices.
en_US
openAccess
DDI, data formats, metadata, statistical packages, Stat/Transfer, JMP, R, SAS, SPSS, Stata
DDI as a Common Format for Export and Import for Statistical Packages
Supplementary materials
oai:kuscholarworks.ku.edu:1808/262952018-05-09T19:34:31Zcom_1808_11004com_1808_54col_1808_12487
Hoyle, Larry
2018-04-09T19:46:08Z
2018-04-09T19:46:08Z
2018-04-06
http://hdl.handle.net/1808/26295
https://orcid.org/0000-0002-8262-2393
This presentation will be a first look at a sample codebook serialized in DDI4 XML. The sample codebook is for a subset of variables from the Australian Election Study, 2013 - au.edu.anu.ada.ddi.01259 from the Australian Data Archive (ADA). The subset was first developed at the DDI4 Dagstuhl week 2 Sprint 2016 as an example of physical formatting of data. A complete codebook for the subset was begun at the DDI4 Dagstuhl Week 1 Sprint 2017 as a test case for the simple codebook functional view. It has proved useful in showing what can be represented in the DDI4 model, as well as showing the style of the resulting XML.
The presentation will include a walk-through of the original codebook from the ADA showing how each piece of information is represented in DDI4 XML.
openAccess
DDI
DDI4
Codebook
DDI4 XML
A Sample Codebook in DDI4 XML
Presentation