Content Backlog
Work in Release Plan
Title | View status | Purpose | Description of view |
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Methodology | RELEASE 3 | To provide an understanding of the study design addressing a business case (e.g., research question) | A series of design specifications (see topic areas below), not necessarily in a predefined order, that as a whole, constitute the methodology. Also known as the study design. |
Qualitative | RELEASE 3 | To develop a robust XML-based schema for qualitative data exchange (compliant with DDI) and encourage tools development based upon these needs. (This purpose statement taken directly from DDI Qualitative Working Group) | The relevant set of elements to enable the description of qualitative data objects. This may include any non-numeric data types (rich text, audio/visual, etc.) as well as a description of the relevant processes that have been performed on these objects (utilising the appropriate objects from the Process package/view). Additional note from Achim, 22/8/2014: This package should also enable description by data records for qualitative segments and other objects like new data sources. This is basically a general description method for semantically not well known or well defined objects (at design time of DDI 4). This topic includes a focus on the draft model on qualitative data in terms of identifying objects which are already covered by the quantitative model, which can be described by data records, and which are necessary in a dedicated qualitative package. |
Classification | RELEASE 2 | The Classification view incorporates the objects required to represent and manage classifications in DDI 4.0. | The Classification view covers the structure and description of classifications, the management of classifications, and the relationships amongst classifications. |
Simple Codebook | RELEASE 3 | Packages together the basic contents of a data dictionary (simple data description) with high level information on the data (discovery, coverage, and data relationships). | |
Discovery | RELEASE 1 | Listing of the elements used in the disco RDF vocabulary that belong to other RDF vocabularies | |
Simple Instrument | RELEASE 2 | Develop a robust model that is comprised of core elements that ably describe a simple survey instrument. | Critical to this view is a recognition of data capture situations that are not questionnaire- or survey-centric. |
Simple Data Description | RELEASE 2 | To develop a robust model that can describe all aspects of simple, rectangular data file in our domain. | The model must include bridges from the physical representation of a rectangular data file to high-level conceptual objects in the model. |
Enhanced Citation | RELEASE 3 | DDI is positioned to respond to NSF citation needs (see body of user story) and will provide a logical place to record the needed citation information during a project's workflow. We should ensure that we have the necessary elements to record this enhanced citation in the object library and that any relevant views include that capability. | This would cross several views - for example Discovery, Classification, Methodology, and Complex Instrument, places where contribution to a published or reusable product (an instrument, a dataset, a study, etc) could be recorded. The work would include the specification of objects as well as the development of controlled vocabularies (e.g. for contributor role). |
Complex Data Description | RELEASE 3 | To develop a robust model that can describe aspects of more complex data file types. . | Any data file that is NOT simple (i.e. an unformatted (ASCII) rectangular data file): e.g., Multiple Data Sources, Stacked Datasets, Multi-dimensional Tables or Stores |
Complex Instrument | RELEASE 3 | Any instrument that is NOT simple. A complex data capture is probably defined by the execution of complex control sequences or processes |
Work proposed to be included in release plan (but not yet resourced)
Title | View status | Purpose | Description of view |
---|---|---|---|
Comparison/Harmonization | PROPOSED | aka Concordance processing and products.. | |
Study Inception | PROPOSED | This document describes all the elements that might be used to record information on the beginning phases of a research study, such as an analysis plan, sampling method, weighting strategies, funding information, and infrastructure requirements, which can be combined into a Data Management Plan. | |
Data Management Plan | PROPOSED | Data management plan; development, content, execution | |
Data Collection and Processing | PROPOSED | To describe the activities and outputs derived from the implementation of methodology. | This view describes the various activities that constitute the implementation of data collection and data processing according to the specification set out in the methodology/study design.
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Collection Management | PROPOSED | Archiving and Access Control | Description and application of access control information, and the purpose, organization, and relationships within a collection |
Ideas for future work
Title | View status | Purpose | Description of view |
---|---|---|---|
Protocol Specification | IDEA | Protocol specification assists in the representation and execution of complex surveys and longitudinal studies. | This view contains elements from the process model. Using these elements it is possible to specify the arrangement of study units in a study. |
Data Processing Pipeline | IDEA | This view is for the specification of data processing pipelines. | This view contains a subset of objects from the process model together with related objects from other packages. |
rDisco | IDEA | Disco is intended to describe microdata for discovery purposes. | In this view we propose to combine a subset of Disco with other vocabularies including parts of Dublin Core, DataCube, DCAT and PROV not already in Disco. |
Analysis and dissemination | IDEA | This view describes the activities involved in the analysis of final data products produced from data collection, and the dissemination of the findings of that analysis to the relevant user community. | This includes describes the implementation of analytical procedures applied to data files for the purposes of answering research questions or business needs specified in the study inception. The design of these procedures is specified in the project methodology.
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