What's New

Recording of the Webinar to Explain DDI Scientific Board Restructuring

Ingo Barkow, Jared Lyle, and Joachim Wackerow presented a Webinar on 24 November 2020 to discuss the upcoming changes to the DDI Scientific Board and answer questions.  A recording of the Webinar is now available on the DDI Alliance YouTube channel: https://youtu.be/RB3ANFvcnwc

The DDI Scientific Board proposes the scientific work plan to the membership for approval and facilitates the scientific and technical work activities of the DDI Alliance. As announced with the recent DDI Bylaws changes, the new Scientific Board will be composed of seven voting members elected by the Members of the Alliance. Representatives from Members and Associate Members of the Alliance are eligible to serve as elected members of the Scientific Board. A majority (4 out of 7) of the elected members of the Scientific Board must be from Member Organizations. No Member or Associate Member shall have more than one representative serving on the Scientific Board at the same time. For the initial election, three members will be elected for two-year terms and four for four-year terms. Terms will start on 1 January 2021 and run through June 2023 and June 2025, respectively.

References:

Structured Data Transformation Language (SDTL) approved

Earlier this month, DDI members voted on the Structured Data Transformation Language (SDTL).  Nineteen of the 28 eligible voting designated member representatives voted, with all responding “YES, the validity and usefulness of Version 1.0 of SDTL has been demonstrated and it should now be accepted as a part of the DDI standard.”  The vote passed with a two-thirds majority. 
 
SDTL is an independent language for representing data transformation commands in statistical analysis packages, such as SPSS, Stata, SAS, R, and Python.  Commands like RECODE, MERGE FILES, and VARIABLE LABELS are rendered in a structured format (JSON, XML, RDF) that is easy for machines to read and process.  Command scripts translated into SDTL produce variable-level data transformation histories, which can be translated into natural language.  SDTL can be added to Data Documentation Initiative (DDI) and other metadata standards for use in data catalogs, codebooks, and other documentation.  SDTL was developed by the Continuous Capture of Metadata for Statistical Data (C2Metadata) Project, which was funded by National Science Foundation grant ACI-1640575.
 
As a next step, the DDI Technical Committee will incorporate corrections noted in the Public Review and prepare the specification for publication.  
 
Thanks to everyone who contributed to the development of SDTL, especially George Alter (Principal Investigator of the C2Metadata Project), the C2Metadata Project members, the DDI SDTL working group, and the DDI Technical Committee.
 
 
More details about SDTL:

Webinar to Explain DDI Scientific Board Restructuring: 24 November

The DDI Alliance is hosting a Webinar on 24 November 2020 9am Eastern Time (US and Canada) to discuss the upcoming changes to the DDI Scientific Board and answer questions.  Ingo Barkow and Joachim Wackerow will present.
 
As announced with the recent Bylaws changes, the new Scientific Board will be composed of seven voting members elected by the Members of the Alliance.  The Scientific Board may appoint up to two external Advisory Members, without internal vote.   Representatives from Members and Associate Members of the Alliance are eligible to serve as elected members of the Scientific Board.

To join the Webinar: 

https://us02web.zoom.us/j/83784781681

Meeting ID: 837 8478 1681
Find your local number: https://us02web.zoom.us/u/kcgeybKON

Structured Data Transformation Language (SDTL) Webinar: Recording and Slides

George Alter, Chair of the Structured Data Transformation Language (SDTL) Working Group of the DDI Alliance, explained during a 2 November 2020 Webinar the value of SDTL to the DDI community. SDTL is a new tool for creating machine actionable data provenance.

SDTL is an independent language for representing data transformation commands in statistical analysis packages, such as SPSS, Stata, SAS, R, and Python. Commands like RECODE, MERGE FILES, and VARIABLE LABELS are rendered in a structured format (JSON, XML, RDF) that is easy for machines to read and process. Command scripts translated into SDTL produce variable-level data transformation histories, which can be translated into natural language. SDTL can be added to Data Documentation Initiative (DDI) and other metadata standards for use in data catalogs, codebooks, and other documentation.

A recording of the "Introduction to Structured Data Transformation Language (SDTL)" Webinar is now available on the DDI Alliance YouTube channel: https://youtu.be/62dLnRkwQUg. Presentation slides are also available: http://hdl.handle.net/2027.42/163363.

References:

Seeking DDI Scientific Board nominations

The DDI Alliance is soliciting nominations for members of the recently restructured DDI Scientific Board.  Nominations may be sent directly to Jared Lyle, Executive Director, DDI Alliance (lyle@umich.edu).  Please submit your nominations by 7 December 2020.  In early December, the Alliance membership will elect the members of the Scientific Board.
 
The purposes of the Scientific Board are to:
  • Provide direction and coordination in the development of the substantive content of the DDI standards and other work products of the Alliance by its sub-committees and working groups within the context of the Alliance Strategic Plan.
  • Implement the scientific work plan agreed at the Annual Meeting of the Scientific Community.
  • Oversee the substantive content of DDI standards and other work products.
  • Undertake research and testing concerning proposals for DDI standards and other work products.
  • Develop and promulgate best practices for use of DDI standards and work products.
  • Assess progress and barriers to progress.
  • Provide a report on progress of the scientific work plan over the previous year, and proposals for the future scientific direction and related activities to the Annual Meeting of the Scientific Community.
 
The restructured Scientific Board will be composed of seven voting members elected by the Members of the Alliance.  For the initial election, three will be elected for two-year terms and four for four-year terms; all terms will start 1 January 2021 and run through 30 June of their respective term periods.  The Executive Director and Chair of the Technical Committee shall serve as ex‐officio members, without internal vote, of the Scientific Board. Representatives from Members and Associate Members of the Alliance are eligible to serve as elected members of the Scientific Board.  A majority of the elected members of the Scientific Board must be from Member Organizations.  

DDI Bylaws amendments approved

In September and October, DDI members voted on proposed amendments to the DDI Bylaws about a restructuring of the DDI Scientific Board, which is the scientific and technical body of the Alliance.  Twenty-one of the 28 eligible voting designated member representatives voted "Yes", one voted "I formally decline to vote", and six did not respond.  The vote passed with a two-thirds majority, which means the Bylaws amendments are adopted.  
 
These changes were proposed by a temporary working group composed of DDI member representatives, discussed at the 2020 annual Meeting of Members, and subsequently distributed to the entire membership for comments and further edits.  We especially thank the temporary working group, chaired by Ingo Barkow, that drafted and proposed the Bylaws amendments. 
 
To view the updated Bylaws, please visit: https://ddialliance.org/alliance/bylaws

Registration for EDDI 2020 is now open

Registration for the Virtual European DDI Conference EDDI 2020 is now open, at http://eddi20.sciencesconf.org
Registration is open until Wednesday 25th 2020 23:59. 

The conference will take place on 1/2 December 2020, and workshops and tutorials will also be held on 30 November 2020.
The full program is available at: https://eddi20.sciencesconf.org/program. All times are CET.

Links to participate in the virtual Conference will be sent to participants on Thursday November 26th 2020.

Mari Kleemola & Jon Johnson 
EDDI 2020 Co-Chairs

Structured Data Transformation Language (SDTL) Vote

Dear DDI Alliance community,

We are ready to vote on Version 1.0 of SDTL (Structured Data Transformation Language) for publication. Next week, Designated Member Representatives will receive a link to cast their votes. It is important to vote; a two-thirds majority is required for approval. 

SDTL is a new product for DDI and we are asking you to approve its inclusion in the product line of the DDI Alliance. Over the past year this product has provided the Technical Committee with:

  • Statement of content and functionality
  • Information on the business case for the product
  • Objectives for the product
  • Position within the suite of products supported by the DDI Alliance
  • A maintenance plan for the product

The public review was completed between July 1 through August 31, 2020. All issues have been addressed and the product prepared for the final vote on publication.

To assist you in evaluating this product for inclusion in the suite of DDI products a webinar will be presented on

Monday, November 2, 2020 at 10:00 Eastern Time (16:00 European Time)
To join the Webinar:
https://us02web.zoom.us/j/82041378650

Meeting ID: 820 4137 8650
Find your local number: https://us02web.zoom.us/u/kEZvDttN

The following content should also be informative:

SDTL is an independent language for representing data transformation commands in statistical analysis packages, such as SPSS, Stata, SAS, R, and Python.  Commands like RECODE, MERGE FILES, and VARIABLE LABELS are rendered in a structured format (JSON, XML, RDF) that is easy for machines to read and process.  Command scripts translated into SDTL produce variable-level data transformation histories, which can be translated into natural language.  SDTL can be added to Data Documentation Initiative (DDI) and other metadata standards for use in data catalogs, codebooks, and other documentation.  

We wish to thank George Alter and the SDTL Working Group, as well as the Technical Committee, for the preparation of the SDTL product for publication.

Structured Data Transformation Language (SDTL) Webinar: 2 November

The Structured Data Transformation Language (SDTL) Working Group of the DDI Alliance will host a Webinar on 2 November at 10am Eastern Time to explain the value of SDTL to the DDI community.  SDTL is a new tool for creating machine actionable data provenance.  The webinar will describe SDTL and explain how it works with DDI.

SDTL is an independent language for representing data transformation commands in statistical analysis packages, such as SPSS, Stata, SAS, R, and Python.  Commands like RECODE, MERGE FILES, and VARIABLE LABELS are rendered in a structured format (JSON, XML, RDF) that is easy for machines to read and process.  Command scripts translated into SDTL produce variable-level data transformation histories, which can be translated into natural language.  SDTL can be added to Data Documentation Initiative (DDI) and other metadata standards for use in data catalogs, codebooks, and other documentation.  

To join the Webinar:
https://us02web.zoom.us/j/82041378650

Meeting ID: 820 4137 8650
Find your local number: https://us02web.zoom.us/u/kEZvDttN

New Paper: DDI-Lifecycle Facilitates Cross-Study Linking of Cognitive Data

The National Archive of Computerized Data on Aging (NACDA), located within ICPSR, has published a working paper that describes a methodology that used DDI Lifecycle tools to identify and organize health questions and measures related to Alzheimer’s and other cognitive impairments using data maintained or supported by NACDA. This project specifically used the National Social Life, Health and Aging Project (NSHAP) and the National Health and Aging Trends Study (NHATS) as the comparison proof of concept.

The methodology used in this process identifies variables that measure Alzheimer’s disease (A.D.) and other cognitive impairments within NSHAP and NHATS, as well as sociodemographic and comorbidity data commonly associated with increased risk of A.D. and other cognitive impairments. The project generated enhanced metadata using DDI Lifecycle software to make the discovery of A.D. and other cognitive impairments variables more straightforward and increase the user-friendly elements of these studies. Finally, the proposed supplement included the creation of a customized bibliography of the use of NSHAP and NHATS data in the analysis of A.D. and other cognitive impairments research, allowing researchers to more easily review the existing body of literature using these data resources.