Workshops

Upcoming Workshops

NADDI 2016 Conference Workshops:

Documenting and Managing Your Data with Dataverse

April 6, 2016, Edmonton, Alberta, Canada

Instructor: Larry Laliberte, University of Alberta Llibraries, Digital Initiatives.

Dataverse is an open-source software platform developed at Harvard University which provides researchers with an easy way to share, cite, discover, analyze and preserve research data. Dataverse offers to researchers a number of key features including:

  • an intuitive interface into which to enter project-level metadata that can then be used repeatedly with other applications; 
  • allowing for the minting of Digital Object Identifiers (DOIs) and creation of data citations that can be used in publications;
  • a streamlined way to manage multiple versions of data files;
  • a service that helps organize data for submission for preservation processing.             

This half day workshop will expose attendees to these key features of Dataverse. Workshop participants will additionally discover how to create metadata records, upload and control levels of access to data files, and to perform variable level analysis.

Documenting Questionnaires and Datasets with DDI: A hands-on Introduction with Colectica

April 6, 2016, Edmonton, Alberta, Canada

Instructors: Dan Smith & Jeremy Iverson, Colectica

This workshop offers a hands-on, practical approach to creating and documenting both surveys and datasets with DDI and Colectica. Participants will build and field a DDI-driven survey using their own questions or samples provided in the workshop. They will then ingest, annotate, and publish DDI dataset descriptions using the collected survey data. The course will cover the following DDI content areas:

Questionnaire Design

  • Survey Instruments
  • Questions
  • Concepts and Universes
  • Question banks

Dataset Documentation

  • Datasets and dataset layouts
  • Summary Statistics
  • Code Lists and Categories
  • Data harmonization with RepresentedVariables and ConceptualVariables

Attendees may optionally bring their own Windows laptops to participate in the hands-on exercises.

Delivering Open Data and Statistics as a Service

April 6, 2016, Edmonton, Alberta, Canada

Instructors: Pascal Heus & Andre DeCarlo, Metadata Technology North America.

Publishing open data and delivering statistics as a service are fundamental objectives of statistical agencies, data archives, and research facilities. This entails bringing together data and metadata in easily accessible and usable fashion, for direct download or dynamic consumption over web services.

This workshop will introduce participants to a metadata driven statistical data management framework, outlining tools, techniques, and recommended practices necessary to achieve such vision. This includes data/metadata management, open data packaging, service oriented architecture, data warehouse/virtualization, and administration of large file repositories.  We will along the way demonstrate how this can be supported by open source technology and specialized products such as SledgeHammer (data/metadata packaging), our recently released Ari? platform (metadata management and new Rich Data Services (REST API for dynamic data/metadata access), and partners solutions such as  Denodo or iRODS. The role and importance of metadata in general, and DDI in particular, will be emphasized and illustrated throughout the presentation.

Rich Data Services, as a 'unifying' layer, will be particularly highlighted. RDS is an innovative middleware offering metadata driven data querying or tabulation services on SQL or Socrata data sources, while concurrently providing access to rich metadata alongside the data. RDS further offers powerful features to create custom open data packages for automated delivery, and facilitates incremental metadata enhancements. RDS can be used to rapidly establish data portals, dashboards/visualizations, metadata catalogs, and power web/mobile applications. RDS is  available to interested early adopters (contact us) and will be released later this year.

Documenting Open Data: Metadata for Discovery, Access and Reuse

April 6, 2016, Edmonton, Alberta, Canada

Instructors: Sharon Farnel (Metadata Coordinator, University of Alberta) and John Huck (Metadata & Cataloguing Librarian, University of Alberta)

Open Data can be defined as data that is easily discoverable, freely accessible, and meaningfully reusable without restrictions from copyright or other control mechanisms. Metadata is an integral part of open data because users rely on it to find, access, reuse and cite data that is meaningful to them. In this workshop we will introduce a simple framework to help participants understand how different kinds of metadata underpin these tasks. Through hands-on exercises and discussion, participants will use the framework to evaluate selected data repositories and metadata standards, and then practice creating metadata themselves. Attendees will gain a deeper understanding of Open Data and come away with a practical way of looking at metadata from the point of view of both data consumers and data producers.

Past Workshops

Facilitating Process and Metadata-Driven Automation in the Social, Economic, and Behavioural Sciences with the Data Documentation Initiative (DDI)

October 12-16, 2015

Schloss Dagstuhl - Leibniz Center for Informatics, Wadern, Germany

Course Instructors:

Arofan Gregory (ODaF - Open Data Foundation, Tucson, Arizona, USA)

Wendy L. Thomas (MPC - Minnesota Population Center, Minneapolis, Minnesota, USA)

Joachim Wackerow (GESIS - Leibniz Institute for the Social Sciences, Mannheim, Germany)

Description of the workshop

This training workshop will provide an introduction to using the Data Documentation Initiative (DDI) standard to enable many of the processes common to the social, behavioural, and economic sciences, from the conceptualization of surveys through data collection, processing, analysis, and dissemination. The focus of the workshop will be on the “Lifecycle” branch of DDI, version 3.2, which provides a detailed model of the metadata needed to support both human-driven and automated processing. The workshop will be organized in a task-oriented manner, with participants actively documenting real-world use cases in order to learn how best to employ the DDI model and associated technology. The use cases produced can be published as the final output of the workshop, as a resource to the broader DDI community. Participants are encouraged to bring their own organizational use cases.

The workshop is aimed at data producers, managers, and users who are not already experts in the DDI, or who wish to become more familiar with the latest version of the standard (version 3.2). There will also be information provided about DDI RDF Vocabularies and the envisioned shift in future versions of DDI Lifecycle to a model-based approach – the style of modeling and some of the standard implementation syntaxes (RDF and XML) will be covered. The workshop will include hands-on exercises and work within break-out groups on specific use cases, but will be accessible to participants with all levels of technical expertise.

Please have a look at the workshop page for further details, practical information, and registration:
http://tinyurl.com/DDI-Workshop

 

Metadata Management Using DDI and Colectica 

IASSIST Annual Conference, June 2, 2015

Time: 9:00 - 12:00

Presenters:

Jeremy Iverson, Colectica

Dan Smith, Colectica

Description:

The DDI Lifecycle metadata standard enables creating, documenting, managing, distributing, and discovering data. Colectica is a software tool that is built on open metadata standards, and helps facilitate adopting DDI into the research data management process.

This workshop starts with a high-level overview of the DDI content model, and then teaches how to create DDI XML, both manually and with Colectica. Finally, participants will learn how to publish DDI metadata.

This workshop covers the following topics:

  • Introduction to DDI 3.2
  • Introduction to Colectica
  • Documenting concepts and general study design
  • Designing and documenting data collection instruments and surveys
  • Documenting variables and creating linkages
  • Ingesting existing resources
  • Publishing resources
  • Hands-on: use Colectica and DDI to manage a sample study