Workshops

N.B. The workshops are for the participants attending the conference in person and will not be broadcast digitally.

All workshops will be held at the Faculty of Humanities, Renströmsgatan 6

Directions to Workshop venue - Humanisten Gothenburg University from the Swedish Exhibition Center

Workshops Tuesday 7 June 10-12

How to set up and configure a Dataverse repository that suits your needs

Room J336
Maximum amount of participants 30

Tuesday 7 June 10-12
Topics: Data management and archiving
Organisers: Alina Danciu, Geneviève Michaud & Baptiste Rouxel, CDSP

Since its creation, the Center of Socio Political Data of Sciences Po has been committed to design and develop services to support research data lifecycle. Pursuing its mission for data preservation and dissemination over the years, it has also been engaged in creating innovative information systems and tools for data collection.

In 2016, the CDSP launched the first Dataverse repository in France, and has built a strong experience with Harvard IQSS’ Dataverse open source solution.

During this workshop, we will guide you through the complete process of launching a test Dataverse repository instance and performing some useful adjustments and customisations that suit your project and environment, beginning with an introduction to the Data Documentation Initiative (DDI).

Learning objectives:
Provide participants with a general understanding of the skills needed to setup a Dataverse instance. Present several choices that will have to be made to configure a Dataverse instance fitted to several use cases.

Prerequisites:
Understand the basics of Research data management. Experience as a curator of research data.

Teaching data visualization: Adapting the Visualizing the Future data visualization modules for your institutional context

Room J412
Maximum amount of participants 50

Tuesday 7 June 10-12
Topics: Data literacy
Organisers: Alisa B. Rod, McGill University, Tess Grynoch, University of Massachusetts Chan Medical School, Negeen Aghassibake, University of Washington Libraries, David Christensen, The Seattle Public Library & Angela Zoss, Duke University Libraries

Foundational concepts in visualization and design are critical to creating and reading data visualizations but are often not included in traditional library data services instruction. This 2-hour hands-on workshop would provide attendees with the pedagogical tools and content to teach data visualization for a variety of audiences and skill levels.

We plan to follow a “train the trainer” model to empower attendees to develop context-specific versions of the materials and implement them at their own institutions.

The first hour of the workshop would provide attendees with a quick overview of the content of two open access data visualization instruction modules and will focus on highlighting specific topics and areas where the materials can be customized. The two instruction modules are “Data Visualization 101” and “Ethics in Data Visualization” and they cover topics such as key parts of a data visualization, accessibility, ethics-centered design, and identifying bias in the data and visualization creation process.

In the second hour, attendees would have the opportunity to repurpose the materials to fit their institutional audience and needs. This would consist of creating a sketch of a lesson plan and breaking up into smaller groups to workshop their tailored plans with other attendees.

We plan to conclude the training session by providing information about how to share ideas and adapted materials using the dedicated GitHub site for these two instruction modules.

Learning objectives:

Following the completion of this workshop session, attendees will be able to:

Locate data visualization instruction modules and resources.
Create tailored lesson material based on the two data visualization modules to fit institutional contexts.
Incorporate active learning activities into data visualization instruction.
Describe how to incorporate tailored or new content into the original module Github site.

The CESSDA Data Archiving Guide: A resource for people who love data

Room J310
Maximum amount of participants 30

Tuesday 7 June 10-12
Topics: Data management and archiving
Organisers: Libby Bishop & Yevhen Voronin, GESIS, Ilze Lace, SND & Dimitra Kondyli, EKKE

The CESSDA Data Archiving Guide (https://dag.cessda.eu/) is a new resource developed by CESSDA and is designed to provide employees at data archives and repositories with an understanding of the work a data archive performs.

The information in the DAG was collected by experts from CESSDA social science data archives reflecting the procedures and policies at their local archives. While the context of these archives varies — in size, the underlying technical architecture or in the specific services provided to researchers — the DAG focuses on common ground and is a useful tool for professionals new to data archiving or those who are knowledgeable in one domain and now seek to broaden their expertise.

The workshop is made up of representatives from three of the data archives who have built DAG and will follow the structure below:

Introduction to DAG (15 mins)
Present the content of three sections: FAQs, Policies, and Pre-ingest.
Interactive sessions with participants, as full group or in breakout groups, depending on numbers. (30 mins for each chapter, 15 presentation and 15 for discussion)
Next steps – Focused discussion with participants on several topics (15 mins)

Comments on current content
Suggestions for topics future sections
Discussion of how DAG might be distinctive as a resource for data professionals because it provides a sustainable infrastructure supported by CESSDA.

Based on participant feedback from the soft launch of this website, the link will be made available to participants in advance, and questions to solicit feedback will also be provided. Reviewing the website content and feedback questions before the event is recommended, but not required, for participation.

Sustainable Survey Question Banks and Data Catalogs using DDI and Colectica

Room J415

Tuesday 7 June 10-12
Topics: Data management and archiving
Organisers: Jeremy Iversen & Dan Smith, Colectica

DDI Lifecycle is an open standard used by data archives to document survey questions and resulting datasets. Colectica is a fully supported, off-the-shelf software tool that can create and publish DDI content, including survey question banks and data catalogs.

Using open standards and existing software allows organizations to focus on publishing their content instead of developing information formats and performing software maintenance.

This workshop covers the following topics:

Introduction to DDI Lifecycle
Introduction to Colectica
Create DDI-backed question banks
Use questions from a question bank to build a survey
Document datasets using DDI and Colectica
Publish question banks and data catalogs on the Web
Harvest questions and data documentation using OAI-PMH harvesting protocol

Learning objectives:

Learn why DDI Lifecycle is used by data archives for documenting survey questions and survey data
Learn how DDI based question banks can be used for question discovery, re-use, and harmonization
Learn how Colectica tools can help manage DDI metadata and DDI infrastructure

Workshops Tuesday 7 June 13-16

Research Code Management

Room J336
Maximum amount of participants 20

Tuesday 7 June 13-16
Topics: Data documentation and reproducibility
Organisers: Florio Arguillas, Cornell Center for Social Sciences, Limor Peer, Yale Institution for Social and Policy Studies & Thu-Mai Lewis Christian, Odum Institute, University of North Carolina

Lessons and workshops on Research Data Management are becoming a standard offering at many institutions. Research Code Management (RCM), a very important component of a reproducibility package, however, is not often given the equal importance that it deserves.

Code shows the finer details and implementation of the research methodology and is essential for a complete and transparent scholarly record. Research Code Management acknowledges that code is a research object and aims to prepare it for archival and preservation. In this workshop, we will introduce participants to proper management of code as it relates to the whole research compendium and discuss potential pitfalls to watch out for. There will be examples and exercises to elucidate the various components of research code management.

Learning objectives:

Learn how to manage code as it relates to the whole research compendium (reproducibility package)
Learn the various components of code and their importance
Learn how to prepare/update code for independent understandability

Prerequisites:
Participants need to have some familiarity with statistical software or statistical analysis

Analyzing Survey Data with Tableau

Room J412
Maximum amount of participants 35

Tuesday 7 June 13-16
Topics: Data literacy
Organiser: Harrison Dekker, University of Rhode Island
*Attendees will not need to install any software in order to participate.

Tableau data visualization software is primarily thought of as a tool for business analytics. While there are compelling reasons why it may not be an appropriate tool for academic research,

the software does offer a variety of features that make it an ideal tool for teaching data literacy as well for a variety of analytical tasks that many data professionals routinely engage in, such as creating presentations, data dashboards, etc.

Tableau has made significant enhancements to its data “wrangling” and management capabilities, to the extent that for many use cases an entire processing pipeline can be built within the environment without having to write any code. These features in combination with Tableau’s powerful visualization tools are ideally suited for exploratory analysis and presentation of survey data.

The workshop is intended for an audience with no prior Table au experience but who are familiar with survey data. In addition to exploratory data analysis, particular attention will be given to Tableau’s survey data wrangling capabilities, e.g. variable creation, recoding, application of statistical weights, and pivoting. Emphasis will also be placed on how Tableau can be used in data literacy training.

Learning objectives:

Data visualization using Tableau
Preparing survey data for analysis with Tableau

Strengthening Managerial Capacities in Data Policy Management and Team Building

Room J310
Maximum amount of participants 25

Tuesday 7 June 13-16
Topics: Data management and archiving
Organisers: Irena Vipavc Brvar, ADP, Brian Kleiner, Swiss Centre of Expertise in the Social Sciences, FORS & Francesco Giovanni Paoletti, University of Milano-Bicocca, Italy

Learning from experienced colleagues is a valued and sought-after resource for management training in research infrastructures (RIs) and core facilities (CF). RIs and CFs that are still in the developmental stage,

may be lacking management and leadership expertise appropriate for the operation of services provided or acquired in an incomplete and unstructured manner. The overall objective of the RItrainPlus project is to develop and deliver a training program to fulfil the competency requirements for the current and future managers of European RI and CF. The proposed workshop aims to tackle two important issues of leadership in RIs and CFs, namely data policy and management and team building.

The Data policy and data management section aims to make participants aware of the skills required by infrastructure managers to define data management policies and lead their teams to effective execution. It will cover the requirements for developing and implementing meaningful data-related policies across the research lifecycle. Topics include long-term preservation, data security and staff access requirements, data storage and backup, personal data handling, and documentation. Participants will learn what is required to define appropriate workflows, roles, and responsibilities among RI staff.

The RI and CF management team culture section will address the issue of building a stronger team. Our workplace culture is created based on a set of values, beliefs, and behaviors. The teams are constantly under tremendous constraints and pressures, which makes building the right team culture laborious. It is very easy to rely on old habits and take the easier route if that means completing a task and moving on. In this section, we will use examples and active discussion to address some of the challenges of team building: intercultural teams, getting to know our team, consensus building, diversity promotion.
The workshop will include content and practical part.

Learning objectives:

Obtaining skills required by infrastructure managers to define data management policies and lead their teams to effective execution
Learning about how to build a stronger team to improve (internal) workplace culture.

What can DDI do for you? An introduction to the DDI

Room J415
Maximum amount of participants 30

Tuesday 7 June 13-15
Topics: Data documentation and reproducibility
Organisers: Benjamin Beuster & Hilde Orten, Sikt – Norwegian Agency for Shared Services in Education and Research

Are you interested to learn about what DDI can do for your organization or institution? DDI is an international product suit of standard for describing data from the social, economic and behavioral sciences, currently cross-domain.

This tutorial provides an overview of the work products of the DDI Alliance. The conceptual basis of DDI will be described, introducing the participants to the main building blocks and items of the main standard products. Practical examples on how DDI can be used beneficially in the business processes of organizations and institutions that manage research data will also be shown.

The overall approach of the tutorial is DDI-version agnostic. The examples shown will however be based on specific DDI versions (DDI-Codebook, DDI-Lifecycle and the forthcoming DDI-CDI).

Main focus will be put on the following areas:

Data description and variable management
Questionnaire design and implementation
Question and variable banking
Cross-domain data integration
Making your data and metadata FAIR (Findable, Accessible, Interoperable and Reusable) using DDI

Learning objectives: Learn about DDI main products

DDI-Codebook
DDI-Lifecycle
DDI-CDI

Workshops

Workshops Tuesday 7 June 10-12

How to set up and configure a Dataverse repository that suits your needs

Teaching data visualization: Adapting the Visualizing the Future data visualization modules for your institutional context

The CESSDA Data Archiving Guide: A resource for people who love data

Sustainable Survey Question Banks and Data Catalogs using DDI and Colectica

Workshops Tuesday 7 June 13-16

Research Code Management

Analyzing Survey Data with Tableau

Strengthening Managerial Capacities in Data Policy Management and Team Building

What can DDI do for you? An introduction to the DDI

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