The SSH Training Discovery Toolkit provides an inventory of training materials relevant for the Social Sciences and Humanities.

Use the search bar to discover materials or browse through the collections. The filters will help you identify your area of interest.


Quantitative analysis

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easySHARE is a simplified HRS-adapted dataset for student training, and for researchers who have little experience in quantitative analyses of complex survey data. While the main release of SHARE is stored in more than 100 single data files, easySHARE stores information on all respondents and of all currently released data collection waves in one single dataset. Moreover, for the subset of variables covered in easySHARE, the complexity was considerably reduced. For example the information collected only from one person of a couple or in a household was transferred to all respective respondents; time constant information collected only in the first interview was transferred to all later interviews; the coding of missing values was enriched to provide an easier understanding of the routing and filtering of the interviews; etc. In addition, several ready to analyse variables have been added, such as health indexes, demographic information, or economic measures. When possible measures have been selected or recoded to facilitate comparative analyses with the US Health and Retirement Study (HRS).

Managing Evidence: A CAEL Module

In this era of evidence-driven reform, school leaders must learn to harness an array of data to drive improvement. In this module, you will explore key concepts in performance measurement, research design, and data analysis (qualitative and quantitative) to understand what can be gleaned from different sources. With your cohort, you will discuss the data you have available and learn how to draw on multiple forms of evidence to make more informed policy and programmatic decisions.

Webinar recordings

Recordings of past webinars organised by the UK Data Service.

Analytical Information Systems

Learn about the use of programming for data analysis, data management, and statistical analysis techniques.

Literary corpora

This is a list of literary corpora that are available as part of the CLARIN Resource Families initiative.

Literary corpora comprise poetry and fictional prose texts, such as novels, short stories and plays. They bring together the collected works of a single author or representative from a specific literary period. Since the literary corpora are often available through powerful concordancers, they are especially well suited for a quantitative and qualitative approach to comparative literary analysis, within or across different genres and historical periods.

Data handling tutorials

Practical tutorials to manage and handle research data for particular software packages: SPSS, R, ArcGIS and N-Vivo. Tutorials contain many practical exercises.

Foucault's Toolbox Master Spreadsheet 2019 - 4

This is the master spreadsheet that contains various categories of data regarding the 1,062 journal articles that formed the journal literature sample for "Foucault’s Toolbox: Use of Michel Foucault’s Writings in LIS Journal Literature, 1990-2016."


Video presentations on CLARIN topics given in various contexts, such as the CLARIN Annual Conference, CLARIN workshops, research institutions and universities.

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GESIS Training

At GESIS we offer a wide range of events, especially training courses on empirical social research methods. Our theory founded and hands-on courses develop participants’ methods skills and are aimed at both early career and senior researchers from Germany, Europe, and the whole world.

OpenScience MOOC

Research is getting a global makeover, in part thanks to the power of the internet and the tools it provides for us, and in part due to a growing call for accountability (e.g., reproducibility and data provenance) in research. Global policies are emerging at different levels that include some aspect of Open Research, Open Scholarship, or Open Science, and inclusive of all research disciplines. But our universities are often letting us down, and they are not teaching us the knowledge, tools and skills we need to do research effectively in the 21st century.

“Open Science” has many interpretations, but at its core it is about increased rigour, accountability, and reproducibility for research. For us, it is based on the principles of inclusion, fairness, equity, and sharing. Open Science can be viewed as research simply done properly, and it extends across the Life and Physical Sciences, Engineering, and Mathematics, to Social Science and Humanities.

This MOOC is designed to help equip students and researchers with the skills they need to excel in a modern research environment. It brings together the efforts and resources of hundreds of researchers and practitioners who have all dedicated their time and experience to create a community to help propel research forward.