Description

Interested in looking into characteristics of different types of data?

Data holds the answers to all manner of questions and analysis methods can extract those answers - linking the two is “data preparation”. Anyone interested in working with data will likely need to know at least some of the principles outlined.

Furthermore, cross-discipline data analysis is part of the scientific progress. This workshop offers the opportunity to look into data preparation procedures for different data types and to learn about their individual characteristics.

On 07 September, we start with a general introduction into data preparation. Afterwards, a brief overview about important aspects of image data, climate model data, clinical data, and qualitative data preparation will be presented. Such aspects will be addressed in single hands-on sessions focusing on specific data types (see below). Knowing about the contents of the single sessions, participants can register for hands-on sessions. Registration for the hands-on sessions starts on 07 September 2022.

07.09.2022 | General introduction and image data preparation (09:30-10:30)

An understanding of how to approach a new dataset and the typical steps that will be necessary in a variety of contexts. An insight into the preparation of image data and practical experience performing such tasks using Python.

07.09.2022 | Climate model data (10:30-11:00)

This topic will be useful for students that plan to work with models of Earth System components as their primary research tool. It also will be useful for researchers that require information about past or future state of the Earth System as additional parameter in their research (e.g. weather conditions when interview was taken, or clinical study was performed).

07.09.2022 | Clinical data (11:00-11:30)

Clinical data is either collected during the course of ongoing patient care or as part of a formal clinical trial program. To analyse clinical data a sophisticated data management concept including data preparation procedures is needed to comply with data protection regulations.

07.09.2022 | Qualitative data (11:30-12:00)

The term “qualitative data” is used to describe a broad variety of heterogeneous data, including various types of text (e.g. transcripts of interviews or observations), audio, video, picture or material artefacts. From the perspective of “quantitative” research – i.e., the application of statistical methods to standardized numerical data –, qualitative materials just seem to be data that need more structure. But qualitative material is a specific type of data that is usually richer, more context-dependent and more sensitive than quantitative data. On the other hand, qualitative data can be fruitfully analyzed with common tools of quantitative inquiry (e.g. text mining). Thus, this workshop addresses both quantitative and qualitative researchers and aims to introduce them to the particular ethical, legal and practical challenges of qualitative materials – e.g. in terms of data protection, informed consent, anonymization, documentation and data sharing – to outline good practices as well as examples of fruitful research data management.

Prior knowledge

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Technical requirements

• Own PC, laptop
• Internet, web browser (up-to-date)
• For online format a second screen might be beneficial

Program/Schedule