Generation and Refinement of Figures, Schematics, Concept maps
Most people are visually oriented. The human brain can capture more information visually than in written format. Therefore, well-designed visualizations are key in communicating complex principles.
SELECT PIECES OF WORK
Nowadays, (big) data is generated everywhere. Terms like 'data-driven decision making' are coined and used frequently. We have all seen graphs generated from data, that are badly done. When these graphs are used in presentations we are unable to readily understand them. People are visually oriented: we grasp visual information a lot faster than written or oral content. Hence the benefits of data visualization. It enables you to understand complex concepts and identify new patterns. Well-done data visualization generates visually appealing graphs, intuitive to understanding and with a clear message. Visualizations should be embedded in and assist your narrative.
I have specialized in the creative, visual form of data visualizations. Working with scientists, statisticians, analysts and management I assist with finding core messages and underlying concepts, designing the most appropriate and accurate graph for the narrative, and giving it a final touch by making it visually appealing.
A simple, meaningful schematic or cartoon, resulting from deep technical discussions can make sure that everybody truly understands the topic. By ensuring that a visualization has been fully thought through in detail, it can greatly facilitate external communication, as it is intuitive to read and understand.
INTUITIVE SCHEMATIC TO ALIGN WORK FROM MULTI-DISCIPINARY GROUPS
I designed this schematic to generate an overview of all the assays that were run by different teams on the same samples. The goal was an easy and intuitive schematic which also reflects the underlying statistical principle of derivation and validation of statistical models.
FROM DATA TO A CONCEPT OF BIOLOGICAL AGING
After measuring parameters in a person's blood one can determine if that person is biologically older or younger than their actual chronological age. Here you see how I derived a schematic drawing from the actual full data set (A-D). The data shown has been modified from its original version due to proprietary reasons.
THE ROLES OF DATA STEWARDS IN THE DATA STEWARDSHIP LANDSCAPE IDENTIFIED IN DENMARK AND THE NETHERLANDS
This is a figure I designed for the Dutch Techcentre for Life Sciences to demonstrate how the landscape of data stewards (professionals who handle research data) compares in the Netherlands to Denmark. This figure was included in the Strategic Research and Innovation Agenda (SRIA) of the European Open Science Cloud (EOSC). It can be found on zenodo.