Week 2.5: Summarising

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Week 2.5: Summarising#

One of the key components of research is how you present your findings to an audience. One effective way to communicate in science is to tell a concise and impactful story about your research. Often research projects generate a lot of ideas and outputs. The volume and the complexity of these outputs can get in the way of telling your story. This week will focus on how we summarize information in two different ways: the first by analysing and presenting data using visualizations; the second is by presenting a summary of your research in the form of an abstract. Both formats are powerful tools, they also have constraints. Abstracts typically have a word limit ranging between 250 to 300 words. Visualizations should be simple and clear. Therefore, you need to carefully select the information you need to communicate in your abstract and to plan and select the best type of visualizations to convey the message of your data. Some important questions to ask are what to include? What is relevant? What can help explain your ideas? And what might make them confusing or misleading.

Monday:

Wednesday:

Friday:

  • Friday Symposium

Workshop: Data Analysis and Visulization#

A core task in research projects is data collection and analysis. Effectively communicating results derived from data analysis is often as important -and requires as much planning- as the data analysis itself. During this session, we will focus on data and results communication using visualizations or, in other words, on data visualization.

During this workshop, you will familiarize yourself with the guidelines for effective data visualization in the academic setting. We will discuss important principles of academic data visualization. You will also get the opportunity to practice with visual data representation techniques, tools, and styles to best tell your story and rid your visuals of ambiguous and misleading elements.

Although teaching statistics and bioinformatics is outside the scope of this workshop and this minor, we would like you to keep an eye on the big picture: You must be able to document and motivate your data analysis choices as well as reflect on possible alternatives.

Key Concepts#

  • Write an analysis plan before you start analysing your data.

  • Think about alternate methods of analysing data

  • Cleaning data-what and when and keeping original data.

  • Guidelines for Academic Data Visualization

  • How to pick the right representation for my data to tell my story

  • How to use style and color to highlight important features in data

Relevant Learning Goals#

  • Effectively communicating data and results

  • Choosing the most effective data representation

  • Using effective style for their visualizations

  • Recognize and avoid bad or misleading practices in data visualization

Workshop: Writing an Abstract#

By now you should know what an abstract is. You have read several abstracts. And it is time to write one. In this workshop, you will be guided through abstract writing process. The abstract is an important part of a research paper for both readers and writers. Readers use abstracts to swiftly learn about the aim of a study as well as the expected findings and conclusions. This information will help a reader decide whether to continue reading your paper or not. Writers can use abstracts at an earlier stage to determine the key components of a paper and to guide the writing process. The abstract should then be iteratively improved to best reflect the content of the paper, inform the readers, and catch the attention their attention.

This workshop focuses on the key elements of abstracts and on strategies for writing them. Together, we will analyse and discuss a sample of abstracts. You will have to opportunity to, individually, write an abstract for your project. Then you will merge your team’s abstracts. Note that the abstract may still change after this workshop. Consider it a living dynamic part of the paper that is subject to change until the final version of your paper is handed in.

Key Concepts#

  • Structure and Content: Learn how to structure an abstract, including key sections such as objectives, methods, results, and conclusions.

  • Clarity and Brevity: Master the art of concise writing to capture the essence of your research while maintaining clarity.

  • Impact: Understand how an engaging abstract can draw readers into your work and enhance the visibility of your research

Relevant Learning Goals#

  • Recognize the importance of a well-crafted abstract in scientific research.

  • Structure an abstract effectively, focusing on essential components.

  • Write an engaging abstract that concisely conveys the significance and findings of your research.

Group Activity of the Week#

Continue with research. Write your data analysis methods section. Look at how they have been written in the various papers you’ve read.

Discussion Questions#

  • What are ethical considerations in data analysis?

  • How can data be misrepresented by the type of visual used?

  • Why does making an analysis plan before you start collecting data matter?

  • At this stage, to what extent can you determine key elements in your research project that should be included in an abstract?

  • As you progress in your project, do you find it’s changing?

  • How are you planning on analyzing your data? What other ways could you do it?

  • What questions do you have about the other projects?

  • Have you figured out something that might help other groups?

  • Do you have a question that other groups could help you with?

Weekly Submitted Assignments#

Group#

Write a draft of the data analysis method section of your paper.

Individual#

Submit your individual abstract from the workshop (you’ll merge your abstracts later with your group)

References#

Silyn-Roberts, H. (2013). Chapter 3: An Abstract, a Summary, an Executive Summary. In Writing for Science and Engineering. 2nd ed. Elsevier, pp. 53-61. Available here (if required, login using your TU Delft NetID).