Now that you've gained an understanding of some of the considerations around data and ethics, let's think a bit further about how you may apply some of what we have discussed in your work. Below you will find some additional readings that dives deeper into some of the topics that were covered in our lessons. If you would like, you can also consider exploring the "Projects or Challenges to Try" to see how you might apply what you've learnt.
- Marieke Guy's data management presentation discusses some ideas around planning for data management before, during, and after a project.
- Queensland University of Technology's Management of Research Data provides some ideas around ownership, roles and responsibilities of data-driven projects. While this is specific to Queensland University of Technology, it is useful for understanding some of the different roles in a research project.
- The Graduate Center, CUNY's Data Management research guide provides resources and specific steps for CUNY faculty, staff, and students.
- The Council for Big Data, Ethics, and Society's Perspectives on Big Data, Ethics, and Society is a white paper that consolidates the council's discussions on big data, ethics, and society.
- Catherine D'Ignazio & Lauren F. Klein's Data Feminism (scroll down the page to access the book chapters for free). It looks at "big" data from a feminist perspective, and discuss the importance of understanding long histories and socio-political contexts in research, as well as providing an overview of the field.
- Feminist Data's Manifest-No discusses the realities of "big" data and the fallacies of unequal harm and risk distribution, particularly towards marginalized communities.
- Mimi Onuoha's Missing Data Sets looks at "blank spots that exist in spaces that are otherwise data-saturated," that usually affect those who are the most vulnerable.
- Computational social science with R is a 2-week summer institute program that follows the Bit By Bit: Social Research in Digital Age format. The current repository (updated: Jul, 2020) contains the institute's workshops and materials.
- The European Data Portal's tutorial on Open Data offers a guided insight to the importance of choosing the right format for open datasets.
- The Data Visualisation Catalogue by Severino Ribecca provides a guide to data visualizations for different types of data and narratives.
- From Data to Viz by From Data to Viz also provides a guide to data visualization for different types of data and narratives.
- Consider a project where you are interested in the trend of Euro-American political views. You've decided to look at the 2018 European Social Survey and the U.S.-based 2018 General Social Survey. How would you approach the data? If you're interested in reporting on the trend of global political views, what do you have to consider when you join these data sets? What assumptions do you have to make? How would you collapse responses?
- How does increased data literacy add to your project planning?
- How do you address your use of data and your ethics? For example,how might ethics play a part in the way you think about (a) data collection? (b) anonymity and confidentiality? (c) data and its relation to the communities it emerges from?
- Consider your next project, what are some considerations from this workshop that you might bring into your project?