The combination of digitised and born-digital data transactions and interactions create new forms of ‘big data’ we can study, from digitised newspapers to social media. This is generating new methodologies for study and innovation, such as citizen science, collaborative design and social editing As you move into a world with growing reliance on automated methods which augment or replace human activities, you should reflect critically on these processes.
In 2008, Chris Anderson provocatively claimed (‘The End of Theory’, Wired, 2008), that the availability of ‘big data’ removed the need to develop theories and methods for research: ‘With enough data, the numbers speak for themselves’. As you have seen throughout this course, this is problematic. In Week 1, Session 3 you saw that ‘data’ should always be conceived as ‘capta’, something that is constructed. In their Data Feminism, Catherine D’Ignazio and Lauren Klein observed that:
all knowledge is situated. … When approaching any new source of knowledge … it’s essential to ask questions about the social, cultural, historical, institutional, and material conditions under which that knowledge was produced, as well as about the identities of the people who created it.
It’s not just data: software and computer processes, such as search engines and algorithms need context. For example, Safiya Umoja Noble (2018) argues that automated decision-making systems such as search engines exacerbate racial inequality. She asks social scientists and digital humanities scholars to engage in a dialogue with developers and policymakers to reflect upon the impact of algorithms on societies and communities.
You should ask the accessus questions whenever you read an article or use a dataset or tool to reconnect it with those who produced it, enabling you to understand its potential limitations or biases. The best way to learn more about digital research in the Humanities is to experiment and do it. Asking questions of your data, tools and methods will enable you to do so in a more critical and ethical way.
Activity 5 Reflecting on your learning journey
Look back on the whole of the course and write down:
- one concept or method you have learned that you did not know before and in what session(s) you encountered it
- one method/tool that you are going to use in the future and why
- the most important thing you’ve learned and how you think it will influence your future research
- You answer will depend on your circumstances and prior expertise. For example, you may have learned about ‘data wrangling’ for the first time in Week 2, Session 3, or about knowledge infrastructures in Week 3, Session 1.
- For example, you may have decided to use Creative Commons licences when you publish your work, allowing other to reuse, test and build upon your research results.
- For example, you may realise that you need to question and evaluate the datasets and tools you employ, using the accessus questions and continuing with intellectual property, the ethics of data collection and use and the FAIR principles.