openresearch — naclscrg

Open research in social sciences

Mon, 12 May 2025 15:19:54 +0000

Recently I had the chance to consider good examples of open research in social sciences. Once again, with thanks to the various open research communities I'm a part of and in the interests of my enquiry taking the form of open research, here are some relevant resources/examples. On a meta level, it was interesting what people suggested, which says something about their perspectives on the matter.

From The Turing Way

Anne reminded me the importance of recognising/avoiding what I would call the trap of “performative objectivity”, i.e.:

...traditional 'social science' (which can often fall prey to the same ideas of being 'objective' and 'removed' from the communities they are studying or working with, in their desire to be more aligned with the hard as opposed to 'soft' sciences)

This then reminded me of the excellent book Data Feminism:

https://data-feminism.mitpress.mit.edu/

This book was a great read, and contains — among other things — great examples of projects which avoid that trap, and creative ways to share and conceptualise “data”.

With that in mind, here's a good example of community-led research:

https://grassrootsjusticenetwork.org/resources/community-action-guide-on-community-led-research/

Engaged and public anthropology can be creative in its outputs (as opposed to “traditional” academic outputs), such as an open city documentary festival:

https://opencitylondon.com/about-us/

Or a set of walking tours:

https://open-city.org.uk/events

Anne also mentioned that Paz Bernaldo from Open Life Sciences and Beth Duckles from “organisational mycology” (so curious what this term means!) may have insights, too.

Beth later responded with some very useful examples, saying that:

...participant action research (PAR) and community based participatory research (CBPR) are another set of methodological approaches that seeks to reconsider subject/object of the research by including the folks “being studied” in the research leadership, essentially trying to lessen the power inequalities and make the research more community led. It comes out of a social justice lens, particularly Paolo Friere's work.

One of which is a piece of open participatory research that makes “the research process, data collection and analysis open to those who were able and interested in being a part of the process”:

https://zenodo.org/records/8015576

There are also online repositories for publishing open social science outputs, such as SOCARXIV and SOAR:

https://socopen.org/

https://www.gesis.org/ssoar

Beth also linked to a discussion about “open social science”:

https://blogs.lse.ac.uk/impactofsocialsciences/2022/01/11/eight-components-for-open-social-science-an-agenda-for-cultural-change/

And Angela Okune worked for a long time with a community in Kenya, published on the Platform for Experimental, Collaborative Ethnography (PECE: pronounced “peace”):

https://worldpece.org/

Anne also curated a list of tools for social science researchers:

https://open-source-social-science.github.io

Even though it's a list of tools, tools affect the questions we could ask and I think Anne's list can serve as an inspiration for what kinds of open research one could do!

From FORRT

Priya reminded me of the wonderful work she and others at the UK Reproducibility Network did to collate examples of open research across disciplines:

https://www.ukrn.org/disciplines/

https://doi.org/10.31219/osf.io/3r8hb

Aleksandra shared a platform her lab established to share psychological methods/tools translated into Serbian. To me, this is a great example not because it's about psychology research, but because that it's a community effort at translation, making resources accessible to a different audience:

https://www.repopsi.f.bg.ac.rs/en/

Flavio shared a great paper about “Teaching open and reproducible scholarship: a critical review of the evidence base for current pedagogical methods and their outcomes”. An important reminder that pedagogy/teaching is a key component of open research:

https://doi.org/10.1098/rsos.221255

Also, FORRT resources on adopting open research and replication:

https://forrt.org/adopting

https://forrt.org/replication-hub/

On a more meta level, Flavio noted that FORRT itself might be a good social sciences example of people coming together as a community to build something.

From NASA TOPS

Christine shared two very cool resources.

SEEKCommons, which seeks to promote “the 'commons' in science and technology with an emphasis on collaborative socio-environmental research”:

https://seekcommons.org/about.html

And the ICPSR (Inter-university Consortium for Political and Social Research), which “provides leadership and training in data access, curation, and methods of analysis for the social science research community”:

https://www.icpsr.umich.edu/web/pages/about/

Citizen science

There's also lots of work in the citizen/community science circles that may be good examples of open research in social sciences.

For example, the classic story I always tell is about Public Lab:

https://publiclab.org/

Where their famous open source balloon mapping kit — originally for mapping the spread of the 2010 Deepwater Horizon oil spill — was adapted by those in the Bourj Al Shamali refugee camp to see their urban space from above for the first time:

https://placesjournal.org/article/camp-code/

The story in this article is an inspiring example of open research. And, the article itself is open research by Claudia Martinez Mansell, sharing her work in a public way.

Other resources

A great talk about open qualitative research by Natasha Mauthner, Professor of Social Science Philosophy and Method at Newcastle University: https://oercommons.org/courseware/lesson/134043/overview

Qualitative research software

Qualcoder is an open source replacement for proprietary qualitative research software like NVivo:

https://github.com/ccbogel/QualCoder

Some Qualcoder learning resources:

And there's also Taguette which seems much more user-friendly:

https://www.taguette.org/

To complement Tageutte, I also learned of a new tool which allows you to view your codes in different ways:

https://qdb.n.gardella.cc/

Acknowledgements

In alphabetical order.

The Turing Way

Anne Lee Steele, Beth Duckles

Framework for Open and Reproducible Research Training (FORRT)

Aleksandra Lazić, Flavio Azevedo, Priya Silverstein

NASA TOPS community

Christine Kirkpatrick

#openresearch

Unless otherwise stated, all original content in this post is shared under the Creative Commons Attribution-ShareAlike 4.0 International license

Talk - Open source hardware for more equitable open science

Mon, 02 Dec 2024 16:36:30 +0000

Since 2023, I've given several variations of my talk about open source hardware as a key component of open science. Here, I will share extra notes on what didn't fit in the talk, a transcript, further reading/resources, and a recording of the talk. This note is structured as follows, please scroll down to the section you're looking for.

Recording
Transcript
Further reading/resources

Recording

I've given several variations of this talk with multiple recordings. For now, here is the recording of an early iteration I gave at the Edinburgh Open Research Conference in mid-2023 (click on the “Presentation Video” link on the page):

https://doi.org/10.2218/eor.2023.8112

I will try to put other recordings here on a best effort basis.

Transcript

I will put a transcript of the talk here as soon as I can.

A digital preservation workflow for academic research

Mon, 11 Nov 2024 15:23:54 +0000

As part of the Data Lifeboat meeting I attended in November 2024, I'm jotting down some rough, high-level thoughts on what a good digital preservation workflow might be. I am writing this as a stream of consciousness from my experience as an academic researcher. There are certainly things I missed or that I will think of later.

The workflow is organised below into three stages: Pre research; during research; and post research. Within each one I'll write down what would be good to happen at that stage.

Pre research

Start with a research “data” management plan. I'm using the term data very broadly here to mean the artefacts that result from a research projects, which could be (but not limited to) general notes, numerical data, interview transcripts, audio/video recordings, artwork, lab notebooks, etc.

When writing the plan, think about:

What artefacts do you anticipate from the research? Which will be shared and preserved? Remember things may be be produced throughout, not just at the end.
How will artefacts be shared and preserved? Any anticipated barriers? How might they be overcome? How could this be done in a way that ensures, as much as possible, that they can be human and machine readable years later?
Where will they be preserved? Make sure the appropriate digital repositories are in place.
When do you expect each output to be produced? Will the “how” be ready at those times? Closely related is for how long (what timescales) do you hope for they to be preserved? 10 years? 20 years? 100 years?!
Who will take on the responsibility of carrying out this plan?

From experience, I know that a big challenge is not just coming up with such a plan, but to budget the time, resources, and labour to implement it. In academic research, I think this is an underappreciated point. At least from my scientific background, there are many scientists who scramble to prepare and publish data (usually because an academic journal requires them to publish data) at the last minute, and end up doing a poor job at digital preservation.

During research

During the course of a research project, remember to do good documentation. In my view, it is especially important to write down things like spontaneous learnings (“what are we learning along the way?”) or to note deviations from the research plan.

Documentation could also be informal, like rehearsal notes for performing arts or daily lab notebooks for an experimental scientist. Blog posts are also good.

Regularly check in with the original data management plan to see if it is being followed or if changes are needed.

Post research

In my view, a post-mortem is a critical exercise in any research project. This is true, too, for reflecting on how well a project's digital preservation plan/data management plan worked. Some questions to ask:

Did we produce the digital artefacts we anticipated at the beginning?
What was the experience of sharing and preserving those artefacts? Any points of friction?
What would we do differently next time?
How will we preserve and shared what we learned from this post-mortem to inform future efforts?

Another meta issue I see in academic research is the lack of appreciation, and highlighting of, the reuse of digitally preserved material. At least from what I've seen, there's lots of talk in #openresearch circles about sharing and how to do it well, but far less on using what others have shared!

I think if we do a good job of telling stories about the use of shared stuff, then we can more effectively make a case for digitally preserving said stuff and reducing #intellectualpoverty.