This summer I’m writing a series of posts about the curriculum of the research process, from the initial idea to the development of a complete draft. This week, I’m focusing on how to build and utilize a research network to support the development of your project from the initial idea to the data scaffolding of the first draft.
Why do you need a network? Why can’t you just lone wolf this research thing? For starters, going solo necessarily means you’re going to try reinventing the wheel at some point. Beyond that, your network can help you avoid common pitfalls in finding and using specific datasets, alert you to working papers in your general field, expose you to new methods that are being piloted in your discipline, and provide support when the going gets rough (it’s going to at some point). Your network also includes people who could be potential readers for your paper before you submit it to a journal and people who use their platform to boost junior scholars by inviting them to present in conference sessions, seminars, and workshops.
The first step to building your research network is to do a literature review of scholars currently working in your research area. Be sure to engage in cross-disciplinary networks related to your field. Find out who is currently active in your field and when at conferences, seminars, and workshops (in person or otherwise) be sure to introduce yourself and follow up with scholars by email no more than two days after the last day of the event. Get your name out there as someone who is working on this topic and make yourself a network asset by offering to referee papers and serve as a conference discussant.
Networks often first prove their value when you have your research idea and hit a speedbump along the way. For example, one common speedbump is when you have a good (or great!) research idea but you don’t have a good dataset. Whereas identifying your research idea is the foundation to a strong paper, finding and using data is part of the scaffolding. It’s possible the data does exist and you just don’t know about it. It’s possible the data exists in a difficult format and you need to do some web-scraping first. There is no reason to do manual data entry when you can use common web-scraping techniques to collect it, and there is no reason to reinvent the wheel on scraping data when someone in your network is probably familiar with the methods (and the code) you need for your project.
Finding the dataset you need can sometimes feel like the finding the age-old needle in a haystack. Before reaching out to your network, consider what you particularly need help withy. Have you checked this list of data options?
- Data Repositories: repositories are a good starting place for finding data, especially data which other scholars are already prepped. A few (extremely) useful repositories are linked below, but there may be some that are more relevant for your field.
- Checking the Literature: data that has already been used in published papers has the benefit of providing a citation to justify the use of the data, and published papers are a gold mine of data sources – some recognizable and publicly accessible, others which may just be a considerate email to the authors away. In my field, there are a few commonly used datasets which everyone knows (and knows the pitfalls). Save them.
- Restricted Data: the data exists but you need to complete an IRB review or secure funding in order to access it, reach out to your network for help, particularly as a junior scholar. Someone else is almost always interested in using that data for another project, and senior scholars can help you with the grant process to get project funding. Bonus: now you have at least two projects that you can work on in the same topic and a co-author to help with the work. After all, if you write one paper with a dataset, you can probably actually write at least three papers.
A final note of caution when building these networks to support your research idea: most academics like expanding their networks and working with junior scholars. If you run into someone who doesn’t, don’t be discouraged. There are more people in the former category, and it’s just a matter of keeping a stiff upper lip and trying again elsewhere. As my hero Dory from Finding Nemo said, just keep swimming, just keep swimming, just keep –
Next week, we’ll cover the oft-dreaded writing and revision process (and how to hack your productivity motivator if you struggle with that blank page and blinking cursor).
Helpful (Major) Data Repositories: