We Are Talking Loudly and No One Is Listening
“Listening is not merely not talking, though even that is beyond most of our powers; it means taking a vigorous, human interest in what is being told to us” — Alice Duer Miller
A couple of months ago I wrote about how we need to be advocating for data sharing and data management with more focus on adoption and eliminate discussions about technical backends. I thought this was the key to advocating for getting researchers to change their practices and make data available as part of their normal routines. But, there’s more than just not arguing over platforms that we need to change — we need to listen.
We are talking loudly and saying nothing.
I routinely visit campuses to lead workshops on data publishing (as train the trainers style for librarians and for researchers). Regardless of the material presented, there are always two different conversations happening in the room. At each session, librarians pose technical questions about backend technologies and integrations with scholarly publishing tools (i.e. ORCiD). These are great questions for a scholarly publishing conference but confusing for researchers. This is how workshops start:
Daniella “Who knows what Open Access is?”
<50% researchers in room raised hands
Daniella “Has anyone here been asked to share their data or understand what this means?”
<20% researchers in room raised hands
Daniella “Does anyone here know what an ORCiD is or have one?”
1 person total raised their hand
We are talking too loudly and no one is listening.
We have characterized ‘Open Data’ as successful because we have incentives, and authors write data statements, but this misconception has allowed the library community to focus on scholarly communications infrastructure instead of continuing to work on the issue at hand: sharing research data is not well understood, incentivized, or accessible. We need to focus our efforts on listening to the research community about what their processes are and how data sharing could be a part of these, and then we need to take this as guidance in advocating for our library resources to be a part of lab norms.
We need to be focusing our efforts on education around HOW to organize, manage, and publish data.
Change will come when organizing data to be shared throughout the research process is a norm. Our goal should be to grow adoption of sharing and managing data and as a result see an increase in researchers knowing how to organize and publish data. Less talk about why data should be available, and more hands-on getting research data into repositories, in accessible and researcher-desirable ways.
We need to only build tools that researchers WANT.
The library community has lots of ideas about what is a priority right now in the data world such as curation, data collections, and badges, but we are getting ahead of ourselves. While these initiatives may be shinier and more exciting, it feels like we are polishing marathon trophies before runners can finish a 1 mile jog. And we’re not doing a good job understanding their perspectives on running in the first place.
Before we can convince researchers that they should care about library curation and ‘FAIR’ data, we need to get researchers to even think about managing data and data publishing as a normal activity in research activities. This begins with organization at the lab level and figuring out ways to integrate data publishing systems into lab practice without disrupting normal activity. When researchers are concerned about finishing their experiments, publishing, and their career, it is not an effective or helpful solution to just name platforms they should be using. It is effective to find ways to relieve publishing pain points, and make the process easier. Tools and services for researchers should be understood as ways to make their research and publishing processes easier.
“When you listen, it’s amazing what you can learn. When you act on what you’ve learned, it’s amazing what you can change.” — Audrey McLaughlin
Librarians: this is a space where you can make an impact. Be the translators. Listen to what the researchers want, understand the research day-to-day, and translate to the infrastructure and policy makers what would be effective tools and incentives. If we focus less time and resources on building tools, services, and guides that will never be utilized or appreciated, we can be effective in our jobs by re-focusing on the needs of the research community as requested by the research community. Let’s act like scientists and build evidence-based conclusions and tools. The first step is to engage with the research community in a way that allows us to gather the evidence. And if we do that, maybe we could start translating to an audience that wants to learn the scholarly communication tools and language and we could each achieve our goals of making research available, usable, and stable.