Meet Our Team: Danica Evering, Research Data Management Specialist
We’re so pleased to welcome Danica Evering as the newest member of the SCDS team. As our second Research Data Management Specialist, Danica works alongside the Research and High-Performance Computing department and Dr. Isaac Pratt to enhance RDM activities, events, and resources on the McMaster campus. In Fall 2022, she will begin to host RDM workshops and consultations—for now, learn more about our new colleague with this quick Q&A.
SCDS: First things first, please give our readers an elevator pitch for RDM. What are the field’s main concerns and why should researchers prioritize managing their data?
Danica Evering: Research Data Management cares for data through its lifecycle and frames data itself as a valuable research output. A publication is just one researcher or research group’s interpretation of a dataset. Research is often publicly funded. If we frame research as a public good, researchers can build on existing datasets instead of creating very similar data again and again.
There are many benefits to researchers in prioritizing good RDM practices. It ensures your data is secure and protects your participants and intellectual property. It can save you time if your data is well-organized, ensuring no data is lost and needs to be re-collected. When you share your data, it can increase visibility for your project and get you citation credits—and sometimes new collaborations if someone builds on your dataset. It allows for others to verify your results.
RDM fosters a culture of high-quality, reproducible research which furthers our collective knowledge.
SCDS: Take us through a day in the life of an RDM Specialist. It’s an emerging field and many people may wonder what it looks like on the ground.
DE: Because we’re responding to researcher needs, every day in the life is very different. We do consultations with researchers and research groups. Currently, our main requests are for support with Data Management Plans (DMPs) for grants and assisting researchers with sharing their data in McMaster Dataverse.
RDM outreach and education is part of our work, we’re currently developing workshops and training modules for this fall to educate researchers on incorporating RDM, building a DMP, connecting your research through Persistent Identifiers (PIDs), understanding grant expectations, data sharing, sensitive data management and publishing, and finding and reusing datasets.
Over the next year, Isaac and I are also working with Dr. Jay Brodeur and our Institutional Strategy Working Group through the process of developing a McMaster RDM Strategy. This is an expectation of the Tri-Agencies who provide federal funding for research, but it’s also an incredible opportunity to connect with researchers across campus to revisit how we do research and what support researchers need. We’ve been developing documents this summer and will be sharing these with our broader research community in the fall. Isaac has already met with many researchers through focus groups; these conversations and town halls in the fall will hopefully ground a strong RDM culture at McMaster.
Also I just want to mention! UK and Australia have a few years on Canada in articulating research data services, and a recent book about RDM describes RDM services as consisting of: institutional policy and articulating a clear mission; support, advice, and training; infrastructure; and evaluation strategy. It was validating to find, it accurately describes our day to day.
SCDS: I’d like to discuss your work as an artist and critic. Your recent artwork engages with issues of land, displacement, and privilege; during your Master’s degree in Communication Studies, you completed a thesis on how arts organizations working towards social change negotiate their complicity in elitism and capitalism. How does your experience in these fields intersect with your work in RDM? More generally, what do you see as the role of the arts and/or critical humanistic inquiry in data-centered fields?
DE: Artists I’ve worked with and the art I’ve made is research in many ways. Although many people think of art as sculptures and paintings, art is also video games, maps, performances, community meetings, sound walks, GIFs. Artists are engaging with standpoints and local histories and resistance movements and more—all that work is research and produces research data.
At Concordia, our Communications Department was part of articulating research-creation, which brings together creative and academic research practices. However, humanities research doesn’t have the same broad systems for creating persistent identifiers and we have lower participation in things like ORCID. Many of us still aren’t aware of RDM.
When it’s generous and curious, art can hold contradictory points in the same hand which can be helpful. One of my research participants, Cristobal Martinez, talked about his work with Postcommodity as generating noise, each art project as a container for thinking critically though the mediator of complexity.
SCDS: Can you point us towards some compelling examples of research data being turned into art? Data visualization can be a powerful way of illustrating and/or commenting on prescient issues, like the ones explored in your artistic portfolio.
DE: A really great recent example of this is Plastic Heart project by Synthetic Collective which featured both scientific and artistic methodologies to look at all the angles of plastic—material, historical, ecological, cultural, chemical. This show features some amazing artists working with data collection and visualization, including Christina Battle and Skye Moret.
I also got a chance to see Kite’s video Listener as part of Soundings: An Exhibition in Five Parts (curated by Candice Hopkins and Dylan Robinson) at the KWAG. This piece is created with an electronic interface woven into the artist’s hair (an extra-sensory tool), disrupting police scanner audio with algorithmically re-arranged poetry, guided by a geometric projection of women’s quillwork shapes which acts like a compass for the artist. Kite has talked about this as a Lakota data visualization interface.
Art and data are not at all at odds—artists and humanities researchers are working with data and furthering conversations about Indigenous Protocol and Artificial Intelligence, cyberfeminism, data sovereignty and community action, and more.
SCDS: So far, McMaster Dataverse (the university’s institutional data repository) leans heavily towards quantitative data from STEM fields. Can you discuss RDM’s role for researchers working with qualitative data?
DE: We often think of data as being mainly quantitative data from STEM fields, and there’s a long history of open science which RDM is a part of. This landscape is more complicated than it might appear, though! McMaster Dataverse is part of Borealis Data, a network of repositories across the country. If you look at Borealis’ metrics, Social Sciences research is the second-highest area for this past year, just after Earth and Environmental Sciences. This is not an ideal gauge, since this is in due in part to StatsCan collections getting migrated into Dataverse, and there are thousands of repositories and science and engineering researchers may be depositing their data into discipline-specific repositories. All this to say, data sharing practices are interesting and nuanced.
However, qualitative methods have considerations that are important for data sharing. Information can be deeply contextual and developed around relationships of trust, so sharing data needs to be done very carefully. De-identifying data can be more labor-intensive if you’re working with interview transcripts and oral histories. In some cases, you may just want to share a README file and metadata, so your data is findable but you can control access better.
You may want information to be available to your community but not everyone, which I heard Dr. Sharon Webb talk about for the Queer in Brighton audio archive. At the same time, data sharing can also ease the burden on over-researched groups, which I’ve come to understand in speaking with Sherman colleague Subhanya Sivajothy, a data librarian who shared this great article on Information Maintenance as a Practice of Care.
I’m also excited to expand the types of data that are shared—not just spreadsheets and images and PDFs but also audio and video—and the variety of fields that are sharing data. I’m working on a sound walk right now for the Don Valley and the curator and I are discussing depositing field notes, audio recordings, and images from that project. What can this mean for new intra- and inter-disciplinary conversations?
SCDS: RDM is an energetic and rapidly-expanding field across Canadian universities. What is it like to work in a field at the moment that it defines itself and solidifies its core goals? If your work can inflect the future of the field, what core principles or practices are you most invested in codifying?
DE: This is an immensely exciting moment in RDM! Research Data Management has been a thing since there has been research data to manage, and all researchers perform RDM over the course of their work. However, there is an emerging need for solid researcher support due to developments in research (more data generally and it’s more complex); and growing requirements from funders, journals, etc.
Because the Tri-Agencies are prioritizing Institutional Strategies, it’s also a time of laying out a path for how and why we do what we do, as well as actionable steps to take us where we want to go.
Maybe because it’s rooted in open research and has an ethic of collaboration, there’s a very vibrant and engaged professional community of practice. It’s a growing field and there’s lots of work to be done in raising awareness and connecting with other RDM providers to ensure we’re co-developing, sharing, and implementing best practices. While we should be cautious about championing absolutes like openness (Simone Browne has written about Black surveillance), this open research goal of building each other up as we build knowledge up together, is something important to aim for.
SCDS: Just for fun, what’s a dream project you’d take on if you had endless time and resources?
DE: I got into Wikipedia editing through a Hackathon, and I think it’s a fun way to collectively learn about something and then do it together. Could we have a giant deposit-a-thon with researchers who have data from projects saved on their hard drives to get it tidied up and submitted to a repository?
SCDS: Last but not least, I’m asking everyone about their life beyond work. Tell us something interesting about yourself—the last show you binge watched, your favourite way to eat eggs, info on your pristine haircut, anything.
DE: Ok I’m going to just answer these questions one by one! I just binge watched What We Do in the Shadows at the same time as Coffin Run; my favourite way to eat eggs currently is steamed, they are custardy and soft; I buzz my own hair each week with clippers to keep it fresh.