Finding Funding and Collaborators: ‘EILEEN

Researcher’s Toolbox: ‘EILEEN’ Dr. Acuna Devises Easier, Faster Way to Find Competitors, Collaborators and Funding Sources

Daniel Acuna

E I L E E N: Exploratory Innovator of LitEraturE Networks W hat if there was a fast, automatic way for scientists, researchers, pre-award grant workers and others looking for research monies and funding sources to automatically discover who else is working on the same types of projects, and where the funds might exist to sponsor their research?

That would be efficient, useful and it could revolutionize the way program officers evaluate proposals and how researchers find fundable ideas, thought Assistant Professor Daniel Acuna. So, he came up with an idea for creating an online data collection tool and recommendation system he calls “EILEEN,” which stands for “Exploratory Innovator of LitEraturE Networks.”

The tool creates a unified dataset that captures diverse scientific disciplines and federal grant award types, helping researchers find similar published research on specific topics, appropriate funding opportunities and relevant grant sources much faster than they could normally. It also lets them discover who else in their field might be working on similar projects, thus be either potential project collaborators or funding competitors. The tool also allows users to look at specific project titles to assess whether similar works have been funded in the past, the kinds of organizations that have sponsored those projects, and the particular approach that attracted successful grant awards.

Dr. Acuna was awarded a National Science Foundation (NSF) grant totaling $168,712 for the project, formally titled, “Improving Scientific Innovation by Linking Funding and Scholarly Literature. The monies, an NSF EAGER (Earlyconcept Grants for Exploratory Research) grant, are to be used over three years (2016 through 2018). EAGER grants are designed specifically to fund potentially transformative or exploratory research that explores new subjects, different methods or interdisciplinary approaches. CREATING THE “BRAIN” Over the course of 2017, Acuna developed a working model of a search engine “brain,” a webbased navigational tool. It’s designed to help in the scoping and planning of funded research projects via an automated recommendation system. Using a few key words, the system looks for publications and grants across certain scholarly areas. Beyond merely a search engine, as the user saves and rejects information, the tool learns and fine-tunes both current searches and those on like areas in the future. The scope of the search is wide. Over the past year, the EILEEN team has worked on the project with datasets that include about 28 million publications and 3 million grants, Acuna says. The tool generates instantaneous reports about publications, grants, scientists and organizations related to users’ particular interests.

“It’s a system that will help both scientists and pre-award grant developers, and essentially anyone at a college or university doing any kind of active research. The tool helps them find similar publica“It’s a system that will help both scientists and pre-award grant developers, and essentially anyone at a college or university doing any kind of active research. The tool helps them find similar publications and grants to what they themselves are proposing.” — DANIEL ACUNA, ASSISTANT PROFESSOR

DRAFTER123/ i STOCKPHOTO BY GETTY IMAGES

tions and grants to what they themselves are proposing,” he explains.

Doing the same kind of search with existing systems means a much more cumbersome, threeor four-step process, he adds. “There’s no way to do it. You’d have to go to several websites, first search for sources and then search for recommendations, and then use different sources to look for grants. So it would take you three to four steps to do the same things, and with horrible systems that were probably invented 20 years ago,” he contends. EILEEN, by comparison, is simple, user-friendly and very “Google-esque,” Acuna says. “It’s faster, more accurate and it widens your reach by the numbers of sources and scientists you can find.”

ALPHA VERSION AVAILABLE Acuna has launched what he calls the alpha version, a first-run prototype where users can establish a profile, set specific preferences and create their own library of saved searches. He has invited groups of researchers to use it, test it out and offer him their feedback. He’s considering if and when to move on to a Beta version someday, and has studied the markets and the processes required for commercialization. While the market for such a product might be small and developing a business around EILEEN would take him off his teaching career track, it’s still a one-day possibility, he says.

In the meantime, he is encouraging scientists, scholars and award preparers to try the tool and see if it is useful to them, and a small number of researchers have given EILEEN a whirl. “People find it is great,” Acuna reports. “The only problem that we’d like to solve is that we don’t have the impact of the documents built in. When you search things on Google, you get a scale of relevance and see those listings that have a lot of traffic. With ours, you get the key words, but the listing won’t show the papers that are the most famous. But we’re working on that,” he adds.

The practical inspiration for this recommendation system came from Acuna working to overcome his own research challenges, he says. As a young scientist, Acuna recalls, it was cumbersome to find other scientists working in his specific interest area as well as search for appropriate potential grant sources. “I really want for junior scientists to get help. Junior scientists can feel really lonely, and it’s really hard to find appropriate grants. It’s my goal to help those people who are striving the first few months in their job, or people operating without a grant-writing or pre-award staff. I want to help those people, and if they can use this system and criticize it or offer suggestions for its use, that would be very good,” he explains.

In its next phase, Acuna has help; a doctoral student whose focus is fine-tuning the tool’s usability, reach and effectiveness and web presentation is working with him. n