Customer success story with Andrea Gasparini

How did you find out about the Researcher Workspace?

I heard about the Researcher Workspace from Anita during her presentation at the VIRAK Conference in Trondheim, Norway last June. It sounded like a game changer for research. I especially liked the idea that you can work with a big chunk of articles and apply the tools in a flexible manner. Anita also mentioned the recent paper published on “ Searching for Carriers of the Diffuse Interstellar Bands Across Disciplines, using Natural Language Processing”, where Iris.ai engine was used to conduct an interdisciplinary search for compounds that could be carriers for Diffuse Interstellar Bands (DIBs), a long-standing open question in astrophysics. The machine found several molecules studied primarily in biology. It sounded very interesting and relevant for me and I wanted to look into it more.

Could you tell me about a project where you used the RW?

I used the Researcher Workspace for two projects so far. The first one was about the Swedish artist – Hilma af Klint and how her work could be understood from a designer’s perspective . The second project was about the use of Artificial Intelligence in libraries since it’s something that I work with closely. I was researching how people are addressing the new field and how it changes how the libraries work.

Can you talk us through the process of how you used the tools for that project?

I used the Open Access Dataset and the Explore tool to find the relevant articles based on my own problem statement. The tool provided me with really relevant and good results. I got a great overview about the topic and highlights. The strong part of the Explore tool is that it’s interdisciplinary and presents you some topics that you may not think about but that are still relevant.

What challenges did you experience that Iris.ai helped you overcome?

Even though I am a researcher, I’m not an expert in all of the fields. The Researcher Workspace helped me uncover perspectives that I was not aware of.  There are some interesting papers on the borderline of my research field or in a completely different field that Iris.ai helped me find. I’ve tested many tools and the Researcher Workspace has an advantage of having all the necessary tools in one space. In the future I hope that the Researcher Workspace will become a go-to tool for a researcher like Excel is for an accountant. 

What would be the ideal workflow to accelerate your research use case? 

The ideal workflow is an orchestra of different tools. Firstly I search for the articles in different sources that are not available in the Researcher Workspace. Then I create the Open Access dataset in RW and use the Explore tool to find more articles. By merging these resources, I can construct a robust foundation for my literature review. When using the Explore tool, sometimes there’s a topic in the map that I didn’t expect and it gives me the inspiration to think more deeply in that perspective and discover more. In summary, I think using tools like Iris.ai can change how researchers work. 

Why did you choose to use our tools over other options?

Well, there are some key reasons. Firstly, Iris.ai is a Norwegian company, and that’s really important to me since I live in Norway myself. Another reason is a clear data privacy policy. In many other tools it’s unclear what exactly happens with your data. It’s possible that you might inadvertently share not just your ideas but even parts of your text, contributing to the training or expansion of these systems, which might occur in places like China or the United States. We lack clarity about this process.

So, transparency is important to me, and that’s why I opted for Iris.ai tools.