Designed an analytical Dashboard for Researchers.
Bibliometricians working in academic institutions often face challenges when needing to conduct quick analyses due to a lack of streamlined tools. The conventional method involving APIs and backend workflows can be time-consuming and requires specific technical know-how. This project aimed to develop a dashboard for bibliometricians, which would not only save them time but also provide a platform where their analyses could be hosted, thus promoting open science.
Our research question was to identify what data and features would be more useful for the bilbiometricians.
Over the previous 18 months I collected user feedback from other DataCite services aimed to address the researchers needs using ProductBoard and Usersnap. I analysed the collected insights in terms of usability and effort for the bilbiometricians. I chose this method to identify what users were feeling and their attidute towards exisiting tooling.
To understand the needs and capabilities of our users, I conducted in-depth interviews with bibliometricians from different organizations. My questionnaire explored their technical capabilities and the data dimensions required for their work.
To capture a holistic view of the project, I also interviewed community stakeholders, funders, and the engineering team at DataCite. These interviews were pivotal in identifying the community's needs, defining the dashboard's success criteria, and understanding the feasibility in the context of DataCite's infrastructure.
The interviews lead me to create a compotetive analysis of other tools in the market. This analysis helped me to understand the current state of the art and the features that were more useful for the users.
I then analyzed the collected data using a strategic framework that categorized insights into dimensions, indicators, aggregations, computations, and filters. This methodology greatly informed my design of the visualizations.
These findings were then synthesised in two user stories:
1. As a bibliometrician, I want to be able to quickly analyze the citation patterns by subject area of my institution's researchers.
2. As a bibliometrician, I want to be able to quickly analyze the citation patterns by researchers' maturity level in my institution.
Subsequently, I co-designed a series medium-fidelity prototypes in Figma. These prototypes were then presented to the users during expert walkthroughs. This interactive approach allowed me to gain detailed insights and feedback to refine my design iteratively.
To make a Concept Testing I used the Figma protopyte to which was presented to ten experts during expert walkthroughs. This interactive approach allowed me to gain detailed insights and feedback to
refine my design iteratively.
A parallel process for enriching metadata with subject classification was necessary due to the existing infrastructure limitations.
The existing visualization tools at DataCite could address user needs, but significant backend development would be required for data processing.
The dashboard's success would be gauged based on its ability to address at least one of the user stories within the stipulated time frame.
My research and findings led me to recommend the following actions:
1. Develop a workflow to enrich metadata with subject classification using client information as a proxy.
2. Construct the dashboard using the current tech stack, but anticipate heavy backend alterations.
3. Focus initially on user story two, as the current system has ample data for useful visualizations.
Our chosen framework for data analysis proved effective for designing the visualizations. These learnings will be invaluable in our future projects and continuous improvement of the dashboard.
Organizations participated in idea validation
The feedback from users was positive and encouraging, which indicated a high level of user satisfaction.