Open Journal Systems (OJS) is a journal management and publishing system that was developed by the Public Knowledge Project to expand and improve access to research.
PROBLEM
Users of the OJS go through a long and complicated process to submit papers, review submissions and edit the journal. The Editor's of OJS had a hard time in following up with author submissions, assigning manuscripts to assistant editors and tracking down the reviewers in the system to finally publish an issue of the Journal.
WHAT WE DID
We redesigned OJS with a focus on improving communication and coordination as well as enhancing the visibility of task status and action items to ease and streamline the work done by academic journal editors at all phases of the issue creation process. From receiving a rough manuscript from an author to coordinating the peer review process, copy-editing, and compiling suitable articles to publish in an issue, our redesigned OJS empowers editors to get the work done right.
OUR JOURNEY
1. Contextual Inquiries
2. Data Analysis and Modeling
3. Ideation
4. Paper Prototyping
5. Thinkalouds
6. High Fidelity Prototype
2. Data Analysis and Modeling
3. Ideation
4. Paper Prototyping
5. Thinkalouds
6. High Fidelity Prototype
Contextual Inquiries
To understand the context of OJS's use and we conducted semi-structured interviews with the following users of the system in their own environment. We asked them a set of standard questions and then observed while they did their usual tasks to find their pain points and frustrations with the system.
A Journal Manager | Two Journal Editors | Two Journal Reviewers | One Author
These sessions gave us a complete idea of how OJS works and what its limitations were. It also helped us understand redundant functions and work-arounds users had come up with to complete their tasks.
The inquiries revealed that journal editors were the most frustrated users of the system, since they were the ones who co-ordinate with all the other parties. We also learnt how they had devised ingenious ways to overcome its lack of support for some of their processes.
Following are some of the pictures taken during our inquiries.
Pictures from our Contextual inquires with the users of OJS
The Editors used 5 different systems for managing, communicating and co-ordinating with the other users of the system. Due to the constraints of the project timeline we narrowed our focus down to solving the problems faced by the Editors, as that was most challenging and they were the heavy users and had the most problems with OJS.
Analyzing the Data
We used flow modeling technique to better understands what tasks happened at which phase of the review/edit process, and we needed to figure out who was involved at what stage and how they affected the process. The flow diagram helped us tremendously in our design process and visioning of the solution.
Flow chart detailing a manuscript's journey from its author to publication
A time lapse of our 3 and half hour long affinity mapping process where we burned our fuels all night to absorb all the data we had gathered until now
Creating an affinity diagram and flow diagrams illuminated the very process-driven tasks that editors do to publish a journal issue.
Analysis and Modeling helped us identify areas of focus:
1. Highlight manuscript status and pending tasks
2. Improve coordination and eliminate conflicts between users.
3. Update visual design to promote discoverability and awareness of available feature.
1. Highlight manuscript status and pending tasks
2. Improve coordination and eliminate conflicts between users.
3. Update visual design to promote discoverability and awareness of available feature.
We started to envision what a possible solution might look like and started adding features and functionalities that we derived from visioning exercises and story boards that we created.
Paper Prototyping and Think-alouds
We created paper prototypes which we used to conduct think-alouds with the journal editors to find out how well it supported their work process and get feedback for possible improvements.
The New and Improved Open Journal System
After Validating the low-fi prototype, we built a high fidelity mock-up with Axure to embody our design solution and conducted think-alouds with editors to discover how we might improve the idea.
Takeaways
This project taught me how to do user research right. We invested a lot of time upfront to understand our problem space and we used many visioning and modeling techniques to process the data we gathered. This really helped us create a solution that our end users and stake holders really liked, and the solution was backed up with solid data.
Contextual inquiries are exceptionally great at building empathy towards the users.
The joy on the users face when we showed them the hi-fi mockup was really motivating to create wonderful experiences that solves user problems and are a joy to use.
