My Year as a JSTOR Labs Intern

My Year as a JSTOR Labs Intern

My name is Jake Silva and I’m a master’s student from the University of Michigan’s School of Information specializing in Human Computer Interaction and Data Science. For the past nine months, I’ve worked on the JSTOR Labs team in Ann Arbor, Michigan where I’ve observed and participated in the team’s use of cutting edge technologies and methodologies in UX Design and Research, Data Science and Product Development. These include guerilla user-testing, week-long design sprints, fuzzy text-matching, geospatial tagging and optical-character recognition technology. While the use of these technologies and methodologies is exciting and innovative,  they serve as tools to support Labs in fulfilling its core mission: exploring ways to make scholarship richer and more accessible for researchers, teachers and students as well as the general public.

This mission became very evident during our development of a mobile app focused on constitutional scholarship. To test our design ideas, we set up inside a coffee shop across from the University of Michigan and recruited students to participate in 10-minute usability tests. We used paper prototypes to observe their interactions with our design ideas and gauged what needed to change. During these tests, one political science student became so excited by the idea of the app that he offered to recruit other students for user testing and asked us to contact him once we released it. It’s this excitement and usefulness for users that Labs ultimately strives to achieve with its projects. This example also illustrates one of the principle methodologies Labs uses to test, validate, and build its ideas: the design sprint.

The design sprint, which we also refer to as a “flash build” or Labs week, is inspired by the “Lean Startup” movement, a model for iterating on ideas rapidly based on user input and data. For the sprints, the team meets in a single location and uses the lean methodology to produce a working prototype in a week. I participated first hand in this process during our Labs week to develop a constitutional scholarship app. On Monday, we brought in folks outside the Labs team and focused on brainstorming ideas for the app. This involved multiple individual sketching rounds, brief design presentations to the room and consensus building by vote to come up with a few design solutions. We then turned these into paper prototypes to test with users the next day. Once a clear design solution emerged from the tests, we began to refine each interaction in the app as well as create the necessary technological infrastructure to build it. At each iteration of our design, we went out into the field to test and validate with users. As a participant in these tests, I learned the incredible value they provide in informing the design of a product. As a team, we each bring our own biases, assumptions, and ideas to a design solution and risk overlooking design flaws as we spend more time with the product. User testing helps mitigate these problems and is an unbiased way to solve conflicting design ideas within a team. As an aspiring user-centered design professional, I was happy to see and learn from our team’s emphasis on placing the user first during our sprints.

Technologically, Labs uses a variety of tools to accomplish its mission. I won’t soon forget my first week when I was bombarded with a variety of technologies including Git, Apache Solr, Python, Django, MapReduce and AWS. Other technologies soon followed like PostgreSQL, Hadoop, AngularJS and data visualization tools. Over nine months, I built and honed these skills as well as learned about new ways to manipulate and model data such as entity extraction and geospatial tagging. During my time here, I worked on the technology side of several Labs projects. For example, Classroom Readings aims to help teachers find reading assignments for their classes. I helped to expand the initial body of articles available to teachers from 9,000 to over 50,000 using the processing power of Hadoop MapReduce, a commonly used programming model in big-data science. After the expansion, I designed and built functionality to make it easier for JSTOR’s Education & Outreach team to manage curated readings lists – or “QuickLists” -- on the site. Another project I worked on was creating data visualizations using Labs’ Understanding Shakespeare API. The API provides data on JSTOR scholarship that matches with individual lines in Shakespeare plays. Using open source JavaScript visualization libraries, I created two visualizations. One shows the number of JSTOR articles citing Shakespeare over time (starting in 1729!) and the other is an interactive heatmap showing the intensity of scholarship for the top five characters in each play per act.

In addition to honing my UX, data, design, and development skills, I also learned what it takes for a team to be successful. The Labs team is a small but diverse group, incorporating individuals with engineering, UX design, visual design, and product and project management skills. We met for daily standup meetings and reflected throughout the year on how we could improve as a team, where we succeeded and failed and how we fit into the greater JSTOR team. This is important as tools, methodologies, and priorities rapidly shift in a mission-driven technology company. I’ve learned so much from this fantastic team over the last nine months and greatly appreciate their support and interest in my development. I’m also happy to have worked on making scholarship richer and more accessible. Finally, I feel lucky to have had the opportunity to work in such an innovative space and look forward to returning to JSTOR after this summer for the 2016-17 academic year.