The Problem

The Client

Open Context is an open digital repository of cultural heritage and archaeology data maintained by a 501©3 nonprofit organization, Alexandria Archive Institute. The platform has published 150 projects, representing 2 million items contributed by more than 1,000 data authors. Open Context provides two main services: publishing and exploring services.

As archiving is an important part of data preservation and access, our clients posed the concern that a focus on archiving alone meant that data would often be poorly described, hampering user understanding and data reuse. Additionally, for privacy purposes, they did not track users and thus knew very little about how users interacted with the platform. 

Our 4 member group, the Emphasis Lab, was tasked with the role of investigating Open Context’s user experience and provide corresponding findings and recommendations that could be implemented for future versions of the platform.

Project Duration: January 2022 - May 2022

research objectives

  • Understand the motivations of Open Context’s primary user groups in accessing archaeological data and use cases of applying the data.

  • Determine if the users accessing Open Context are able to find the information they seek in a format valuable to their needs.

  • Identify areas in which the user experience may be improved and provide concrete recommendations for future development.

methodology

System Analysis

Market Research

Assess Usability

System Analysis

interaction mapping

We visually mapped the Open Context site to understand site components and how they work with each other.

  • Explore Open Context’s information architecture and how pages interlink to internally and externally

  • Become familiarized with the system’s functions, features, and hierarchal organization structures

Findings + REcommendations

user interviews

We conducted semi-structured interviews to understand needs of Open Context’s core user bases.

  • There were x6 interviews completed in total at 60 minutes each. We had x2 participants per each category listed:

    • Current Open Context users

    • Open Context team members

    • Archeological researchers, educators, and enthusiasts that may be the potential users for Open Context

Interview transcripts were analyzed via thematic analysis. Each interview session was reviewed by at least two team members, extracting and annotating meaningful information into affinity notes on a virtual whiteboard tool, Miro. Notes in similar themes were clustered and formatted into an affinity wall.

Findings + Recommendations

Affinity wall with thematic groupings of interview findings and quotes (interviewees identified by color-coded notes)

Market Research

Comparative Evaluation

We compared Open Context’s system, positioning and product against competitive systems and other systems with tangential similarity.

To identify and evaluate the key usability strengths and weaknesses of Open Context’s online system competitors, we first determined its appropriate competitors. As the system that we were working with was the digital archaeological repositories, we chose to focus on Web platforms for preservation and public online access to archaeological research data. Therefore, based on Newman's taxonomy, we selected x7 competitors with 5 types of comparisons in the archeological archives space.

Using the findings from our interviews analysis, we created a matrix of 20+ features and tools and analyzed each competitor against data search, storage, and export. Our final comparison primarily focused on:

  • Marketing positioning

  • Partnerships

  • System accessibility

  • Other common functions

findings + recommendations

surveys

We conducted quantitative analysis of user needs against a broader sample of participants meeting Open Context’s core user base.

To gain insights to improve database exploration and search function of Open Context, we decided to target current and potential users:

  • All Open Context users

  • Archeological researchers, educators, and enthusiasts that may be the potential users

Based on project constraints, the team aspired to receive a minimum of 50 responses as a target sample size. To effectively gather information from the target audience, our team used a stratified sample method to randomly select people from both of our target respondent populations. The survey questionnaire was drafted, reviewed by the client, then piloted against 6 people (Emphasis Lab and client contacts). The final survey was designed in Qualtrics.

To recruit survey participants, the team relied on the client to distribute the survey by posting survey links on Open Context’s Twitter and sharing via email distribution lists. Through this, the client estimated that the survey reached out to a few thousand potential participants, of whom 108 people opened the survey, 76 people answered at least one question and 56 people completed the survey, with a completion rate of 74%. In the responses, 54% of respondents had experience using Open Context. Among people who had not used Open Context, 92% of them described them as Archeological related practitioners. In general, 96% of respondents were within our target population.

Findings + recommendations

Finding: Open Context users are “expert” users

Finding: Current and future users express similar needs in archaeological database functions

Assess Usability

Heuristic evaluation

We assessed the Open Context Search product against a checklist of usability best practices.

usability testing

We reviewed users interacting with the Open Context search product to assess their ability to complete tasks and their thought process.

Research Questions

  • Which areas of the site are the most difficult to navigate and why?

  • What functions do not perform as users expect?

  • How do users interact with the Search and Filter tools?

  • What do users think of the Open Context live site and the staging site?

Methodology

To understand how users interacted with Open Context, a testing plan was established, where participants were asked to complete a series of 5 system tasks over moderated virtual sessions. These task observations were followed by post-task and post-test questionnaires.

Study participants consisted of x5 individuals who had never used Open Context before:

  • x2 database novices

  • x2 experienced with databases

  • x1 who has never used an online database repository to store their work

These participants were recruited from survey respondents who opted into future studies, and directly sourced by the Open Context team. A screening questionnaire was distributed to ascertain fit to established criteria. The screener focused on participant demographic information, their self-identified expertise level with databases, and testing availability. Final participants were identified based on degree of database expertise and demographic information.

The Study

System tasks revolved around the following 5 Open Context functions and were accompanied by written and verbal instruction:

  1. Project Search and locating data records

  2. Advanced filtering process

  3. Narrowing results using the chronological distribution slider

  4. Data export and report customization

  5. Map-based search in both live and staging environments

Findings + Recommendations

Group Heuristic Evaluation

The analysis performed by the Emphasis Lab is based on Nielsen’s 10 Usability Heuristics for User Interface Design. Using this framework, the team audited Open Context interfaces. Four evaluators performed x2 independent assessments to review general interface feedback and consistency across system elements. Using the heuristic checklist, each evaluator produced a list of “problems” ranked against a 0 (Not a usability issue) to 4 (Usability catastrophe) scale. Independent assessment was followed by a team calibration to review problems against frequency and severity, and to decide upon a universal rating for each.

Findings + Recommendations

Finding: Lack of system feedback. Note the lack of clear visual headers on the page.

Finding: Accessibility and Inclusion. 18 contrast errors were identified on this media record entry page.

Finding: Filters go unnoticed. This is a screenshot of an initiated search, where users need to scroll down to see the returned data record results.

Finding: Iconography. The left image shows the current download button on the Open Context map where the icon is relatively small. The right image mockup representing a larger and clearer icon.

Reflections

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Areas for consideration

At times, the team relied on personal networks for study participation, which could have generated familiarity bias during tests/interviews. Additionally, due to our time frame (Jan 2022-May 2022), some of the processes and techniques may have been less robust than ideal, or were beyond the project scope. However, all aspects of this investigative process indicated that Open Context remains an invaluable tool to both data authors and data seekers alike and should continue to perform as such.

My takeaways

  • Do not assume user paths. There were a lot of aspects about Open Context that were only discoverable through the user interviews, surveys, and testing. These provided new insights from various perspectives that would have not rendered from our team’s limited experience within the platform.

  • There is more to usability than architecture. Findings regarding accessibility, jargon, and iconography proved to be just as important as the actual site structure when it came to evaluating the user experience on a holistic level. I will be sure to stay cognizant of these methods and approaches when gauging usability of products in the future.