Library of Congress

UX Research & Analysis - Product Design

This project critically evaluates access points to the Library of Congress digital audio and video collections and design solutions to improve the engagement users have with each artifact and collection.

Client: Library of Congress
Timeline: 12 Weeks
My Role: User Experience Researcher
Tools: Photoshop, Sketch, Figma, Pencil & Paper

The reading room at the Library of Congress, Washington, D.C.

Project Objective

Explore new ways for audio and video discovery, acquisition, and interaction on the Library of Congress website.


Brainstorming, Literature Review, Competitive Analysis, User Scenarios, Contextual Interviews, Affinity Diagramming, Experience Modeling, Sketching, Prototyping



Library of Congress is the largest library in the world and the first one to start making their resources available online. It has holdings that currently include 21,000 digitized audio records and 8500 digitized videos, plus many more records.
In the fiscal year 2017, the Library of Congress(LoC) has received over 110 million visits to its website with over 503 million page views and 2.7 million downloads. The US Congress, schools, researchers, authors and many more rely on the Library as an archive and engage with it as a source of authentic knowledge. For many artifacts, the Library is the only source where they are digitally available. 
The Library is looking for innovative solutions to democratize digital and physical access to their collections and to build a lifelong connection with the people who use it.



Target Audience

Library of Congress is home to a large collection of audio and video(A/V) material that makes for great primary source content in various projects, research papers, and even documentaries. Usage of the digital collection often follows school schedules and due to scope and access, we are focusing on individuals found at universities. Our primary target users include researchers, educators, and authors who need primary sources and information in the domains on American history and government, as well as creatives who are involved in the domains of music, art, journalism, and history that use the Library as a source of information for their projects



MacBook Pro – 8




  • Supporting context-based distinguishing for assets might be useful in user search because different users might search for similar information but with the different contexts of use.
  • Half of the searches conducted to begin with keyword strategies (analytical strategies) and the remainder begins with partition selection (browsing strategies).
  • Useful to have the proxy method for displaying video results when users need quick and fast skimming of video over high-resolution content.

Video Search Process Phases

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Starting: defines/refine the need/request in order to develop a set of criteria
Scoping: implicitly or explicitly decide on the general approach and strategy
Applying: user initiates formal interaction(s) with the information resources
Selecting: make decisions on what to select from a returned set
Iterating & Ending: involves modification to the search or corresponding criteria

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To identify opportunities and threads, we conducted a deep competitive analysis to learn about similar or best-in-class platforms:

  • Video preview while hovering over thumbnails to get an idea of the content beyond a thumbnail
  • Short descriptions on the search results page provide insight into what content to expect
  • Related search suggestions based on initial keywords to help refine searches 
  • Providing chapters to different sections within a video to quickly jump to topics and parse content within the video
  • Creating short clips from the original video to extract and share relevant content


Below are a few user scenarios that demonstrate how some new ideas might make it easier for people to discover new A/V content and judge its relevance to their use case. 

Personal Tags on A/V Content: 
Bill has a History project due next week. To find a relevant clip, he searches for his topic on the Library of Congress website and finds a video. In the video, he tags certain video segments with a relevant title so he can revisit it later.

Crowdsourced Tags on A/V Content: 
Sarah has to complete an article about Mozart. On the LoC website, she finds a video with tags that are comments about each section of the video previously marked by other viewers; using the tags she can easily skim through the video.

Long A/V content split up into Chapters: Maya can view a video’s chapters which segment the video into smaller chunks so she can determine if the video covers any relevant topics to her interests. She finds a relevant chapter and the video marker skips to that time. (source of inspiration: Twitch)

 Most Watched Segments of A/V Content: Ann searches and finds a video for “contemporary views about civil war” to write an essay about it. She watches the parts that video player tells are most-watched, which indicates what parts are popular or generate the most debate (source of inspiration: Soundcloud)

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Recommended/Related Content to current A/V Content: Cassie is conducting exploratory research on the impact of wars in Europe. After searching and watching some videos on the topic, she is presented with recommended videos for the topic, and she browses them.

Previewing A/V Content: Natalie is looking for videos related to the battles in the French Revolution to get inspiration for her documentary. She uses the LoC interface to hovers over the videos and preview them. She doesn’t find any war scenes of the first few videos, so she skips them, and clicks one further down the list.

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We interviewed 7 Subject Matter Experts(SMEs) from the Library of Congress and academia who knew the platform best and offered key insights into their fields including User Experience, Engineering, and Cataloging. We intended the interviews to be free-form but had a few areas of interest including, how audio/video content is organized and accessed in the LoC? what technical systems enable search and discovery of content? how is the content model of LoC artifacts used in searching? what are interesting visual search interface examples in the wild? how are search results displayed and prioritized? What metadata and parameters affect them? etc. 

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SME interviews allowed us to learn the following results, add the depth our content needed to stand out and get noticed, and craft a really great interview focus:

●   Metadata consistency, richness, quality, etc. are concerns while digitizing artifacts
●   Experts care about the richness of metadata and fine-grain details while searching
●   They really care about specific collections and are extremely familiar with those
●   Have to go to online-libraries or digital collections, e.g. LOC, WGBH OpenVault, etc.
●   Most agreed that current digital-libraries and collections cater to a more “experienced” audience like academics or researchers than a more lay user
●   The collections are often organized in a way that makes sense to the curator but not the user; e.g. naming a collection after the dataset sponsor and irrelevant to the data.





  • Historians & Creatives
  • Male and Female
  • Ages 20s to 60s

Interview Focus
●   Understand the current experience for searching A/V content within the participant’s domain
●   Understand how users discover media relevant to them and their domain
●   Learn about the participant’s needs and frustrations while searching for A/V content.


This affinity diagram acts as a collection of all raw data and insights (over 400 yellow notes) gathered during the contextual interviews and the interpretation sessions. The research team looked for correlations and themes to organize the data and understand the scope of the problem: the insights, worries, issues, and key elements in the user's A/V search habits.



We identified five overarching themes(green notes) that reflect the user story at the highest level and can be used to navigate the rest of the diagram. The green notes also encompass the blue and pink groupings beneath them. We found that people use prior knowledge and experience to search for A/V contents for different purposes, from education to personal needs. Content quality, metadata, popularity, relevance, and authenticity are some of the crucial challenges to the A/V content discovery process.


This user journey map visualizes the current process that our target user goes through while searching for A/V content.  It reflects the data collected during the contextual interviews and organized in the affinity diagram to illustrate what triggers the need to search and discover A/V artifacts and the following events. 


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The journey map shows the stages users need to get through before they can find the desired media. If they can’t find the data in the first source, they must then go to the next platform, stepping through the process again. It also identifies the searching and discovery tasks that an A/V seeker is struggling to accomplish. It shows the step by step actions they take, the tactics(strategies) they use, the problems they run into, and the potential opportunities and solutions that could be provided to ease the whole process for them. 


This identity model highlights the underlying identity elements of our target users. This model focuses on how the A/V search process enhances or detracts from a person’s sense of self. We wanted to be mindful of the population we were designing for, the different identities they have, what characteristics people value in themselves, and how that impacts their search and access to A/V materials.

IDENTITY – Horizontal Layout
IDENTITY – Horizontal Layout abi
IDENTITY – Horizontal Layout-1

After going through several iterations, we created three different identity sections: I am, I care about, and I do. These were the identities that we felt would best capture the personalities of our users. It helped us to better understand the variety of personalities, interests, and preferences of our users. It also demonstrates how these attributes influence Users' A/V searching decisions to either use or dismiss particular content.



 Wall walking is the first step before beginning to ideate conceptual possibilities in response to the user data. It allowed members of the team to immerse themselves into the data and draw up design ideas from the user data. The team silently went through the experience models and the affinity diagram to follow the thread, build our own understanding of the data, and explore the design consequences. Then, we identified and wrote down plusses, minuses, design ideas, and questions on sticky notes and stuck them on next to the related sections.

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After the wall walk, the first stage of the design ideation was to make a list of Issues and Hot Ideas that we determined as the most strategic ideas.
The Issues List consists of the observations we made about the practice, what the team believes is broken and should be addressed in the data, what might be an opportunity for improvement, and what is surprising points that can be useful in later design thinking to improve the user’s experience.


The Issue list is created keeping in mind how we can address the world of the user, support, or solve user challenges to add value and improve their experience. For example, some participants tried to search for a certain media of their choice and they kept getting irrelevant data from random unauthorized sources.

Then we gathered a summary of hot ideas which are design ideas that may improve the process of discovery, acquisition, and interaction on an ideal A/V online digitized archive. Stimulating creative design thinking as a starting point, we produced hot ideas that include a wide range of strategic, extreme and sometimes contradictory ideas. We used this as a trigger to inspire new thinking and imagination that could contribute or ideated further in the product concept phase. For example, providing keyword searches, literal and qualitative tags, along with easy to navigate visual representation of data that could help to generate relevant results.



In the next stage, to bridge data and design, we discussed the initial product concepts and went through hot ideas and issues from the previous step. Visioning––as a way of brainstorming ideas through visual storytelling–– helped us to tell coherent user stories about the new world of the user and generate design ideas and visions. One team member started and others quickly added as a way to get ideas flowing within the team.
After the visioning process, the team had a direction of development for the user. Then,
 the ideas got fine-tuned and corroborated with team members stating the positives and negatives of each vision. The team spun out a story about the new practice they proposed that would enhance a product through technology.



In the final ideation step, the visions got fine-tuned further to dig into the details of each concept and avoid a lot of overloads. We narrowed down and iterated on each design ideas to improve the initial product concept. It made the resulting vision into a transformative experience for the user and allowed the team to focus more on how the design relates to the concepts.



The idea of wall walk and visioning sessions was to start wide with radical varied ideas and then drill them down to generate coherent, implementable product concepts.
Once the team generated several design ideas, we incorporated the best individual visions' findings to synthesize product concepts. Below is the overview of three explicit product concepts based on our insights:

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LoC A_V Final Presentation
  • Offering related keyboards that could potentially be added to the search term
  • Collapsable quick view of the audio file
  • Download, share, and collection icons followed by a tooltip
  • Metrics to show the number of views and downloads
  • Different sections of the audio file are labeled
  • Trim feature
  • Tagging of content upfront
  • Qualitative tags such as capturing emotions
  • Interactive transcript
  • Highlights the parts that is currently playing
  • Click on a text to jump to the related audio part
  • Showing the collection the audio file belongs to 


LoC A_V Final Presentationk
  • Highlighted search keywords for better parsing of relevancy
  • Media type of results determined by keywords
  • Dynamic thumbnails shown based on keywords
  • Thumbnail preview on hover
  • Tagging of content upfront
  • Qualitative tags such as capturing emotions
  • Chunking content into segments with titles and contextual descriptions
  • Ability to create and share clips of short segments of videos
  • Computer-generated transcripts
  • Click on segments to jump to that part of the video


LoC A_V Final Presentationl
  • Selectable topics on the home page to create dynamic topic lists
  • Featured content grid will refresh based on selected topics
  • Clicking featured content takes user to a Curated  Content Page
  • Explore card in search results
  • Introduces search topic to new readers
  • Contains recommendations and links to start exploring the topic
  • Curated topic pages are designed to introduce a topic to new readers
  • Introduce the topic to new readers
  • Provide many different jumping-off points for topic exploration
  • The page layout changes to best accommodate relevant content

Design phase is happening now. Stay tuned for updates coming soon!
Here’s a preview:

Moving forward in Spring 2020, we will identify which product concepts will be designed and:

  • Storyboard to work out the details of the design concepts
  • User Environment Design to structure the system
  • Interaction design patterns identification for an initial user interface
  • Paper prototype and user testing to validate concept, function, and interaction
  • User feedback interpretation from prototype interviews to make changes
  • 2-3 iteration rounds of the paper prototype testing
  • Online click-through prototype
  • User testing of the interaction and visual design in online format
  • Design iteration with 2 rounds of users to ensure overall acceptance