Dr. Luther named ACWM Emerging Scholar

Dr. Luther was selected as one of eight Emerging Scholars by the American Civil War Museum in Richmond, VA. He will give an invited presentation on Civil War Photo Sleuth to audiences at the grand opening of the newly expanded museum on May 4. The goal of the program is to “highlight some of the most interesting work of the next generation of writers, communicators, and thinkers of Civil War era history/public history.”

Two papers accepted for IUI 2019

Two members of the Crowd Lab each had a paper accepted for presentation at the upcoming IUI 2019 conference in Los Angeles, CA. The acceptance rate for this conference, which focuses on the intersection of human-computer interaction and artificial intelligence, was 25%.

Crowd Lab Ph.D. student Vikram Mohanty will present “Photo Sleuth: Combining Human Expertise and Face Recognition to Identify Historical Portraits“, co-authored with undergraduate David Thames and Ph.D. student Sneha Mehta. Here is the paper’s abstract:

Identifying people in historical photographs is important for preserving material culture, correcting the historical record, and creating economic value, but it is also a complex and challenging task. In this paper, we focus on identifying portraits of soldiers who participated in the American Civil War (1861- 65), the first widely-photographed conflict. Many thousands of these portraits survive, but only 10–20% are identified. We created Photo Sleuth, a web-based platform that combines crowdsourced human expertise and automated face recognition to support Civil War portrait identification. Our mixed-methods evaluation of Photo Sleuth one month after its public launch showed that it helped users successfully identify unknown portraits and provided a sustainable model for volunteer contribution. We also discuss implications for crowd-AI interaction and person identification pipelines.

Crowd Lab Ph.D. student Tianyi Li will present “What Data Should I Protect? A Recommender and Impact Analysis Design to Assist Decision Making“, co-authored with Informatica colleagues Gregorio Convertino, Ranjeet Kumar Tayi, and Shima Kazerooni. Here is the paper’s abstract:

Major breaches of sensitive company data, as for Facebook’s 50 million user accounts in 2018 or Equifax’s 143 million user accounts in 2017, are showing the limitations of reactive data security technologies. Companies and government organizations are turning to proactive data security technologies that secure sensitive data at source. However, data security analysts still face two fundamental challenges in data protection decisions: 1) the information overload from the growing number of data repositories and protection techniques to consider; 2) the optimization of protection plans given the current goals and available resources in the organization. In this work, we propose an intelligent user interface for security analysts that recommends what data to protect, visualizes simulated protection impact, and helps build protection plans. In a domain with limited access to expert users and practices, we elicited user requirements from security analysts in industry and modeled data risks based on architectural and conceptual attributes. Our preliminary evaluation suggests that the design improves the understanding and trust of the recommended protections and helps convert risk information in protection plans.

Congratulations to Vikram, David, Sneha, Tianyi, and their collaborators!

Photo Sleuth press in Slate, Smithsonian, and more

Our Civil War Photo Sleuth project got a burst of publicity in recent weeks, leading to hundreds of new site registrations and contributions. Here is a round-up of some highlights:

New Photo Research Tool in Civil War Times magazine

Thanks to these media outlets for the great publicity!

Presented at Image of War Seminar

Dr. Luther and his frequent collaborator Ron Coddington, editor and publisher of Military Images magazine, gave an invited presentation on Civil War photo sleuthing at the 18th annual Image of War Seminar in Alexandria, VA, hosted by the Center for Civil War Photography. The presentation included a brief history of American Civil War photography and a live demonstration of the Civil War Photo Sleuth website.

Public launch of Civil War Photo Sleuth website

Assistant Surgeon Francis Marion Eveleth, identified by Dr. Luther via Civil War Photo Sleuth website

On August 1, we held our public launch party for the Civil War Photo Sleuth website at the National Archives Building in Washington, DC. Our team spent the day helping new users (in person and online) get signed up and contributing to the site. Dr. Luther and Military Images editor Ron Coddington gave brief remarks, and we were joined by many distinguished guests, including Library of Congress and National Archives staff. The National Archives’ Innovation Hub provided the perfect setting for the event. We were also grateful for VT Computer Science and Civil War Times for event photography and social media coverage (more photos are available here).

A highlight of the event was sharing a new identification — made via the website — of a previously unknown Civil War soldier tintype from the Library of Congress collection. The donor of the photo, Tom Liljenquist, was present to receive the identification.

Keynote at Stories of War Symposium

Attendees of the Stories of War symposium

Dr. Luther gave an invited keynote presentation at Vietnam War / American War Stories: A Symposium on Conflict and Civic Engagement, hosted by the Institute for Digital Arts & Humanities at Indiana University-Bloomington. Other keynote speakers included included David Ferriero, the Archivist of the United States; and John Bodnar, Distinguished and Chancellor’s Professor of History at IU. Dr. Luther’s presentation was titled, “Rediscovering American War Experiences through Crowdsourcing and Computation,” and the abstract was as follows:

Stories of war are complex, varied, powerful, and fundamentally human. Thus, crowdsourcing can be a natural fit for deepening our understanding of war, both by scaling up research efforts and by providing compelling learning experiences. Yet, few crowdsourced history projects help the public to do more than read, collect, or transcribe primary sources. In this talk, I present three examples of augmenting crowdsourcing efforts with computational techniques to enable deeper public engagement and more advanced historical analysis around stories of war. In “Mapping the Fourth of July in the Civil War Era,” funded by the NHPRC, we explore how crowdsourcing and natural language processing  (NLP) tools help participants learn historical thinking skills while connecting American Civil War-era documents to scholarly topics of interest. In “Civil War Photo Sleuth,” funded by the NSF, we combine crowdsourcing with face recognition technology to help participants rediscover the lost identities of photographs of American Civil War soldiers and sailors. And in “The American Soldier in World War II,” funded by the NEH, we bring together crowdsourcing, NLP, and visualization to help participants explore the attitudes of American GIs in their own words. Across all three projects, I discuss broader principles for designing tools, interfaces, and online communities to support more meaningful and valuable crowdsourced contributions to scholarship about war and conflict. 

Beta release of Photo Sleuth software in Gettysburg

The Civil War Photo Sleuth team. From left: Intern Natalie Robinson, Lab Director Kurt Luther, Intern Ryan Russell, and Ph.D. Student Vikram Mohanty.

The Civil War Photo Sleuth team released a beta version of our software for identifying unknown Civil War photos at the 45th Civil War Artifact and Collectibles Show in Gettysburg, PA. Our table was set up next to our partners at Military Images Magazine. The team was excited to help dozens of attendees sign up for the site, and these new users tentatively identified several unknown soldier photos during the show.

We also demoed an earlier version of the Photo Sleuth software at the previous year’s Gettysburg show in 2017. More details here.