Designing a Topic-Based Literature Exploration Tool in AR — An exploratory study for neuroscience

The large and increasing amount of scientific literature makes it difficult for researchers to analyse and understand relations between topics even in their specific sub-field. Neuroscience researchers are interested in relations between, for example, anatomical regions of the brain and the diseases that affect them. To explore relations in the extensive body of literature, using the topics themselves rather than individual articles, can provide a higher-level approach. We have created a prototype interactive AR environment to learn more about how topic-based literature browsing might aid researchers in analysing and understanding relations between topics. Given the three-dimensional nature of the brain, we postulate that visualizing neuroscience topics in Augmented Reality would support the exploration of relations between them and thus improve and extend existing literature exploration workflows. We follow a usercentered approach to identify visualization and interaction design requirements. Using an existing analysis of tens of thousands of neuroscience papers, we designed an interactive AR environment to support researchers in finding relations between brain regions and brain diseases that integrates with existing literature review practices. We carried out two qualitative evaluations to verify our design, first with eight neuroscience students as domain experts and then with seven experienced researchers as literature exploration experts. Our analysis of participants’ feedback shows that visualizing topics and their relations in the immersive AR environment is clear, understandable and helpful for topic-based literature exploration, specifically, between brain regions and brain diseases. Our AR literature exploration tool has the potential to be used by neuroscientists in their routine literature review

DatAR: An immersive literature exploration environment for neuroscientists

Maintaining an overview of publications in the neuroscientific field is challenging, especially with an eye to finding relations at scale; for example, between brain regions and diseases. This is true for well-studied as well as nascent relationships. To support neuroscientists in this challenge, we developed an Immersive Analytics (IA) prototype for the analysis of relationships in large collections of scientific papers. In our video demonstration we showcase the system’s design and capabilities using a walkthrough and mock user scenario. This companion paper relates our prototype to previous IA work and offers implementation details

Exploring relations in neuroscientific literature using Augmented Reality: A design study

To support scientists in maintaining an overview of disciplinary concepts and their interrelations, we investigate whether Augmented Reality can serve as a platform to make automated methods more accessible and integrated into current literature exploration practices. Building on insights from text and immersive analytics, we identify information and design requirements. We embody these in DatAR, a system design and implementation focussed on analysis of co-occurrences in neuroscientific text collections. We conducted a scenario-based video survey with a sample of neuroscientists and other domain experts, focusing on participants’ willingness to adopt such an AR system in their regular literature review practices. The AR-tailored epistemic and representational designs of our system were generally perceived as suitable for performing complex analytics.We also discuss several fundamental issues with our chosen 3D visualisations, making steps towards understanding in which ways AR is a suitable medium for high-level conceptual literature exploration

Introduction to the Sixth Annual Lifelog Search Challenge, LSC'23

For the sixth time since 2018, the Lifelog Search Challenge (LSC) was organized as a comparative benchmarking exercise for various interactive lifelog search systems. The goal of this international competition is to test system capabilities to access large multimodal lifelogs. LSC'23 attracted twelve participanting teams, each of whom had developed a competitive interactive lifelog retrieval system. The benchmark was organized in front of live audience at the LSC workshop at ACM ICMR'23. As in previous editions, this introductory paper presents the LSC workshop and introduces the participating lifelog search systems

Introduction to the Sixth Annual Lifelog Search Challenge, LSC’23

For the sixth time since 2018, the Lifelog Search Challenge (LSC) was organized as a comparative benchmarking exercise for various interactive lifelog search systems. The goal of this international competition is to test system capabilities to access large multimodal lifelogs. LSC’23 attracted twelve participanting teams, each of whom had developed a competitive interactive lifelog retrieval system. The benchmark was organized in front of live audience at the LSC workshop at ACM ICMR’23. As in previous editions, this introductory paper presents the LSC workshop and introduces the participating lifelog search systems

Indexing, Searching, and Retrieving of Recorded Live Presentations with the AOF (Authoring on the Fly) Search Engine

The tremendous amount of data resulting from the regular usage of tools for automatic presentation recording demand for elaborate search functionality. A detailed analysis of the according multimedia documents is required to allow search at a very detailed level. Unfortunately, the produced data differs significantly from traditional documents. In this demo, we discuss the problems appearing in the presentation retrieval scenario and introduce aofSE, a search engine to study and illustrate these problems as well as to develop and present according solutions and new approaches for this task