Niklas Elmqvist, Ph.D.

@article{Wong2015,
title = {Evaluating Social Navigation Visualization in Online Geographic Maps},
author = {Yuetling Wong and Jieqiong Zhao and Niklas Elmqvist},
url = {http://www.umiacs.umd.edu/~elm/projects/socnav-eval/socnav-eval.pdf, Paper},
year = {2015},
date = {2015-02-22},
journal = {International Journal of Human-Computer Interaction},
volume = {31},
number = {2},
pages = {118--127},
abstract = {Social navigation enables emergent collaboration between independent collaborators by exposing the behavior of each individual. This is a powerful idea for web-based visualization, where the work of one user can inform other users interacting with the same visualization. We present results from a crowdsourced user study evaluating the value of such social navigation cues for a geographic map service. Our results show significantly improved performance for participants who interacted with the map when the visual footprints of previous users were visible.},
keywords = {}
}

@article{Gad2015,
title = {ThemeDelta: Dynamic Segmentations over Temporal Topic Models},
author = {Samah Gad and Waqas Javed and Sohaib Ghani and Niklas Elmqvist and Tom Ewing and Keith N. Hampton and Naren Ramakrishnan},
url = {http://www.umiacs.umd.edu/~elm/projects/theme-delta/theme-delta.pdf, Paper},
year = {2015},
date = {2015-02-17},
journal = {IEEE Transactions on Visualization and Computer Graphics},
volume = {21},
number = {5},
pages = {672--685},
abstract = {We present ThemeDelta, a visual analytics system for extracting and visualizing temporal trends, clustering, and reorganization in time-indexed textual datasets. ThemeDelta is supported by a dynamic temporal segmentation algorithm that integrates with topic modeling algorithms to identify change points where significant shifts in topics occur. This algorithm detects not only the clustering and associations of keywords in a time period, but also their convergence into topics (groups of keywords) that may later diverge into new groups. The visual representation of ThemeDelta uses sinuous, variable-width lines to show this evolution on a timeline, utilizing color for categories, and line width for keyword strength. We demonstrate how interaction with ThemeDelta helps capture the rise and fall of topics by analyzing archives of historical newspapers, of U.S. presidential campaign speeches, and of social messages collected through iNeighbors, a web-based social website. ThemeDelta was evaluated using a qualitative expert user study involving three researchers from rhetoric and history using the historical newspapers corpus.},
keywords = {}
}

@article{Madhavan2014,
title = {DIA2: Web-based Cyberinfrastructure for Visual Analytics of Funding Portfolios},
author = {Krishna Madhavan and Niklas Elmqvist and Mihaela Vorvoreanu and Xin Chen and Yuetling Wong and Hanjun Xian and Zhihua Dong and Aditya Johri},
url = {http://www.umiacs.umd.edu/~elm/projects/dia2/dia2-vast2014.pdf, Paper},
year = {2014},
date = {2014-11-13},
journal = {IEEE Transactions on Visualization & Computer Graphics},
volume = {20},
number = {12},
pages = {1823--1832},
abstract = {We present a design study of the Deep Insights Anywhere, Anytime (DIA2) platform, a web-based visual analytics system that allows program managers and academic staff at the U.S. National Science Foundation to search, view, and analyze their research funding portfolio. The goal of this system is to facilitate usersʼ understanding of both past and currently active research awards in order to make more informed decisions of their future funding. This user group is characterized by high expertise yet not necessarily high literacy in visualization and visual analytics--they are essentially \"casual experts\"--and thus require careful visual and information design, including adhering to user experience standards, providing a self-instructive interface, and progressively refining visualizations to minimize complexity. We discuss the challenges of designing a system for \"casual experts\" and highlight how we addressed this issue by modeling the organizational structure and workflows of the NSF within our system. We discuss each stage of the design process, starting with formative interviews, participatory design, prototypes, and
finally live deployments and evaluation with stakeholders.},
keywords = {}
}

@article{Madhavan2012,
title = {Portfolio Mining},
author = {Krishna Madhavan and Mihaela Vorvoreanu and Niklas Elmqvist and Aditya Johri and Naren Ramakrishnan and G. Alan Wang and Ann McKenna},
url = {https://ieeexplore.ieee.org/document/6329888, IEEE Xplore},
year = {2012},
date = {2012-01-01},
journal = {IEEE Computer},
volume = {45},
number = {10},
pages = {95--99},
abstract = {Portfolio mining facilitates the creation of actionable knowledge, catalyzes innovations, and sustains research communities.},
keywords = {}
}

@inproceedings{McGrath2012,
title = {Branch-Explore-Merge: Facilitating Real-Time Revision Control in Collaborative Visual Exploration},
author = {Will McGrath and Brian Bowman and David McCallum and Juan-David Hincapie-Ramos and Niklas Elmqvist and Pourang Irani},
url = {http://www.umiacs.umd.edu/~elm/projects/bem/bem.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the ACM Conference on Interactive Tabletops and Surfaces},
pages = {235--244},
abstract = {Collaborative work is characterized by participants seamlessly transitioning from working together (coupled) to working alone (decoupled). Groupware should therefore facilitate smoothly varying coupling throughout the entire collaborative session. Towards achieving such transitions for collaborative exploration and search, we propose a protocol based on managing revisions for each collaborator exploring a dataset. The protocol allows participants to diverge from the shared analysis path (branch), study the data independently (explore), and then contribute back their findings onto the shared display (merge). We apply this concept to collaborative search in multidimensional data, and propose an implementation where the public view is a tabletop display and the private views are embedded in handheld tablets. We then use this implementation to perform a qualitative user study involving a real estate dataset. Results show that participants leverage the BEM protocol, spend significant time using their private views (40% to 80% of total task time), and apply public view changes for consultation with collaborators.},
keywords = {}
}