TY - GEN
T1 - Geo-historical context support for information foraging and sensemaking
T2 - 1st IEEE Conference on Visual Analytics Science and Technology, VAST 10
AU - Tomaszewski, Brian
AU - MacEachren, Alan M.
PY - 2010
Y1 - 2010
N2 - Information foraging and sensemaking with heterogeneous information are context-dependent activities. Thus visual analytics tools to support these activities must incorporate context. But, context is a difficult concept to define, model, and represent. Creating and representing context in support of visually-enabled reasoning about complex problems with complex information is a complementary but different challenge than that addressed in context-aware computing. In the latter, the goal is automated adaptation of the system to meet user needs for applications such as mobile location-based services where information about the location, the user, and the user goals filters what gets presented on a small mobile device. In contrast, for visual analytics-enabled information foraging and sensemaking, the user is likely to take an active role in foraging for the contextual information needed to support sensemaking in relation to some multifaceted problem. In this paper, we address the challenges of constructing and representing context within visual interfaces that support analytical reasoning in crisis management and humanitarian relief. The challenges stem from the diverse forms of information that can provide context and difficulty in defining and operationalizing context itself. Here, we pay particular attention to document foraging to support construction of the geographic and historical context within which monitoring and sensemaking can be carried out. Specifically, we present the concept of geo-historical context (GHC) and outline an empirical assessment of both the concept and its implementation in the Context Discovery Application, a web-based tool that supports document foraging and sensemaking.
AB - Information foraging and sensemaking with heterogeneous information are context-dependent activities. Thus visual analytics tools to support these activities must incorporate context. But, context is a difficult concept to define, model, and represent. Creating and representing context in support of visually-enabled reasoning about complex problems with complex information is a complementary but different challenge than that addressed in context-aware computing. In the latter, the goal is automated adaptation of the system to meet user needs for applications such as mobile location-based services where information about the location, the user, and the user goals filters what gets presented on a small mobile device. In contrast, for visual analytics-enabled information foraging and sensemaking, the user is likely to take an active role in foraging for the contextual information needed to support sensemaking in relation to some multifaceted problem. In this paper, we address the challenges of constructing and representing context within visual interfaces that support analytical reasoning in crisis management and humanitarian relief. The challenges stem from the diverse forms of information that can provide context and difficulty in defining and operationalizing context itself. Here, we pay particular attention to document foraging to support construction of the geographic and historical context within which monitoring and sensemaking can be carried out. Specifically, we present the concept of geo-historical context (GHC) and outline an empirical assessment of both the concept and its implementation in the Context Discovery Application, a web-based tool that supports document foraging and sensemaking.
UR - http://www.scopus.com/inward/record.url?scp=78650946603&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650946603&partnerID=8YFLogxK
U2 - 10.1109/VAST.2010.5652895
DO - 10.1109/VAST.2010.5652895
M3 - Conference contribution
AN - SCOPUS:78650946603
SN - 9781424494866
T3 - VAST 10 - IEEE Conference on Visual Analytics Science and Technology 2010, Proceedings
SP - 139
EP - 146
BT - VAST 10 - IEEE Conference on Visual Analytics Science and Technology 2010, Proceedings
Y2 - 24 October 2010 through 29 October 2010
ER -