TY - GEN
T1 - HIVEBEAT - A highly interactive visualization environment for broad-scale exploratory analysis and tracing
AU - Krüger, Robert
AU - Bosch, Harald
AU - Koch, Steffen
AU - Müller, Christoph
AU - Reina, Guido
AU - Thom, Dennis
AU - Ertl, Thomas
PY - 2012
Y1 - 2012
N2 - The VAST Challenge 2012 deals with large data network analysis. The challenge scenario is centered around the computer network of the fictitious Bank of Money (BoM). BoM operates 888,977 computers which are geographically distributed on a fictitious landmass. The provided data has a hierarchical structure grouping machines in business units, facilities, machine classes and machine types. For each machine, up to 192 status logs in a two day time period were provided. These logs report on three status attributes: policy, activity and number of connections. The main task of Mini-Challenge 1 was to highlight up to five anomalies in the massive data set. We address this challenge by presenting HIVEBEAT, a highly interactive visualization environment for broad-scale exploratory analysis and tracing. It offers eight interactive views which visualize different aspects of the data, support brushing and linking and are complemented with time-dependent and sequence-based filtering. Some of these components build on ideas from earlier works [2, 3, 4]. With HIVEBEAT, we were able to identify five anomalies and justify them with plausible hypotheses.
AB - The VAST Challenge 2012 deals with large data network analysis. The challenge scenario is centered around the computer network of the fictitious Bank of Money (BoM). BoM operates 888,977 computers which are geographically distributed on a fictitious landmass. The provided data has a hierarchical structure grouping machines in business units, facilities, machine classes and machine types. For each machine, up to 192 status logs in a two day time period were provided. These logs report on three status attributes: policy, activity and number of connections. The main task of Mini-Challenge 1 was to highlight up to five anomalies in the massive data set. We address this challenge by presenting HIVEBEAT, a highly interactive visualization environment for broad-scale exploratory analysis and tracing. It offers eight interactive views which visualize different aspects of the data, support brushing and linking and are complemented with time-dependent and sequence-based filtering. Some of these components build on ideas from earlier works [2, 3, 4]. With HIVEBEAT, we were able to identify five anomalies and justify them with plausible hypotheses.
KW - H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval - Search process
KW - H.5.2 [Information Interfaces and Presentation]: User Interfaces - GUI
UR - http://www.scopus.com/inward/record.url?scp=84872948411&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872948411&partnerID=8YFLogxK
U2 - 10.1109/VAST.2012.6400518
DO - 10.1109/VAST.2012.6400518
M3 - Conference contribution
AN - SCOPUS:84872948411
SN - 9781467347532
T3 - IEEE Conference on Visual Analytics Science and Technology 2012, VAST 2012 - Proceedings
SP - 277
EP - 278
BT - IEEE Conference on Visual Analytics Science and Technology 2012, VAST 2012 - Proceedings
PB - IEEE Computer Society
T2 - 2012 IEEE Conference on Visual Analytics Science and Technology, VAST 2012
Y2 - 14 October 2012 through 19 October 2012
ER -