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ToolDescriptionPositive pointsWhat is missingReference




InfozoomThis is a startup partially located in Fraunhofer premises.Can load very large data and do basic analyticsStream data visualization

KibanaBy elastic search

ManY Eye

  Collaborarive visualization tool over the web (Asynchronous, Distributed)
Asynchronous distributed

  1. Annotation ,Feedback, Mashup
  2. Bookmark visualizations, annotate within bookmarks, Commenting
  3. Rating Data and visualization

Isenberg, P., Elmqvist, N., Scholtz, J., Cernea, D., Ma, K.-L., & Hagen, H. (n.d.). Collaborative visualization: Definition, challenges, and research agenda.  (2011)
Web based CollaboratoryData warehouse

Subramanian S, Malan GR, Shim HS, Lee JH, Knoop P, Weymouth dTE, Jahanian F and Prakash A. Software architec- ture for the UARC web-based collaboratory. IEEE Internet Comput 1999; 3(2): 46–54.

Kilman DG and Forslund DW. An international collaboratory based on virtual patient records. Commun ACM 1997; 40(8): 110–117.
Particle PhysicsData Grid Collaboratory Pilot

US Department of Energy CollaboratoriesParticle physics data grid collaboratory pilot.Available from: http://www.doecollabora- (Last Accessed June 2011).
Earth System Grid

Bernholdt D, Bharathi S, Brown D, Chanchio K, Chen M, Chervenak A, Cinquini L, Drach B, Foster I, Fox P, Garcia J, Kesselman C, Markel R, MiddletonD, NefedovaV, Pouchard L, Shoshani A, Sim A, StrandGand WilliamsD. The earth system grid: Supporting the next generation of climate modeling research. Proc IEEE 2005; 93(3): 485–495.
NAtional Fusion Collaboratory

SchisselDP, Burruss JR, Finkelstein A, Flanagan SM, Foster IT, Fredian TW, Greenwald MJ, Johnson CR, Keahey K, Klasky SA, Li K, McCune DC, Papka M, Peng Q, Randerson L, Sanderson A, Stillerman J, Stevens R, Thompson MR and Wallace G. Building the US national fusion grid: Results from the national fusion collaboratory project. Fusion Eng Des 2004; 71(1-4): 245–250.

Collaboratory for Multi scale chemical Sience 

Sandia National Laboratories. Collaboratory for multi-scale chemical science. Available from: (Last Accessed 2010)
Time Searcher 1-3Good candidate for time series searching* TimeSearcher allows users to specify different regions (Motif discovery ) of interest from a query time series, rather than feeding the entire query for matching.User selected patterns are automatically grouped together. * It provides an extended version of timeboxes, variable time timeboxes. It can be used to identify items in a data set that have a values in a given range for an interval consisting of a number of consecutive measurements. * Ability to define a query that is somehow a "reciprocal" of a previously defined query. * It not only supports conjunctive Queries (value range for all) but also Disjunctive ("anyof") Queries interpretation: timeboxes that find items that have a value in the range for at least one time point during the interval. * It supports two different strategies for normalizing data. a) Extreme Normalized b) Deviation Normalized* users still need to specify the query regions in order to find similar patterns (Motif discovery). * Users may need to have some prior knowledge about the datasets and need to have a general idea of what is interesting. * It suffers from its limited scalability, which restricts its utility to smaller datasets, and is impractical for the task at hand.