Data Aggregation

[jhellier]

Large data sets are a challenge. What can we do to intelligently aggregate data to only show what the user needs while still giving hints or cues as to what lies underneath.

Possible Outcomes:

• Discussion of Hex binning for data aggregation
• Novel approaches to hide and show the extended data linkages (graph and force layouts)
• Using a data store to swap out different subsets of a large data set.
• Performance concerns.

[georules]

+1

[enjalot]

+1
I've also been using crossfilter to prototype "mid-sized" datasets in the browser to determine the actual combination of filtering + aggregation I want from a database

[jonathandinu]

+1 Vadim gave a great presentation on this topic and has some great open libraries to integrate with databases

[nydame]

+1

[jhellier]

Another aspect to explore with this is the visual aggregation and disaggregation. Looking for novel approaches to visually showing elements that represent collections of various complexity, breadth and depth.

[curran]

+1

This could be a broader discussion of data reduction and interactions with "Big Data" systems like Hadoop and Spark, using techniques like sampling, filtering, and aggregation. This paper has a great overview of data reduction methods: imMens: Real-time Visual Querying of Big Data

[chabb]

+1