0

I've a data design challenge that requires the presentation of data where the data is comparable (can be plotted or presented as a table) but who's data points are inconsistent.

Inconsistency occurs in that one data series will consist of monthly data points whereas a comparable series will be represent with weekly data points that in turn can be aggregated to provide a monthly average.

The challenge is to present the data in an accessible (comprehensible) way.

As for a little background the data is of type price / value / weight and used for financial analysis and market forecasting purposes.

Because of the financial nature examples and practices are hard to come by, I've a few ideas of how to present this type of data but would like to hear if anyone can point me in the direction of any design patterns I can base further thoughts on?

I've added this example - don't worry about the data

mockup

download bmml source – Wireframes created with Balsamiq Mockups

2
  • If you have some ideas of your own currently can you post one of these so we can get a visual idea of where you're coming from?
    – JonW
    May 11, 2012 at 10:51
  • We may be looking at his best idea for a tabular view. :-) May 11, 2012 at 16:04

1 Answer 1

1

A zoomable graph/chart is the best way I've seen to present multi-scale data over time, or to look at the same data over different time scales. Weatherspark is a good example of a zoomable chart. You can use the mousewheel to expand or shrink the time scale, and the graph dynamically adjusts how it displays the information (as an average, as a range, etc).

1
  • Thanks Myrddin, we are having to include this type of data representation and functionality based on the data we need to include in a tabular form May 11, 2012 at 14:20

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.