Introduction
BROWSER Interface
Using BROWSER
Conclusions
References

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Introduction

BROWSER was developed to provide a simple and flexible graphical means to support exploration of modelled output of time-series data. Unfortunately this feature is usually inadequate or missing in most models, many of which are still “DOS-based. It is currently compatible with fourteen different file types including output from PERFECT (Littleboy et al. 1992), IQQM (DLWC 1998), APSIM (McCown et al. 1996), and SILO (Jeffrey et al. 2001, http://www.dnr.qld.gov.au/silo) models as well as four simple user templates. Other formats can easily be accommodated for in future versions.

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Figure 1: BROWSER interface showing the charting region with "tiled-view" for exploring time-series data.

BROWSER is written in c++ for the Windows operating systems (Win95, 98, NT, 2000 and ME) using Borland’s Visual Class Library (http://www.inprise.com). Charting is undertaken using Steema’s TeeChart component (http://www.teechart.com).

3. BROWSER Interface

Commands are available to the user though toolbar buttons, popup menus and through the main application menu. Toolbars are located along the left hand side of the application window and can be hidden.

Output can be printed or exported in “Enhanced Windows Metafile” and “Bitmap” formats.
 

3.1  Database

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Figure 2: Database interface with file preview

Creating the database involves defining parent directories, which are automatically searched (including subdirectories) for compatible files. The user can modify the database search criteria to recognise particular files. These files will be assumed to be of the form of one of the four user templates.

The database can be rebuilt using the “refresh” option to locate any new files or to remove any deleted files in the database directory list. New directories can be added at any stage and particular files or subdirectories can be excluded from the search.
 

3.2  Data-series Selector

The data are grouped together under the header of their parent file type, or through a common data type (such as rainfall, runoff etc) depending on user preference.

The user is able to show/hide data-series by clicking on its name in the data-series selector. Entire groups of data can be toggled on or off. Editing data-series line properties is achieved by clicking on the line icon next to the series name.
 

3.3  Chart Output

Three main views are presented to the user: 

• a “tiled-view” (Figure 1) presents each data-series in its own separate chart;
• an “overlayed-view” (Figure 3) shows several data-series overlayed on a single chart; while
• a “stacked-view” (Figure 4) places each data-series one above another on a single chart.

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Figure 3: "Overlayed-view" with period shader visible


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Figure 4: "Stacked-view" of  interface

Zooming into and scrolling (panning) around the charts can be achieved though direct interaction between the mouse cursor and the charts:

• zooming requires tracing a rectangle onto the chart while holding down the left mouse button, and
• acrolling requires moving the mouse cursor around the chart with the right mouse button held down.

A unique feature of BROWSER is the “period-setter” tool (Figure 5) consisting of a timeline-like scrollbar allowing the user to change the viewing period, scroll through the data range or quickly jump to a particular period in the data range. This can represent a  “pseudo-animation” of chart data along the timeline. Advanced features of this tool allow precise adjustment of scrolling and zooming parameters.

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Figure 5: "Period-setter" tool in "advanced-mode"

“Double-clicking” on any chart will temporarily enlarge that chart to the full window area for closer analysis. Selecting any other series from the data-series selector or “double-clicking” the chart again will restore the view back to its previous layout.

Readability of the output is enhanced using a “period-shader” tool (Figure 6) through its ability to highlight areas of the chart background representing annual periods of interest and show the corresponding “year-label”. For example, the August to November period could be shown for each year, or a twelve-month period could be highlighted for alternate years.

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Figure 6: "Period-shader" tool showing options

Summary statistics of the time-series data including maximum, minimum, median, mean, 25th percentile and 75th percentile can be presented as a line series or a box plot (Figure 7), and can be superimposed behind its corresponding data-series (Figure 9).

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Figure 7: Summary statistics output (box-plot option) in "Tiled-view" layout

Finally, BROWSER has three options available to create new data-series from existing series:

• the “Combine Series” option allows addition/subtraction of multiple data series,
• the “Scatter Plot” (Figure 8) option creates a separate scatter plot from two data-series, and
• the “Create Cumulative” option converts single data-series into a new cumulative plot.

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Figure 8: "Scatter Plot" created from two open data-series

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4. Using BROWSER

The “tiled-view” allows quick visualisation of each data series to locate obvious abnormalities or features and aids in selecting relevant data series for further investigation.

The “overlay-view” is useful for comparing both trends and magnitudes between data series. Trends are most easily analysed using the “auto axes” option so that each series has its own separate vertical axis while remaining in the same vertical screen space.  Using the “high axes” option allows direct comparison of the magnitude of data using a single vertical axis. However, one disadvantage of this view is that the chart region tends to get a little “cluttered” when too many series are selected, especially when the “auto axes” option is used.

The “stacked-view” alleviates much of the “clutter” of the “overlay-view” while still allowing a clear comparison of trends. Comparing magnitudes is less clear however as each series is now in its own vertical screen space.

The ability to superimpose a data-series over its statistical summaries (Figure 9) provides an efficient method for identifying abnormalities or outliers in an individual data-series. Combined with the advanced navigation features of BROWSER, the user can quickly scan through a time-series investigating how local events compare to the historical measures.

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Figure 9: Close-up of a data-series superimposed over a monthly-box plot statistic

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5. Conclusions

It is planned that BROWSER will be readily available as a gesture to encourage enlightenment and transparency in the modelling world.

6. References

NSW Department of Land and Water Conservation (DLWC), Integrated Quantity Quality Model Reference Manual, 1998.

McCown, R.L., Hammer, G.L.  Hargreaves, J.N.G.,  Holzworth, D. and Freebairn,  D.M., APSIM:  A novel software system for model development, model testing, and simulation in agricultural systems research. Agric. Systems. 50:255-71, 1996.

Jeffrey, S.J., Carter, J.O., Moodie, K.B., Beswick, A.R. (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data", Vol 16/4, pp 309-330, 2001 Environmental Modelling and Software. (Scheduled publication date May 2001)