(710g) Intuitive Visual Communication of Temporal Data

1. Introduction

Energy and resources are important cost factors for wastewater treatment (Hernandez-Sancho
& Sala-Garrido, 2008) and should be optimised. On a daily basis, operation
optimisation requires a sharpened awareness about process characteristics and energy
consumption of any wastewater treatment plant. However, limited thought has
been given to effective visualisation of the relevant data. In our case,
visualisation does not only refer to methods to process data such as principal component
analysis  (PCA, e.g. Maere et al.,
2012) or self-organising maps (SOM, e.g.: D?rrenmatt & Gujer, 2012) but
also to the communication of the processed data in an intuitive and relevant
matter.  For a broader and complex
indicator set such as the ones on wastewater treatment plants (WWTPs), the
actual visualisation and arrangement of the single graphical elements is a
crucial step in addressing the operator's attention.

In our contribution we want to present ideas on accurate and
intuitive visualisation of energy and process data in any facility. The
visualisation is not limited to computational and graphical issues; we also
have to handle topics such as data sources, data quality and data quantity.
With our visualisation tool we want to support the operators in optimising the
performance of WWTPs. Currently the initial version of the visualization tool is
being evaluated in one plant, i.e. WWTP Hard (Winterthur, Switzerland). A
second plant (WWTP Pfungen, Switzerland) has been selected for further testing
and to ensure general applicability of the software.

2. Data preparation

2.1
Data quality

An important
aspect of data visualisation in wastewater treatment and any other engineering practice
is that the displayed data must be of guaranteed quality in order to prevent
errors in the decision-making process. Therefore any data should already be processed
by a data quality assurance tool. This is not the topic of this paper however.

2.2
Data granularity

During development of a data
visualisation tool, several aspects of full-scale data have to be addressed.
One is that not all data are measured at the same frequency. As such, it is
very obvious that the update interval for visualisation cannot be lower than
the update interval for the data which are visualised. However a too frequent computation
may render an erroneous picture to the operator, further leading to aggressive
actions or mistrust in the visualisation tool. This applies especially to systems with long delay
between inputs (control signals) and outputs (measurements). Conversely a too low frequency is
to be bargained against a potentially slower response of the operator if important
events are missed.

3. Results & Discussion

3.1 Visual design elements

3.1.1 Colour bar

Two graphical elements help to
visualise relevant data; the "colour bar" and the "calendar view" (Wicklin &
Allison, 2009). The colour bar (c.f. Figure 3.1, b) includes two scales. One is the numeric scale
of the indicator with the online measured (M) or calculated value and corresponding
guideline (G) and ideal (I) values, if available. The second scale is the
gradient colour fill of the bar from red to yellow to green. This colour
gradient does not include additional information since the colours of the
colour bar are fixed to specific numerical values for each indicator. However,
this additional colour scale is intended to enable a faster and more intuitive
understanding of the plant's status. In addition, the colours of our colour bar
are basically matched with European Union energy label for household appliances
(European Union, 2013), which is also an official label in Switzerland and
therefore well known (c.f. Figure 3.1, a).

Each colour bar has filled
background information including a description of the calculation, used data
sources and the time of the last calculation value. If the data do not allow a
new calculation it will be indicated next to the colour bar.

3.1.2 Calendar View

The "calendar view" consists of a calendar where weekdays are arranged in columns and where each
row represents a week (c.f. Figure 3.2, c). Each day is a small box coloured
according to the characteristic day value (e.g. daily average). However also
weekly or monthly colouring is possible.
The colour scale corresponds to the one in the colour bar. If an
indicator is not calculated the day remains uncoloured. The form and
arrangement of the calendar view elements supports the operator to find weekly
or even monthly patterns within one or among several indicators. Moreover, the
calendar view offers interactive options (e.g. mouse hover effects cf. Figure
3.1 c) to understand the indicated value in relation to plant loads and special
events. In addition to that, the calendar view value will be displayed on the
corresponding colour bar (H).

3.2 Indicators

The data chosen for our
visualisation can be separated in two groups, energy
indicators and process indicators. For the energy indicators we consider
existing guidelines from the Swiss Water Association (VSA, 2008) and from the
German Association for Water, Wastewater and Waste (DWA, draft). Both
associations define energy efficiency indicators for WWTPs. These indicators
help operators with ideal and guideline values to benchmark their plants. Also
in many other industries, associations define key performance indicators allowing benchmarking the performance within
the industry (e.g. facility management cf. ISA 2011).

4. Conclusion

A new tool to visualise energy and process data is presented. It
combines two graphical elements. One to assess the current state of the plant,
one to track and compare historical data. In combination they enable the
operator to analyse the relevant indicators. The tool is currently tested on a
WWTP. The WWTP plant staff will be consulted to make further versions of the
tool more relevant and intuitive. Further roll outs to other plants are
planned. 

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