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Strategic Data Science
for Water Utilities
WORKSHOP
Dr Peter Prevos
Manager Data Science |Coliban Water
• What is Data Science?• Case Studies• Strategic Data Science• Discussion
Strategic Data ScienceProgram
leanpub.com/strategic_data_science
What is Data Science?
Data ScienceDon’t believe the Hype
Davenport, T.H., and D.J. Patil. “Data Scientist: The Sexiest Job of the 21st Century.” Harvard Business Review 90, no. 10 (2012): 70–76.
Source: Google Trends
• Cheap data collection and storage
• Increased computing power• Open source machine
learning
Data ScienceWhat’s new?
• Flooded with data• Data deluge• Data lakes• Data flows• Data pipes
Data ScienceHydroinformatics
csgsolutions.com
Elements of Data Science
Source: Drew Conway
Subject-Matter Expertise
MathematicsComputer Science
DATASCIENCE
MachineLearning
• Useful• Sound• Aesthetic
Good Data ScienceVitruvius, Roman architect and engineer
Water screw, De Architectura, book II.
Useful Data ScienceThe Knowledge – Reality feedback Loop
• Validity• Reliability• Governance• Reproducibility
Sound Data ScienceThe Science of Analysis
• Code is Poetry• Spreadsheets invite chaos
Sound Data ScienceReproducibility
• Tell a story with each graph• Two dimensions only• Colour is not decoration• Multiple graphs for levels of
detail (drill down)
Aesthetic Data ScienceRules of Thumb
Composition C, 1935 by Piet Mondrian
Aesthetic Data ScienceData-to-Pixel Ratio
Aesthetic Data Science
Aesthetic Data Science
Case Study
The Board of directors of a water utility receives a monthly report about water quality performance.
None of the members of the Board are water quality professionals.
The report is full of numbers and statistics that the responsible manager needs to explain to the Board every month.
Data Science Case Study 1Water Quality Board Report
Another section of the report contains information about customer complaints with respect to water quality. The Board often asks how the customer experience relates to the technical data in the other section of the report.
The Board has requested the data science manager to develop a new report that provides them with an easy-to-understand overview of water quality performance.
The report needs to visually combine the technical data with the customer experience information. The report should focus on the salient aspect of water quality performance to provide a strategic perspective for the Board.
Data Science Case Study 1Water Quality Board Report
Data Science Case Study 1Water Quality Board Report
Aspect Source Availability
Catchment Paper records Intermittent
Barriers SCADA Continuous
Network Laboratory Weekly
Customer Experience Complaints Daily
Regulation Correspondence Intermittent
Data Science Case StudyWater Quality Board Report
Strategic Data Science
Data Science ContinuumData Science Continuum
Data Science Workflow
Data Science ToolsCode is Poetry
Data Science Literacy
• Informed Consent• No harm in collecting• Algorithmic fairness
Data Science Ethics
Source: koeppeldirect.com
• Leadership commitment• Systematic approach• Employee competencies• Focus on creating value• Data governance• Ethics
Data Science CultureWhat's needed?
Discussion
A water utility starts a digital metering project and seeks to collect hourly meter reads from every customer. The new technology is deployed to all customers to ensure the service obtains maximum data coverage. Customers are not provided with an opportunity to opt-out of the program.
The program has been well received by the community overall. A small segment of customers opposes this technology due to perceived risks to human and environmental health caused by low-level microwave radiation. There is no scientific evidence to justify their claims. The benefits that the water utility seeks are:
• Improved customer awareness of water consumption• More accurate capital investment forecasting• Reduced leakage, both non-revenue and revenue leaks
Data Science Case Study 2The Ethics of Digital Water Metering
The employees of the water utility are excited about other benefits this data can achieve and have proposed several data science projects.
• Detecting leaks at the customer’s property • Monitoring adherence to water restrictions • Monitoring zero water consumption
Discuss this digital metering project using the three principles of data science ethics. If any of the principles reveals any potential for ethical conflicts, then propose a way to mitigate the impact:
• Informed consent • Avoiding harm in collecting data • Algorithmic fairness
Data Science Case Study 2The Ethics of Digital Water Metering
Thank you
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