Seven public servants’ ideas picked up by Canadian Data Challenge
Launched earlier this year, the Public Service Data Challenge aims to identify and develop public servants’ ideas on how to make better use of data in government – here, we present the longlisted ideas that will go through to the semi-final
Seven ideas put forward by Canadian public servants are to be researched and developed under the Public Service Data Challenge, before the project teams pitch their plans to a panel of top data leaders at a ‘Dragon’s Den’-style semi-final in January. The seven ideas longlisted for development cover policy fields from border security to waterways pollution, and from public procurements to support for remote communities.
“There is so much innovation, enthusiasm, and talent in the Canadian public service and that was clearly demonstrated in the volume and quality of the ideas submitted to the Public Service Data Challenge,” commented Catherine Luelo, the Government of Canada CIO and a ‘champion’ of the Challenge.
“It is encouraging to see that the long-listed ideas submitted come from staff in such varied occupational groups, seniorities, and organisations – from a data scientist to a grants manager; a program assistant to a senior policy officer; and from the Privy Council Office to Prairies Economic Development Canada,” she continued. “I want personally to thank everyone for their ideas; we will review and publish every one of them. I look forward to seeing what will be presented at the semi-final in January!”
Data accelerator
Under the Data Challenge, federal public servants were invited in April 2022 to suggest ways in which the government could make better use of data, or to volunteer to join the project teams charged with producing business cases and facing the judging panel. Some 120 ideas were received; after the Final in April 2023, the best will receive additional funding and support to carry them forwards towards implementation.
Run by Natural Resources Canada, Statistics Canada, Global Government Forum and Microsoft, the Challenge was launched in February by Canada’s chief statistician Anil Arora. Participating staff would get “the opportunity to collaborate in interdisciplinary, cross-departmental teams” as they researched their ideas, he explained, adding that the program aims to “improve policymaking and power the green agenda, drive organisational efficiency, and help us better serve Canadians”.
After the final, the best will receive extra resources and assistance to support further development or delivery. But the Challenge provides all the longlisted ideas with six months of research work by dedicated teams, plus technical advice and the backing of top public servants – building evidence-based business cases designed to attract investment and engagement from departments. As Catherine Luelo explained earlier this year, the format is designed to get “all the right sponsors around the Data Challenge table, with both the desire and the authority to get things rolling.”
Lisa Carroll, public sector lead at Microsoft, emphasised the quality of the ideas received from public servants. “Working as a judge for the Public Service Data Challenge, it was immediately clear that we’d face some very difficult decisions in choosing just seven projects,” she told GGF. “The submissions demonstrated fantastic innovation and passion across the Government of Canada departmental teams, and emphasized the enormous breadth of opportunities to make use of data to improve services to citizens. I’d like to thank all those who sent in an idea or volunteered to join a development team – your commitment and innovation is commendable! We at Microsoft very much look forward to assisting the teams as they begin work to scope their ideas, gather evidence and develop their projects.”
The seven longlisted ideas cover a wide range of topics, techniques and technologies. Some deploy AI to, for example, locate concentrations of seaborne plastic waste, improve advice to farmers, or guide food safety inspections on imported goods. Some combine datasets – strengthening transparency, research and efficiency in procurements and consultations, for example, or improving assessments of remote communities’ needs. Some – like the food inspections idea, and a plan to reduce waterways pollution – comb through historical data to improve public services’ accuracy and effectiveness. All seven are briefly outlined below.
Use satellite and sonar data to locate plastic waste at sea
Plastic waste and discarded ‘ghost’ fishing gear presents a serious threat to the health of our oceans – harming sea life, damaging delicate environments, and ultimately entering the human food chain. The Government of Canada is investing in clean-up operations, but these are extremely costly: an AI-assisted platform would help target this work, much improving its efficiency and effectiveness. Drawing on satellite imagery and sonar data, the tool would create heat maps of plastic and ‘ghost gear’ densities; it could also be further developed to track other pollution sources such as oil spills.
Build a procurements visualisation tool
Under its ‘proactive disclosure’ rules, the government publishes large amounts of data on federal spending; but the current interface is not intuitive and has limited functionality. An interactive data visualisation tool drawing on contracts, grants and outcomes data would much improve its value to users, allowing them to compare datasets and view the data by – for example – program type, area of operations or correlation with improved outcomes. A secure area of the site could enable public servants to share information, advice and contact details, improving procurement operations across government.
Apply machine learning to guide imports checks
Ensuring that Canadians’ food supplies are safe and legal, the Canadian Food Inspection Agency carries out checks on imported goods – but how to decide which consignments to inspect? Staff currently scroll through long lists of shipments, using their experience to make judgements; but a machine learning tool could much improve the efficiency of this process. Fed data on which shipments have been inspected in the past, it could pull similar imports from the list in moments; and given information on where checks have revealed something amiss, it could better target inspections – averting the risk that non-compliant foods reach Canadian citizens, while strengthening deterrence. The tool could also be reconfigured for use in other compliance and enforcement services across government.
Create a needs analysis tool for remote communities
Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) offers a range of support programs for indigenous and isolated communities, seeking to allocate funds in ways that are transparent, impactful and equitable. These decisions could be improved by the development of a community needs index, presenting data on topics such as a community’s purchasing power, remoteness, social capital and vulnerability to climate change. And such an index would be valuable to actors across government, informing policymaking and service delivery in fields such as economic development, infrastructure provision and healthcare.
Pool consultation responses in a data hub
Every year, departments spend millions of dollars carrying out consultations. If the results could be pooled in a data hub, we would quickly build up a huge dataset covering a wide range of topics – providing researchers with a broad and detailed picture of Canadians’ interests, situations and needs, and thus improving decision-making in policymaking and service delivery. Creating a hub could also assist departments to coordinate or merge their consultations, reducing duplication and addressing ‘consultation fatigue’.
Use AI to improve advice to agricultural sector
Through its AgPal website, Agriculture and Agri-Food Canada provides information on thousands of federal, provincial and territorial programs and services for farmers and others involved in agriculture and food production. Currently, users must search by selecting categories from various lists; but such systems often struggle to meet people’s needs, omitting appropriate schemes while suggesting irrelevant ones. Today’s AI natural language processing technologies could transform this search function, allowing users to ask questions and providing far more accurate and personalised responses. An AI-powered AgPal search function could thus help ensure that public funds reach their intended recipients, improving the targeting of services and the support offered to businesses.
Develop a predictive tool to reduce fertiliser run-off
When heavy rain is forecast, farmers in sensitive areas are asked not to apply fertilisers – which, carried into streams and rivers, can reduce oxygen levels and choke up waterways. This guidance is important, but it is a blunt instrument: farmers are dependent on public forecasts, and the advice takes no account of local geography or farming practices. Bringing together records on precipitation and water pollution, we could analyse how past rainfall has impacted water quality across the country. Then, linking this information to new weather forecasts, we could generate far more granular, accurate predictions of the local pollution risk – averting both pollution, and the issuing of alerts when the risk is low.
For more information on the Public Service Data Challenge, see our dedicated website
About Matt Ross
Matt is Global Government Forum's Contributing Editor, providing direction and support on topics, products and audience interests across GGF’s editorial, events and research operations. He has been a journalist and editor since 1995, beginning in motoring and travel journalism – and combining the two in a 30-month, 30-country 4x4 expedition funded by magazine photo-journalism. Between 2002 and 2008 he was Features Editor of Haymarket news magazine Regeneration & Renewal, covering urban regeneration, economic growth and community development; and from 2008 to 2014 he was the Editor of UK magazine and website Civil Service World, then Editorial Director for Public Sector – both at political publishing house Dods. He has also worked as Director of Communications at think tank the Institute for Government.
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