GIS, Data Integration and AI chatbots to enhance public services

INNOCAP project partners organise a second virtual workshop to explore disruptive technologies that will enhance public services.


INNOCAP project partners have virtually met for the second of a series of online sessions to learn more on the possibilities that disruptive technologies can offer to support innovative public services. This second workshop, held on the 9th of May, has focused on Geographic Information Systems (GIS), Data Integration and Artificial Intelligence (AI) chatbots. Like the previous session on 'Online Collaboration and Engagement: 2D/3D + Virtual Reality (VR) and Augmented Reality (AR) guidance technologies', these series of workshops are providing an overview of the tools and their capabilities to spin a further discussion that will ultimately feed into the INNOCAP Capacity Building Programme.

Conversational Agents or Chatbots
"These agents are software applications that communicate with a human using either spoken or written natural language. These are a type of conversational agents used in a wide range of domains for better customer service", explained Agustin Garcia, from the Insight Centre for Data Analytics - University of Galway (Ireland).

Chatbots have become popular in the public service domain as they can reduce the administrative burden and allow citizens to communicate with the government in their everyday natural language. The use of AI technology enables staff to take on more value-added tasks. Agustin presented one successful example developed within another Northern Periphery and Arctic programme funded project, EMERGREEN. Produced by Derry City and Strabane District Council in Northern Ireland, 'RIA', Recycling Information Assistant, was created to reduce the number of phone call from the citizens looking for the basic information.

"How do you imagine the process of creating a chatbot?", asked Agustin to the INNOCAP partnership. He mentioned that there might be some development challenges: scarce, messy and unstructured data, information is dynamic, partners may don't have computer science background and a wide variety of end users (public services). According to him, the approach should be a user-centred design technique, agile development process, and initiated with requirements' analysis and finalised with relevant evaluation by users in the form of dedicated focus groups.

Data Integration
Agustin brought the 'Open Repair Data Platform' case to inspire project partners. This project addressed the increasing amount of waste from electrical and electronic equipment and the lack of convenient and accessible repair solutions by scaling up citizen repair initiatives through the use of digital tools. Aiming to warning the partners, he commented the challenges of data integration. For instance, not all the data available follows a standard; data lives in different places and governed by different organizations; and, data is presented and shared in different formats. Therefore, what can public institutions do to face the potential challenges? The standarization of data by harmonising the data collection efforts; promoting it as a standard available to other community repair networks; using the collected data to produce insights; and ensuring that data is structured, comparable, open, accurate and timely. 

In addition, Agustin mentioned the importance of data integration through the ETL (Extract, Transform, Load) methodology. "This is the process data engineers use to extract data from different sources, transform the data into a usable and trusted resource, and load that data into the systems end-users can access and use downstream to solve business problems", he added.

Geographic Information Systems and Artificial Intelligence
Agustin concluded the last part of the workshop showcasing real project examples that have used GIS, geospatial data collection tools and AI. Among others, he presented 'Towards a Virtual Atlas of Bee-friendly Agriculture' pilot to show INNOCAP partners some real life benefits after using disruptive technologies. "AI can help automate geospatial data creation", he said.