The document discusses InsightDX, an API that aggregates and filters open environmental datasets according to location, making the data easier to use. It solves the problems that environmental data is scattered across different sources and formats, and tying multiple datasets to a single location is challenging. InsightDX aims to make open data more meaningful and accessible for service creators and data users, allowing them to focus on creating valuable tools and services rather than struggling to find and use relevant datasets. The prototype and business model are being validated with potential partners, customers and early adopters working with open environmental data.

1. Yasemin Sertoglu
Cisem Kula
Serbulent Sertoglu

2. Service creators
Hard to find & use relevant environmental data:
• Scattered, different formats, different qualities.
• Data is classified according to subject, not
location.
• Tying multiple datasets to a single location is a challenge.
• Hence, # of datasets used in a project tends to be limited.
Data publishers & Platform owners
# of people and businesses using the data they provide is limited.
The Problem

3. The Solution
 InsightDX is an API that crawls, aggregates and filters datasets on a
platform according the service’s criteria.
 Makes open environmental data more meaningful and easier to use.
 Service creators don’t have to struggle with finding and using datasets.
 They focus on creating stuff that matters for people and environment.
 More people can use open data to create value.

4. The Prototype

5. Customer Segments
 Data publishers
 Owners of platforms that host or signpost datasets
 People & businesses that create services using open data
Early Adopters
 People currently working with open environmental data ARE early
adopters.

6. Validation
 EdX, Data.gov.uk, Environment Agency
 Problem validated
 Solution approved
 Focus on the quality of service & data
 Potential partners: Validated
 Potential clients: Needs to be validated (Budget!)
 Service creators: 7 teams interviewed:
 Problem validation: 7/7
 Solution validation: 5/7 (5 teams use location-based data)
 Focus on the quality and reliability of data
 Preference for volume-based payment

7. Monetisation & Value
 Service creators
 Data publishers
 Platform owners
 Subscription
 Volume-based payment

8. Partners / channels / next steps
 Platform owners & data publishers.
 Open data communities and organizations
 Events (sponsoring?)
This is how we access early adopters. We will learn together, iterate and
expand from there.

9. The Datasets Used
 Environment Agency
• Risk of flooding from rivers and sea: postcode in areas of risk
• Environmental pollution incidents
 Data.gov.uk
• Noise exposure data: England
• Health and safety statistics

10. Thank you
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