Welcome to Project Lintol! Here’s the lowdown on the project, how it could help you, and how you can get involved…
Project Lintol: what are we building?
We’re building an Open Data validating tool. Put simply, this is a bit like a grammar checker for Open Data (data which everyone can access, use or share). It’s designed to be used just before the point of publishing and will detect errors and mistakes in a data set; alerting the data owner and allowing them to make any crucial fixes before their data is released to the public.
The validating tool has been created for an Open Data Institute R&D project exploring how better publishing tools can improve the quality, speed and cost-effectiveness of data publishing.
Who’s funding us?
The funding is from the Open Data Institute. Innovate UK, the UK’s innovation agency, is providing £6 million over three years to the Open Data Institute, to advance knowledge and expertise in how data can shape the next generation of public and private services, and create economic growth. Some of this work will be carried out by the ODI itself, and some by external experts, as in the case of Lintol. Work on improving the conditions for data publishing is one of six projects, chosen by the ODI, in this first year of the funding. Lintol’s validating tool is a key element of this data publishing project.
Offering solutions to a timely problem…
It’s a pretty electrifying time for Open Data in the UK. An unprecedented surge in Open Data publishing is happening as both public and private sector organisations make the transformation towards data transparency. From healthcare and medicine, to the environment, economics, politics, agriculture and transport: Open Data holds within it the possibility to inspire innovation and change.
In order for Open Data to be of its utmost use to the data consuming community, it needs to be of the highest possible quality; free from errors and mistakes. Data sets which contain incorrect information can often be completely unusable. Data publishers go to great lengths to check their data manually; but this is time consuming. Despite thorough checks, inconsistencies in data are detected after the point of publishing: by then it’s too late to fix.
“Poor quality data is a serious roadblock, restricting the flow of Open Data and cutting short its potential journey”.
Martin Naughton, Lead Developer, Project Lintol.
“Creating better data quality tools not only increases trust in the data being published, it also improves the confidence organisations have in the data they publish — removing a major barrier to the publication of data, and significantly helping realise the promises of open data.”
Olivier Thereaux, Head of Technology at the Open Data Institute.
Who can benefit from using Lintol?
Basically, any public or private body involved in publishing Open Data. For example, Belfast City Council or NHS Digital both publish Open Data, as do Deutsche Bank and Arup. We carried out our own research, and realised that no two Data Publishing teams are the same. Some team members are technical, some aren’t. What’s more, there’s no one definitive publishing team structure. With this in mind, we are developing Lintol so it can be used by both technical and non-technical users, and can fit seamlessly into a team’s supply chain or sequence of publishing.
We’re hoping to help erase the “fear” described to us by Data Owners who are keen to avoid publishing flawed data.
Follow our progress, offer us your insights.
For us, it’s key that the principles of Open Data and transparency are part of Lintol’s genetic code, and we’re using a Python based open source workflow engine. To keep up to date on our progress, or ask our team members direct questions, join us on GitHub , or Twitter
