Driving Government Efficiency with Improved Location-based Data

Posted - Matt Beare: For those who may have recently read John Hartshorn’s Blog, will know that I will be in Edinburgh at the end of the month, looking forward to participating in and learning from this year’s INSPIRE Conference. For my part, I will be presenting (Thu 30 Jun @ 16:00) on my experiences of how and where INSPIRE can help drive government efficiency through the improved use of location-based data. These efficiencies will enable public sector organisations to readily share good information, make better decisions, plan more effectively and ultimately deliver better services, to us, the citizen.

I will have this in poster form too, but with a bit of a twist to your typical poster, so why not come along to the welcome drinks and poster session to find out just what that entails (Tue 28 Jun @ 18:00).

I’ll be drawing on experiences from two recent projects to illustrate my point. The first has provided me with the perfect opportunity over the past two and a half years to really understand what INSPIRE is all about and what is required to make it happen. This is the ESDIN project (European Spatial Data Infrastructure with a best practice Network), where 1Spatial worked as part of a large consortium of National Mapping and Cadastral Agencies, researchers, consultants and technology providers, smartly led by EuroGeographics.  My specific focus was to assist in activities around data quality, edge matching, schema transformation and generalization. Therefore, I was delighted to read the comments from the Commission’s final review report on ESDIN, which included:

“The project offers valuable … applications for generalization and schema transformation and, most importantly, effective data quality measures together with tools for testing the conformity to the INSPIRE technical requirements and to the ESDIN specifications. This will gradually allow NMCAs to be able to provide stable geodata and differential updates with a clear identification of the modified features.”

 “ESDIN is one of the first projects that also provide appropriate testing tools that can check the conformity to the ESDIN data specifications as well as conformity to INSPIRE. These results should be forwarded to the INSPIRE community.”

The second project and the main focus of my presentation is one undertaken by 1Spatial last year with Staffordshire County Council (SCC). Seeking to create a safer environment for vulnerable adults, SCC and the local Fire Authority wanted to perform free safety inspections to assess the risk and take remedial action where necessary. But without the appropriate spatial data to support the activity the objective looked unachievable.

They turned to us to help validate and cleanse their client information database and geo-code the data to enable its use in GIS applications to assist in locating the vulnerable and planning visits. Utilising available authoritative address information the project has proven to be a great success, minimising costs within SCC, enabling the Fire Authority to perform the inspections and consequently the exercise has saved lives! What better incentive to effectively share good quality location-based data do you need than that – invaluable. 

Welcome to fabulous Edinburgh…

Posted - John Hartshorn: It's a rare event when I'm allowed to blog (this is the first time), so I'd best make good use of the liberty I've been granted. I'm Edinburgh-bound at the end of June, specifically for the INSPIRE conference, so it seemed like a good time to squeak some thoughts and open the floodgates to the online justice dispensed by those who know more than me. Nothing like the sound of the shallow jumping in at the deep, eh?

I'll be honest from the start – I've slunk around in the shadows of INSPIRE so far, desperately trying to avoid admitting that I can't quite get my head around what the problem seems to be, despite everyone talking about it. It all sounds very complicated.

The problem, as I see it, is that some of you out there are obliged (or at least to contribute to a data supply chain that is obliged) to take a whole load of data, check it, validate it, transform it across to a new schema and, finally, publish it in a new format. Of course, those who live and breathe INSPIRE will scream that I've simplified the problem a little. Don't be offended – isn't that really what the problem is, in layman's terms?

I thought we'd cracked it, to be honest. If you've ever had much to do with my colleagues here at 1Spatial, you'll know that they spend all of their time solving data problems - and they make it seem easy. They make sure that data can be trusted before it's used, propagated, or shared - to them, it's bread and butter stuff. It's the focus of our business and why we exist.

And that's probably why we were in a consortium project that demonstrated automated schema transformation network services to the JRC. You can read all about it here, but if you want an easier-going overview, check out the video we made.

So what treats does 1Spatial have for you at the Edinburgh conference?

My colleague Matt Beare is going to be presenting on Driving Government Efficiency with Improved Location-based Data - and that's what it's all about, right? Trusting the data which we are using to make critical decisions, and making sure that what is published and shared can be trusted, and demonstrably so. In our day-to-day jobs we are all accountable for our decisions, aren't we? If we trust our data by understanding it better, our decisions are surely better-informed and supported by evidence? This is even more the case if we can then improve data by consistently testing its conformance to strict business-rules. Better-informed decisions lead to more efficient use of resources and, ultimately, either lower our operational costs or improve the services we are providing to the public, our customers, etc.

Anyway, Matt is going to talk about a project he's just completed as part of ESDIN in which he and his team developed procedures and guidelines for data quality evaluation, edge matching across boundaries and data sets, and model generalisation. As part of this, he and the team developed a pilot service to show that automation of data quality assessment and improvement can bring real efficiencies, in this case, in the production of INSPIRE compliant data products.

So with us having successfully ticked off the two projects for JRC and ESDIN, we already have proven solutions to tackle some of the issues around INSPIRE. We can read the schema definitions, we can import data from multiple sources and formats, we can check its readiness and quality and we can then automate the whole process right up to the transformation of the data to the right schemas and the subsequent publishing of it in the right format. It's just another data problem like all the others - the commonality being in the automation and repeatable tasks of gathering up data, validating its readiness and quality, transforming it and publishing it. We already had the tools to do it - it really is just another data problem to solve. Which is what we do.

That's why I believe we've cracked it.

Anyway, I'll be in Edinburgh for at least some of the week of the conference and I do hope you get a chance to come along, hear about Matt's work and maybe even say hello to me. In the meantime to read more about our involvement with INSPIRE click here.

The critical question remains, though - will they let me blog again?

Here come the DIP's

Posted - Bob Chell: Three GeoDATA events down (London, Birmingham and Leeds) - review and retrospective time.

To begin with, I am presenting a subject that I am passionate about, but one that, to a certain degree, people have always been happy to ignore or pretend is not there - Data Quality. However, the reaction during my presentation, and more importantly afterwards through conversations with delegates, shows that in the spatial world this is right at the top of their to do lists.

In the end, two of the most important assets to any organisation are its staff and its data. And as well as the focus on efficiency, people are being encouraged to make their data publically available. This is strategic goal. But with it, comes a set of responsibilities, because people will be accountable for that data. To become more efficient, organisations are also looking to consolidate systems and streamline how they work.

The nature of the spatial data that I deal with joins up many different types of systems, managed by and for all sorts of personas. This means that most of my clients work in data-intensive businesses. More and more, spatial data accuracy, spatial data cleansing and spatial data quality health checks are now being mentioned in publications that are not focussed on users of geospatial technology. Take a look in any 2011 issue of Government Computing and you'll see this. Businesses are making direct relations from poor quality spatial data to missing revenue, or lost efficiency - missing or inaccurate address records resulting in lost income tax or missing out on new home bonuses.

As soon as people have made this connection between the data and its business value, they start to see some tangible quick wins. Typically, an organisation might have 100,000 address records in a single system. When you go through the numbers, even if that organisation can make data quality improvements of a small 2 or 3 per cent, it still adds up to 1000s of improved records, which you can put a financial value on. It then becomes possible to decide if the benefit of improving the data outweighs the cost of the improvement process itself.

However, the data-intensive business of the spatial world means that without some form of automation, it could literally take years for businesses to get an understanding of the quality of their data. Without being lean and efficient by automating these tasks, the business case for improving the data is not always there.
I tried to make the GeoDATA events educational, and took the opportunity to talk people through getting organised and setting up a Data Quality Process. It's a data-driven process, rather than product-driven. It shares key concepts with many other Data Quality Processes, but that is because there are key things you must do to ensure everything works efficiently. We encourage people to take a positive approach to this.

The GeoDATA Events continue in Dublin and Edinburgh, so now I know that people like what we are saying at 1Spatial, I need to get our marketing team to print out some more A5 flyers that have nothing more than the Data Quality Improvement Cycle on it. People can really relate to it, and it offers some real genuine guidance on how people can start their own programmes of work.