linkedlocalgovAs often is the way, events have conspired to prevent me from producing this third and final part in this How & Why of Local Government Spending Data as soon as I wanted.  So my apologies to those eagerly awaiting this latest.

To quickly recap, in Part 1 I addressed issues around why pick on spending data as a start point for Linked Data in Local Government, and indeed why go for Linked Data at all.  In Part 2, I used some of the excellent work that Stuart Harrison at Lichfield District Council has done in this area, as examples to demonstrate how you can publish spending data as Linked Data, for both human and programmatic consumption.

I am presuming that you are still with me on my basic assumptions “…publishing this [local government spending] data is a good thing” and “Publishing Local Authority data, such as local spending data, as ‘Linked Data’ is also a good thing”, plus the technique of using URIs to name things in a globally unique way (that also provides a link to more information) is not providing you with mental indigestion.  So, I now want to move on to some of the issues that are causing debate in the community which come under the headings of ontologies  identifiers.


An ontology, according to Wikipeda, is a formal representation of knowledge as a set of concepts within a domain  –  an ontology provides a shared vocabulary, which can be used to model a domain – that is, the type of objects and/or concepts that exist, and their properties and relations.  So in our quest to publish spending data what ontology should we use?  The Payments Ontology, with the accompanying guide to it’s application, is what is needed.  Using it, it becomes possible to describe individual payments, or expenditure lines, and their relationship between the authority (payment:payer) the supplier (payment:payee) category (payment:expenditureCategory) etc.  The next question is how do you identify the things that you are relating together using this ontology.

Lets take this one step at a time:

  1. Give the expenditure line, or individual payment, an identifier possibly generated by our accounts system. eg. 8605670.
  2. Make that identifier unique to our local authority by prefixing it with our internet domain name. eg. – note the prefix of ‘http://’.  This enables anyone wanting detail about this item to follow the link to our site to get the information.
  3. Associate a payer with the payment with an RDF statement (or triple) using the Payments Ontology:
    payment:payer .

    Note I am using an identifier for the payer that is published by  That is so that everyone else will unambiguously understand which authority is the one responsible for the payment.

  4. Follow the same approach for associating the payee
    payment:payee .
  5. And then repeat the process for categorisation, payment value etc.

This immediately throws up a couple of questions, such as why use a locally defined identifier for the payee – surely there is an identifier I can use that other will recognise, such as company or VAT number!  – there are, but as of the moment there are no established sets of URI identifiers for these. are doing some excellent work in this area, but Companies House, the logical choice for publishing such identifiers, have yet to do so.  Pragmatically it is probably a good idea to have a local identifier anyway and then associate it with another publicly recognised identifier:
owl:sameAs .


A_Colorful_Cartoon_Chicken_Laying_a_Golden_Egg_Royalty_Free_Clipart_Picture_100705-004451-507053 Because this is all very new and still emerging, we now find ourselves in a bit of a chicken-or-egg situation.   I presume that most authorities have not built a mini spending website, like Lichfield District Council has, to serve up details when someone follows a link like this: 

You could still use such an identifier using your authority domain, and plan to back it up later with a web service to provide more information later.  Or you could let someone else, who takes a copy of your raw data, do it for you as OpenlyLocal might: or maybe how the project we are working on with LGID might:  If the open flexible world of Linked Data it doesn’t matter too much which domain an identifier is published from, or for that matter how many [related] identifiers are used for the same thing.

It does matter however, for those looking to the identifying URI for some idea of authority.  As I say above, technically it doesn’t matter who’s domain the identifier comes from, but I believe it would be better overall if it came from the authority who’s payment it is identifying.  Which puts us back in the chicken-or-egg situation as to resolving the URI to serve up more information.   The joy of Linked Data is that, provided aggregators consider the possibility of being able to identify source authorities data accurately when they encode it, it should be possible to automatically retrofit  links between URIs at a later date.

In summary over this series of posts we are seeing a technology which, although it has obvious benefits, is still early on the development curve; being applied to a process which is also new and scary for many.  An ideal breading ground for cries of pain, assertions of ‘it doesn’t work’ or ‘not worth bothering’, yet with the potential to provide a powerful foundation for a future open, accessible, and beneficial to authorities, government, citizens, and UK Plc data rich environment.  Yes it is worth bothering, just don’t expect benefits on day, or even month, one.

This post was also published on the Nodalities Blog


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linkedlocalgovI started the previous post in this mini-series with an assumption – ..working on the assumption that publishing this [local government spending] data is a good thing. That post attracted several comments, fortunately none challenging the assumption.   So learning from that experience I am going to start with another assumption in this post.  Publishing Local Authority data, such as local spending data, as ‘Linked Data’ is also a good thing.  Those new to this mini-series, check back to the previous post for my reasoning behind the assertion.

In this post I am going to be concentrating more on the How than the Why Bother.

homeTo help with this I am going to use, some of the excellent work that Stuart Harrison at Lichfield District Council has done in this area, as examples.  Take a look at the spending data part of their site:   On the surface navigating your way around the site looking at council spend by type, subject, month, and supplier is the kind of experience a user would expect. Great for a website displaying information about a single council.

However, it is more than a web site.  Inspection of the Download data tab shows that you can get your hands on the source data in csv format.  Here is one line, representing a line of expenditure, from that data:

“”,”Lichfield District Council”,”2010-04-06″,”7747″,”″,”120.00″,”BRISTOW & SUTOR”,”401″,”Revenue Collection”,”Supplies & Services”,”Bailiff Fees”,””

… which represents the data displayed on this human readable page:

Lichfield District Council Spending Data - Details of payment number 8605670
Looking through the csv, you can pick out the strings of characters for information such as the date, supplier name, department name etc.  In addition you can pick out a couple of URIs:

Linked Data for Lichfield District Council %007C In the context of csv, that’s all these URIs are, identifiers.  However because they are http URIs you can click through to the address to get more information.  If you do that with your web browser you get a human readable representation of the data.  These sites also provide access to the same data, formatted in RDF, for use by developers.

Source of You can see that data by adding ‘.rdf’ to the end of the address, thus: and then selecting the ‘view source’ option of your browser for the page of gobbledegook that you get back.

Inspecting the RDF, you will see that most things, except descriptive labels and financial values, are are now identified as URIs such as and  Again if you follow those links, you will get a human readable representation of that resource, and the RDF behind it by adding a ‘.rdf’ suffix.

The eagle-eyed, inspecting the RDF-XML for Lichfield payment number 8605670, will have noticed a couple of things.  Firstly, a liberal sprinkling of elements with names like payment:expenditureCategory or payment:payment. These come from the Payments Ontology as published on as the recommended way of encoding spending, and other payment associated data, in RDF.

Secondly, you may have spotted that there is no date, or supplier name or identifier.  That is because those pieces of information are attributes associated with a payment – invoice number 7747 in this case.

BBC - Wildlife Finder - Whooper swan facts, pictures & stunning videos Zooming out from the data for a moment, and looking at the human readable form, you will see that most things, like spend type, invoice number, supplier name, are clickable links, which take you through to relevant information about those things – address details & payments for a supplier, all payments for a category etc.  This intuitive natural navigation style often comes as a positive consequence of thinking about data as a set of linked resources instead of the traditional rows & columns that we are used to.  Another great example of this effect can be found on a site such as the BBC Wildlife Finder.  That is not to say that you could not have created such a site without even considering Linked Data, of course you could.  However, data modelled as a set of linked resources almost self-describes the ideal navigation paths for a user interface to display it to a human.

The Linked Data practice of modelling data, such as spending data, as a set of linked resources and identifying those resources with URIs [which if looked up will provide information about that resource] is equally applicable to those outside of an individual authority.  By being able to consume that data, whilst understanding the relationships within it and having confidence in the authority and persistence of the identifiers within it, a developer can approach the task of aggregating, comparing, and using that data in their applications more easily.

So, how do I (as a local authority) get my data from its raw flat csv format, in to RDF with suitable URIs and produce a site like Lichfield’s?  The simple answer is that you may not have to – others may help you do some, if not all, of it.   With help from organisations such as esd-toolkit, OpenlyLocal, SpotlightOnSpend, and with projects such as the xSpend project we are working on with LGID, many of the conversion [from csv], data formatting processes, and aggregation are being addressed – maybe not as quickly or completely as we would like, but they are.  As to a human readable web view of your data, you may be able to copy Stuart by taking up the offer of a free Talis Platform Store and then running your own web server with his code that he hopes to share as open source.  Alternatively it might be worth waiting for others to aggregate your data and provide a way for your citizens to view your data.

As easy as that then! – Well not quite, there are some issues about URI naming and creation, and how you bring the data together that still do need addressing by those engaged in this.  But that is for Part 3….

This post was also published on the Nodalities Blog
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linkedlocalgovNational Government instructing the 300+ UK Local Authorities to publish “New items of local government spending over £500 to be published on a council-by-council basis from January 2011” has had the proponents of both open, and closed, data excited over the last few months.  For this mini series of posts I am working on the assumption that publishing this data is a good thing, because I want to move on and assert that [when publishing] one format/method to make this data available should be Linked Data.

This immediately brings me to the Why Bother? bit. This itself breaks in to two connected questions – Why bother publishing any local authority data as Linked Data? and Why bother using the, unexciting simplistic, spending data as a a place to start?

I believe that spending data is a great place to start, both for publishing local government data and for making such data linked.  Someone at national level was quite astute choosing spending as a starting point.  To comply with the instruction all an authority has to do is produce a file containing five basic elements for each payment transaction: An Id, a date, a category,  a payee, and an amount.  At a very basic level it is very easy to measure if an authority has done that or not.

Guidance from expands on this a little by mandating the following:

Body This should be the URI that represents (or more properly ‘identifies’ – see below) the local authority at
Date Should ideally be the payment date as recorded in purchase or general ledger
Transaction number To identify within authority’s system, for future reference
Amount In Sterling recorded in finance system
Supplier Details Name and individual authority id for supplier plus where possible Companies House, Charity Registration, or other recognised identifier
Expense Area The part of the authority that spent the amount
Service Categorization

Depending on the accounts system this may be easy or quite difficult. There are two candidates for categorization – CIPFA’s BVACOP classification and the Proclass procurement classification system.

… a little more onerous, possibly around the areas of identifying company numbers and Service Categorization, but not much room for discussion/interpretation.

As to the file formats to publish data, the same advice mandates: The files are to be published in CSV file format – supplemented by – Authorities may wish to publish the data in additional formats as well as the CSV files (e.g. linked data, XML, or PDFs for casual browsers). There is no reason why they should not do this, but this is not a substitute for the CSV files.

So fairy clear, and measurable, then. You either have published your required basic elements of data in a CSV format file, or you have not.  Couple this with the political ambitions and drive behind the Government’s Transparency Agenda, and local authorities will have difficulty in not delivering this.  Although some are being a bit tardy and others seem reticent to publish in formats other than pdf.

OK so why bother with applying Linked Data techniques to this [boring] spending data?  Well, precisely because it is simple data, it is comparatively easy to do, and because everybody is publishing this data the benefits of linking should soon become apparent.   Linked Data is all about identifying things and concepts, giving them a globally addressable identifiers (URIs) and then describing the relationships between them.

For those new to Linked Data, the use of URIs as identifiers often causes confusion.   A URI, such as, is a string of characters that is as much an identifier as the payroll number on your pay-check, or a barcode on a can of beans.  It has couple of attributes that make it different from traditional identifiers.  Firstly, the first part of it is created from the Internet domain name of the organisation that publish the identifier.  This means that it can be globally unique. Theoretically you could have the same payroll number as the the barcode number on my can of beans – adding the domain avoids any possibility of confusion.  Secondly, because the domain is prefixed by http:// it gives the publisher the ability to provide information about the thing identified, using well established web technologies.  In this particular example, is the identifier for Birmingham City Council, if you click on it [using it as an internet address] will supply you information about it – name, location, type of authority etc.

Following this approach, creating URI identifiers for suppliers, categories, and individual payments and defining the relationships between them using the Payments Ontology (more on this when I come on to the How)  leads to a Linked Data representation of the data.  In technical terms a comparatively easy step using scripts etc.

By publishing Linked Spending Data and loading it in to a Linked Data store, as Lichfield DC have done, it becomes possible to query it, to identifies things like all payments for a supplier; or suppliers for a category, etc.

If you then load data for several authorities in to an aggregate store, as we are doing in partnership with LGID, those queries can identify patterns or comparisons across authorities.  Which brings me to ….

linkeddata_blue Why bother publishing any local authority data as Linked Data?  Publishing as Linked Data enables an authority’s data to be meshed with data from other authorities and other sources such as national government.  For example, the data held at includes which county an authority is located within.  By using that data as part of a query, it would for instance be possible to identify the total spend, by category, for all authorities in a county such as the West Midlands.

As more authority data sets are published, sharing the same identifiers for authority category etc., they will naturally link together, enabling the natural navigation of the information between council departments, services, costs, suppliers, etc.  Once this step has been taken and the dust settles a bit, this foundation of linked data should become an open data  platform for innovating development and the publishing of other data that will link in with this basic but important financial data.

There are however some more technical issues, URI naming, aggregation, etc.,  to be overcome or at least addressed in the short term to get us to that foundation.  I will cover these in part 2 of this series.

This post was also published on the Nodalities Blog
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