The document discusses open innovation and TRIZ methodology for inventive problem solving. It notes that TRIZ asks designers to define the ideal solution without negative aspects, and looks for solutions across domains by removing domain-specific language. The document then discusses semantic interoperability of data through shared data models and vocabularies, and provides examples of existing linked open data sources and vocabularies that could be reused.

1. Notes for Talk on 12th June to Open Innovation meeting: Peter
Winstanley
06 June 2013
09:17
Introduction
1/ In any area of endeavour - business, administration, entertainment - the availability of resources
for innovation can be the difference between business as usual with standard margins and returns,
and business as exceptional in which the greater efficiency and effectiveness from innovative
products and processes gives us more for less.
2/ There are standard methods applicable to project management (e.g. PRINCE, PRiSM etc), or
quality management (e.g. TQM, Six Sigma) but many people approach the creativity and ideation
process with a clear canvas frame of mind. There is a belief that creativity and invention is an open,
free-form activity with brainstorming/ 6 hats and simple cause-effect and fishbone diagrams as the
tool sets. I want to mention TRIZ, as a systematised methodology for inventive problem solving and
highlight a few aspects which will act as a backdrop to this presentation. I think that this can and
should be incorporated into the development of programmes of work to develop smart cities just in
the same way that quality improvement methods are.
2a/ There is often a mindset/problem of 'rampant incrementalism' that starves the radical
innovation.
3/ TRIZ methodology asks designers to define what the ideal solution would look like - all the
benefits of an efficient system, but without the negative or wasteful aspects. TRIZ also recognises
that in many cases a problem in one domain has actually been solved and is well understood in
another domain - so if we can remove the domain-specific language we can look for inventive
solutions by analogy. If we have to guide the mouse to take a route to the cheese, isn't it easier to
go from known solutions than to be faced with an infinite set of options. TRIZ methodology prompts
us to look at systems from the super-system level - from the bird's eye view and to look for
contradictions that constrain solutions to curves of compromise where an improvement in one
dimension is associated with degradation in another dimension.
4/ With these elements of the TRIZ methodology in mind I'll take a tour of the data interoperability
landscape picking out some of the publicly available datasets and how they might fit into the context
of a Smart City
Birds Eye View
Data is explicitly included in the notion of a smart city .. It's assumed that those in a smart city will be
using data and generating data. "Big data" is a relative and perhaps meaningless term. However, in
order for the data to be shared and re-used by the various constituent parts of the smart city and its
neighbours the data needs to be interoperable. This is recognised, especially in EU Directives and
Frameworks. The European Interoperability Framework describes interoperability at 4 levels:
1. Legal - align legislation so that exchanged data is accorded proper legal weight
2. Organisational - Co-ordinate processes across organisations

2. 3. Semantic - Precise meaning of exchanged information is preserved and understood by all
parties
4. Technical - Planning of technical issues involved in linking computer systems and services
Focussing on the 'Semantic Interoperability' an ideal solution might be that we all use a shared
common data model that allows data to be merged between parties without any "Extraction,
Transformation and Loading" overhead. Semantic Web approaches that use the Resource
Description Framework model of data are at the heart of the strategic path of the EU and other
organisations' to achieve semantic interoperability. Note that RDF is a model, not a syntax.
This approach (described by Berners-Lee in a "1 star" to "5 star" classification scheme) is achieved
by publishing data on the web, making it accessible by HTTP URLs using the RDF model and then
using that RDF formula of triples to describe our data and to link it out to other datasets so as to
develop a network of 'Linked Data' that can be queried by computers in a federated way using the
SPARQL language.
In addition to being technology-neutral and non-proprietary, other key benefits of using RDF for a
significant part of the data exchanges within a smart city are that the RDF is capable of being self-
describing and that it naturally de-duplicates. By making data self-describing and automatically de-
duplicating, the whole process of Extraction, Transformation and Loading (ETL), which is generally
the process with the biggest overhead in data exchanges and one that impedes the scalable
interoperations of data, shrinks to negligible proportions
Warning
Cities can easily lose leverage to private companies their citizens rely on, as the persistent battles of
political leaders against telecom companies over price increases show. And private-sector software can
operate behind a veil: Townsend says that while cities have made lots of data freely available online,
there’s less concern about opening up the proprietary tools used to analyze that data—software that
might help a city official decide who is eligible for services, or which neighborhoods are crime
hotspots. “It’s the algorithms in government that need to be brought out to the light of day, not the
data,” he says. “What I worry about are the de facto laws that are being coded in software without
public scrutiny.”
Pasted from <http://www.bostonglobe.com/ideas/2013/05/18/the-too-smart-city/q87J17qCLwrN90amZ5CoLI/story.html?
s_campaign=8315>
Identifiers of things
Any dataset describes some aspect of some thing. URLs are used in RDF to represent everything.
URLs for information assets such as documents can resolve by returning these assets, but for
abstract things such as concepts and for real world things such as people and places the URL can
resolve to provide some information about the thing they represent.
So, how do I design these URLs and how do I know if there are already URLs 'out there' that I can re-
use.
From other disciplines we know that the cookbook approach is a good one to use to help with the
design. So, for URLs there is a cookbook

3. [https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/60975/designing-
URI-sets-uk-public-sector.pdf] and there is already a service, http://sameas.org that is harvesting
URLs from RDF on the web and organising them into groups that refer to the same entity. The UK
Government Linked Data Delivery Group is developing a registry for URLs
[https://github.com/der/ukl-registry-poc/wiki ]
Clearly we don't want to have too many URLs that are identical in meaning, but it is happening at the
moment because in many instances the organisations that have legal and moral authority to
populate this space are not doing do and others who need the identifiers for their datasets are just
minting them. However, in time this redundancy will diminish and models will coalesce.
So what is 'out there' in the wild, available for use? These are some sources.
• The Scottish Government has minted URLs for its buildings , e.g.
http://cofog01.data.scotland.gov.uk/id/facility/AB0001 as part of its RDF publication of half-
hourly utilities consumption data
• Ordnance Survey have a whole swathe of URLs (http://data.ordnancesurvey.co.uk/ )
representing all the 'things' in the OS dataset, the CodePoint postcode units, the features in
the 50K maps, and the boundary lines for administrative boundaries etc.
• Companies House: URLs for every registered company. [
http://www.companieshouse.gov.uk/about/miscellaneous/URI.shtml ]
• Charities Regulators: CHC and SC have a web page for each registered organisation that can
act as an RDF URL, e.g. https://www.oscr.org.uk/search-charity-register/charity-extract/?
charitynumber=SC039117
• Legislation - laws and SIs in Legislation.gov.uk [ http://www.legislation.gov.uk/asp/2012/2
and the RDF is available at http://www.legislation.gov.uk/asp/2012/2/data.rdf]
• RCAHMS have a URL-based approach to identifying buildings and other monuments. e.g.
http://canmore.rcahms.gov.uk/en/site/268070
• The British Library through http://sameas.org have URLs that identify authors and other
people in their catalogues.
• Virtual International Authority File: http://viaf.org/viaf/46769170/#Dix,_Otto,_1891-1969
• Europeana: through its API, the Europeana project has URLs that identify things in the
museums and galleries world. http://www.europeana.eu
• DBPedia: The RDF version of Wikipedia http://dbpedia.org
So there are identifiers for things at all scales from the identification of countries or administrative
units to an individual museum or gallery artefact.
Terminology
Once we have identifiers for things and concepts we can then describe and link them together with
terminology. This terminology can be similarly identified by URLs. There are many vocabularies in
the wild available for re-use. Some are core such as the vocabularies for RDF (and RDF Schema.
Others are able to be very widely used, such as the vocabularies to describe people and their inter-
relationships (FOAF).
There are vocabularies to organise the relationships between data elements. The RDF Cube
vocabulary [http://www.w3.org/TR/vocab-data-cube/] is a development from the SDMX XML
vocabulary and it is used to describe cubes of data where datasets are arranged in slices that
correspond to the different dimensions of the dataset.

4. There are vocabularies for classification. These are often expressed in terms of another RDF
vocabulary, SKOS. I recently worked with the UN to develop the multilingual RDF representation of
the COFOG [http://unstats.un.org/unsd/cr/registry/regdntransfer.asp?f=236 ] and other related
UN/OECD classification schemes.
Then there are vocabularies being developed as part of the EU ISA programme - "core vocabularies"
that cover the minimum set of terms that are needed to describe a Person
[http://joinup.ec.europa.eu/asset/core_person/description] , a Business
[https://joinup.ec.europa.eu/asset/core_business/description] , a Location
[https://joinup.ec.europa.eu/asset/core_location/description ] and a Public Service
[https://joinup.ec.europa.eu/asset/core_public_service/description ].
There are many domain-specific vocabularies that are available as RDF and are very widely used, in
the health area there is SNOMED-CT [http://www.ihtsdo.org/snomed-ct/] , in the cultural heritage
area there are the RCHAMS, AAT, CLAROS, Europeana etc. Town Planning has the Towntology
Retail: GoodRelations [ http://www.heppnetz.de/projects/goodrelations/ ]
Ontologies, Schemas, etc
We all share models of the things around us in the world …. and well designed things are obvious to
operate - we don't need the manual most of the time.
Ontologies and other schemas are just like that - they formally encapsulate all the legitimate
possibilities and constraints for a model.
By using a specific ontology we 'buy in' to these options and constraints.
Many of the terminologies referred to earlier are also components of an ontology (others that are
classifications schemes, such as the UN COFOG classification, are concept schemes and don't have
the tight constraints that are present in an ontology)
Ontologies allow inference and reasoning over the RDF. Inference allows the end user to create data
relationships that were not explicitly stated. For instance, if in natural language we state that
"William is married to Mary" then the understanding that "is married to" is a reciprocal relationship
allows us to answer the question "Who is Mary married to?" and to make the statement "Mary is
married to William".
So, ontologies can help people to develop that feeling for what to expect with any 'thing', the
possible relationships that there might be between this 'thing' and the types of 'thing' permitted
within the scope of the ontology.
But, in contrast to the XML or the RDBMS world, which also use schemas as patterns and
constraints, where what is not stated as true is false, the RDF world uses an Open World
Assumption encapsulated in the phrase "Anyone can say Anything about Anything" and where what
is not stated is unknown. The consequences of this area that RDF assertions might be made that are
conflicting - the use of a schema doesn't by itself ensure the logical or the real truth, or a data
element might be only partially described. However, the use of a reasoners and other tools that
query the data and test constraints would be able to help in this situation.

5. SPARQL
RDF has its own query language, SPARQL, and this can be delivered to endpoints over HTTP. Results
are returned generally as XML or JSON but transformation to other formats is trivial.
Scottish Government GOLSPIE Utilities consumption data: http://cofog01.data.scotland.gov.uk
DBPedia: http://dbpedia.org/sparql
Examples of RDF in real world systems
DBPedia
Ordnance Survey Linked Data http://data.ordnancesurvey.co.uk
Legislation.gov.uk http://www.legislation.gov.uk/ and http://openuplabs.tso.co.uk/sparql/gov-
legislation
Scottish Government GOLSPIE http://cofog01.data.scotland.gov.uk
DEFRA Bathing waters pilot
TellmeScotland pilot http://opendata.tellmescotland.gov.uk/
BBC World Cup and Olympic Games websites: Read about the dynamic publishing system at
CIPFA lists of Revenue Account headings: http://doc.cipfa.org.uk/CipfaLists.aspx
ProductOntology: http://www.productontology.org/
LinkedGeoData: http://linkedgeodata.org/About and
Cookbooks
URI design:
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/60975/designing-
URI-sets-uk-public-sector.pdf
Creating Linked Data: http://www.w3.org/2011/gld/wiki/Linked_Data_Cookbook
http://delicias.dia.fi.upm.es/wiki/images/7/7a/07_MGLD.pdf
Quick Start for Decision Makers: http://www.semantic-web.at/LOD-TheEssentials.pdf
Non-RDF data that could be very easily used in this way

6. Scottish Neighbourhood Statistics: http://www.sns.gov.uk could have an API such as
http://labs.data.scotland.gov.uk
Travelline Scotland: http://www.travelinescotland.com/welcome.do [raw timetabling data available
in XML from http://data.gov.uk/dataset/traveline-national-dataset ]
SQA Subjects data: http://www.sqa.org.uk/sqa/41276.html
Scottish Government Statistics: http://www.scotland.gov.uk/Topics/Statistics
SEPA Flood warnings: http://floodline.sepa.org.uk/floodupdates/
And many others: https://sites.google.com/site/scotlandsdata/dataandvocabularies
Inspiration and learning from others
http://publicdata.eu/
http://www.onegeology.org/ and http://portal.onegeology.org/
http://www.ebay.co.uk/
http://www.ivoa.net/
http://opencorporates.com/
http://www.productontology.org/
Projects to keep an eye on
http://grants.nih.gov/grants/guide/notice-files/NOT-HG-13-011.html

7. Scottish Neighbourhood Statistics: http://www.sns.gov.uk could have an API such as
http://labs.data.scotland.gov.uk
Travelline Scotland: http://www.travelinescotland.com/welcome.do [raw timetabling data available
in XML from http://data.gov.uk/dataset/traveline-national-dataset ]
SQA Subjects data: http://www.sqa.org.uk/sqa/41276.html
Scottish Government Statistics: http://www.scotland.gov.uk/Topics/Statistics
SEPA Flood warnings: http://floodline.sepa.org.uk/floodupdates/
And many others: https://sites.google.com/site/scotlandsdata/dataandvocabularies
Inspiration and learning from others
http://publicdata.eu/
http://www.onegeology.org/ and http://portal.onegeology.org/
http://www.ebay.co.uk/
http://www.ivoa.net/
http://opencorporates.com/
http://www.productontology.org/
Projects to keep an eye on
http://grants.nih.gov/grants/guide/notice-files/NOT-HG-13-011.html