J Carr - Open Data - Public and Private Sector approaches

8/10/2019 J Carr - Open Data - Public and Private Sector approaches

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Open Data: Public and Private sectorapproaches

Judith Carr

Birmingham City University

MSc

2014


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Open Data: Public and Private Sector approaches.How far are both sectors considering Shakespeare

Reviews Recommendation 9 and what are the barriers asregards technology, culture and change?

JUDITH CARR

In partial fulfilment for the degree of

Master of Science

May 2014

Birmingham City UniversityFaculty of Technology Engineering and the Environment

1stSupervisor: Dr J Bhogal2ndSupervisor: Dr C Evans


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Abstract

The purpose of this dissertation was to explore the relationship between open datapolices and public sector procurement in the UK, using Recommendation 9 of the

Shakespeare Review as reference. The literature review identified key issues and

barriers involved in the implementation of an open data policy and highlighted the added

complexity the relationship between the public and private sectors brings to the concept

of 'open by default' and the open data value chain.

Primary research was carried out, in the form of an e-mail survey to assess local

authority engagement with the inclusion of an open data policy in the procurement

process, together with a series of unstructured interviews to identify operational

issues/barriers. The results were analysed and compared with the literature review and

specific case studies.

Analysis showed that as yet there is little consideration of this added dimension to open

data initiatives outside central government policy documents. That the implementation

of this additional complexity as well as an open data strategy as a whole depended

more on culture and control within and between organisations and the context, rather

than technology. Initial questions were formulated for organisations to consider when

contemplating the adoption of an open data policy and opportunities for further research

identified.


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Acknowledgments

Thank you to all the people who took time to answer my questions and talk to me,

sometimes at length, about open data, without whom this paper would not have taken

shape.

Thank you to my family and friends for listening and supporting me through the research

and writing up and throughout my postgraduate studies.

Thanks also to my supervisors, Jagdev and Cain for encouraging my enthusiasm for the

subject.


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Table of contents

Page

List of figures 1

List of tables 1

Chapter 1 2

1.1 Introduction 2

1.2 Shakespeare Review 5

Chapter 28

2.1 Open DataWhat and How 8

2.2 Open DataWhy 10

2.3 Open Dataopening up process 14

2.4 OpenHow far 19

2.5 OpenThats all context and provenance 20

2.6 OpenCultural dimension 21

2.7 OpenResources, feedback and risk 24

2.8 OpenAnonymisation and misuse 25

Chapter 3 28

3.1 Methodology 27

3.2 Method 30

3.3 Data collection 30

Chapter 4 35

4.1 Analysis of e-mail responses 35


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4.2 Analysis of interviewskey themes 37

Chapter 5 44

5.1 Local Government analysis 45

5.2 Interview analysis, literature review, casestudies

44

5.3 Guidelinesopening questions 48

Chapter 6 Conclusion 50

References 53

Bibliography 58

Appendices

1 Summary of Recommendations 1 to 8 59

2 5 Star Data 60

3 i Definition of OpenOpen Source 61

3 ii Details of Licences 62

4 Table of Barriers 63

5 Definitions 64

6 Adapted value chain 66

7 Questions e-mail survey 67

8 Project Proposal 68


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List of figures

Page

1 Recommendation 9 5

2 Definition of good data 8

3 Value ChainPSI 16

4 Ecosystem 18

List of tables

1 Features of Qualitative Research 29

2 Method and Description of unstructured interviews. 38

3 Questions when considering open data strategy 49


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Chapter One

1.1 Introduction

The Open Knowledge Foundation (founded in 2004) defines open data as

data that can be freely used, reused and redistributed by anyone subject only, at

most, to the requirement to attribute and share-alike (Okfn.org, 2014).

According to the World Bank, data is open if it satisfies the following conditions:

Techn ical ly o pen:available in a machine-readable standard format, which means it

can be retrieved and meaningfully processed by a computer application

Legal ly open:explicitly licensed in a way that permits commercial and non-commercial

use and re-use without restrictions

(Data.worldbank.org, 2014)

Clearly there are two main elements to the concept of 'open data,'open' and 'data'. The

concept of open referencedby the World Bank would mean at its most elemental form,

information that can be used without repercussions (copyright or patents). In this sense,

it is not bound by technology but more by social, economic, cultural and legal

parameters. 'Data' on the other hand, is almost universally used as a technological

term, as in information kept and reproduced in digital form, liberated by being accessible

via the Internet/World Wide Web. However, data is not information; in disciplines such

as Information Science, it is defined as unprocessed information (Hey 2004).

This concept of data as a resource that can be used to create information, which in turn

can help society, governments, the public, companies, in some way, is at the very centre


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of the push to make such data available. This data can be used as part of the DIKW

(data, information, knowledge, wisdom) chain to create value (Hey 2004).

Chignard (2013) in his 'Brief History of Open Data' states that the concept of opening up

information has its origins in the sociology of science and the theories of R K Merton.

The Royal Society in its Science as an Open Enterprise report of 2012 (Boulton et al.,

2012), suggests that it goes even further back in history to the printing press, when

scientists took to printing their theories and research, making 'data' more widely

available and open. For example, Henry Oldenburg, who pioneered printing scientific

treaties, peer reviewing and sharing information, inviting people, even laymen, to write

to him and refusing to publish in Latin, (Boulton et al., 2012).

Whatever the origins of the concept of openness, it cannot be denied that until the rise

in the use of digital technology it remained relatively costly to gather, analyse, interpret

and communicate large amounts of data or information. The Internet, has contributed to

the increase in data and provides the ability to share and store greater amounts through

cloud services (appendix 5). Social media networks allow greater access to information,

and facilitate richer dialogues with customers. In the future the internet of things(appendix 5) and the internet of services (appendix 5) will be part of our everyday

interactions and create even more data. The Internet is seen as both a communicator

and a generator.

If some see the first wave of 'openness' as the creation of the printing press (Tapscott

and Williams, 2010) many now cite the rise of 'the digital age' with the increasing growth

of data accessible via the Internet, the ability to connect data and people, coupled with

new abilities to store, manipulate (mine) large quantities of data and access connections

and patterns, as the second wave.

This openness has potential to contribute to the political agenda of many countries, that


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of more open and transparent government. The potential lies in creating new and

innovative markets in the re-use and application of data or highlighting efficiencies that

can be made integrating new processes, contributing to the much sought after

economic growth needed to move out of recession. Open data is part of the process to

make governments more transparent and accountable, to engage and involve citizens

and counter corruption, (Open Government Partnership, 2014).

The UK, along with the USA, is at the forefront of the Open Data Movement with the

creation of the flagship Data.Gov.UK website, launched in 2010 that to date holds

17,854 datasets. Since the launch of Data.Gov.UK, the UK Government has not been

slow in pushing its agenda. After publishing the Open Data White PaperUnleashing

the Potential in 2012,(Great Britain. Cabinet Office and Paymaster General,2012) the

Government commissioned an independent review of Public Sector Information (PSI,

government data that could potentially be open). This was called the Shakespeare

Review,(Great Britain. Department for Business, Innovation and Skills, (Shakespeare)

2013), published in May 2013.

Shakespeare made 9 recommendations, all of which were accepted by theGovernment,(Great Britain. Cabinet Office, 2013).

Public Sector Information is seen as being generated by public bodies, central or local

government. However, Recommendation 9 (Shakespeare, 2013), recognises that the

public sector does not work in isolation from the private sector. It is this

recommendation and its implications which frame the basis of this dissertation.

1.2 The Shakespeare Review

The Shakespeare Review (Shakespeare, 2013), was accompanied by an additional


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report MarketAssessment of Public Sector information compiled by Deloitte for the

Department of Business Innovation and Skills, (Department for Business Innovation and

Skills, (BIS) 2013).

Recommendations 1 to 8 are summarised in appendix 1. This paper looks at

Recommendation 9 (figure 1 below), as the basis of a review of the concept of open

data in relation to public and private sector organisations.

Although in the UK, the Government is the major force in pushing the 'open data' and

'transparency' agendas forward; the private sector also uses and produces data.

Recommendation 9 clearly lays out the complex relationship between both sectors

when considering open data. Previous reports such as the Open Data White Paper

(Great Britain. Cabinet Office and Paymaster General,2012), focused only on the

potential of the information, the uses that it could be put to and the hopefully resultant

economic growth and benefits.

The Shakespeare review (Shakespeare, 2013), highlighted another development in

respect of the opening up of PSI - where the private sector uses open data, or is

actually creating such data because of a public/private partnership, then surely there is

an assumption that there should be re-sharing and/or opening up of their data.

Figure 1: Recommendation 9

'We should develop a model of a 'mixed economy' of public data so that everyone can

benefit from some forms of two-way sharing between the public and the commercial

sectors.

Where there is a clear public interest in wide access to privately generated data, then

there is a strong argument for transparency (for example in publishing all trials ofnew medicines). As the Royal Societys Science as an Open Enterprise report sets outthis warrants careful consideration in each case so that legitimate boundaries of

openness are respected. For example, data could be made public after intellectual

property has been secured or after a particular product has been launched. Wherethe data relates to a particularly and immediate public safety issue, it should be

published openly as soon as possible

A company working with government should be willing to share information about

activity in public-private partnerships, as information about activity in public-private partnerships held by private companies is not currently subject to theFreedom of Information Act. This could be greatly enhanced without the need for

legislation by creating a field in procurement forms asking for the companys open

data olic re ardin the sou ht contract'


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Recommendation 9 (Shakespeare, 2013), brings into focus that there is no clear

delineation between what private and public sector organisations do as regards

generating PSI, even if their strategic aims and objectives may differ. As a recent report

for Institute of Government Making public service markets work states:

Government is now rarely the sole provider of publicly-funded services. Today, roughly

1 in every 3 that government spends on public services goes to independent

providers.(Institute for Government, 2013, p. 4).

The UK Governments acceptance of the Shakespeare Review (Shakespeare, 2013),

brings into question how such a concept is to be introduced. The aim, of this

dissertation is to undertake an initial exploration of the implications of this on future

policies and processes of both sectors, rather than consider them in isolation. It will

show how this adds complexity to the concept/innovation/philosophy of open data. The

question is how far are both sectors considering this recommendation, and what are the

barriers as regards technology, culture and change?

The objectives are:

To undertake a literature review on 'open data'

To discuss the relationship between technology, the information

economy and open data.

To identify where the open data movement sits in relation to the information

economy and other 'data initiatives'.

To analyse the rationale behind the recommendation

To analyse and review the responses to interviews, discussions and Freedom of

Information requests and evaluate the initial impact of Recommendation 9.

To evaluate the term 'open' in relation to Recommendation 9

To produce guidelines for organisations to consider when implementing a open


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data strategy

The remaining chapters will be structured as follows:-

Chapter 2- an overview of the basic principles of open data, a review of

literature regarding open data initiatives to date and issues surrounding

implementation of such initiatives

Chapter 3details the methodology behind the study and the research

Chapter 4- analysis of data

Chapter 5comparison and analysis of issues raised from research and two

cases studies, development of guidelines in form of questions to ask when

considering an open data strategy

Chapter 6conclusion and identification of further research.


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Chapter Two

2.1 OPEN DATAWhat and How

Open data is not data solely published/ released by government organisations. Any

data from any organisation - commercial, charitable, civic or semi-public, can also be

open data. Most importantly, open data is non personal data.

The Open Data Institute (ODI), a UK non-profit organisation set up to, 'catalyse the

evolution of open data culture to create economic, environmental, andsocial value'

(Theodi.org,2014b), states that the data should be available at no cost, with the

appropriate licence and goes further by describing what good open data is. Good

data...

Figure:2 Definition Good Data (Theodi.org.uk,2014a)

To be most useful, the data should be in a format such as XML, JSON or RDF.

However, many local authorities in the UK also publish data as CSV files.

The more accessible the data the better, as regards being open. There is a 5 star

scheme for Open Data, details of which can be found in appendix 2.

This scheme is used by the UK Government; the expectation is that all departmental

data will achieve at least 3 stars (Great Britain. Cabinet Office and Paymaster

General,2012).

By linking data (appendix 5), more data becomes accessible; it is easier to update

and combine data if links are already made. Unlinked data would require its own

specific search query, which could prove difficult and would certainly be time

consuming. Linking data increases the chance of a query or search success,

(Data.gov.uk, 2014 and Moore, 2010).

1. Can be linked to, so that it can be easily shared and talked about

2. Is available in a standard, structure format, so that is can be easily processed

3. Has guaranteed availability and consistency over time, so that others can rely on it

4. Is traceable, through any processing, right back to where it originates

(Theodi.org, 2014a)


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Data is published or released under licence; data is not considered open unless it

has the appropriate license, (Theodi.org, 2014a). Such licenses recognise the user's

right to access and use the data freely, (Halonen, 2012). Appendix 3i and 3ii give

further details of the open definition/ philosophy behind the licencing of data and

details of the various creative commons licences. In the UK, the ODI has created a

certificate process for data, a process of self certification, with four kinds of

certificate, raw, pilot, standard and expert, (Certificates.theodi.org, 2014).

Open data is made available via an organisations website or via a platform such as

data.gov.uk or more local platforms such as DataGM (Greater Manchester). Data

can be published in a variety of forms, but as a data user, 3 stars plus is the bestoption - all the data should be machine readable with no particular propriety

software needed. Raw machine readable data does not limit the number of use

cases, but instead supports reusability (Braunschweig et al., 2012) .

There are three classes of open data platform as detailed by Braunschweig et al.,

(2012).

Link Collection - the most common type hosting a collection of links, data is

held by different data providers, less standardisation of metadata.

Download Catalogue - host the files as well, higher reusability enabled.

Integrated Databases- offer integrated datasets, 100% machine readable

but offers the least datasets available to look at in any way.

A platform is a digital repository of datasets, digital files of data, accessed via the

Internet and a web address. Platforms can be organised as either non-curated

platforms, run by communities and curated platforms, which are moderated and

usually run by a public or semi-public organisation, (Braunschweig et al., 2012).

The technology used to create open data is the same whatever type of organisation

wishes to open up.


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2.2 OPEN DATAWhy

Government/Public Sector

Open data enhances transparency and accountability. Yu and Robinson (2012) go so

far as to call it a:

powerfulforce. Raw data can now be analysed, processed and combined using

new technologies, which in turn allows for a new level of public scrutiny.'

In a recession, efficient government operations can save money. It is the idea oftransparency and accountability, coupled with potential economic growth that has

brought open data to the forefront of the UK and many other countries' digital

policies.

The origins of openness stem from philosophical ideals but Rufus Pollock's paper

'The Economics of Public Sector Information', (Pollock, 2008), is the much cited

influence on the economic push. The downstream value of opening up data that in

replication has a nil or marginal cost, is measured in billions,(Vickery, 2011, Newbery

and Bently et al., 2008, Pollock, 2008). Indeed, the 2013 report Market Assessment

of Public Sector Information(BIS, 2013), that accompanied the Shakespeare

Review, (Shakespeare, 2013), and informs the economic push in the UK, states that

including an aggregate figure for social value (appendix 5), it is estimated this figure

could be 6.2 billion a year, (BIS, 2013). A hard figure to ignore, as Huijboom and

Van Den Broek, (2011, pp. 1--13), state,most countries(European) legitimise their

policy on such studies.

The UK government sees itself at the forefront of the movement. As the host for the

2013 G8 conference, it oversaw the publication of a G8 Open Data Charter (Cabinet

Office, 2013), published 18th June 2013, stating open data is at the heart of a global

movement to, 'create more accountable, efficient, responsive, and effective

governments and businesses, and to spur economicgrowth'. The first principle of


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the charter is 'open by default',(Cabinet Office, 2013).

The Shakespeare Review calls the concept of open data: radical new and

challenging policy approach,(Shakespeare, 2013). Gurstein calls the open data

movement, relatively new but very significant and potentially powerfulemerging

force,(Gurstein, 2011).

This fundamental shift in the relationship organisations (public) have with their data,

its ownership and its beneficiaries, has implications for many. Initial economic

studies have centred on the re-use value of PSI, outside the organisations that

produced the data (although there is increasing recognition that internal use of open

data creates value, see appendix 1 recommendation 8). This is, undoubtedly, as a

result of the economic climate where savings and efficiencies within the public sector

are of paramount importance and a government objective is to stimulate growth.

Opening up data, then, is an attractive proposition, as it has the potential to do both.

Notwithstanding that, there is a certain naivety in the assumption that everyone will

embrace the open data initiative because of this potential value as Jetzel and Avital

et al. (2013) state:

value generation happens through a complicated network of mechanisms where

public sector, private companies, civil society and citizens all contribute to the

transformation of OGD to value (Open Government Data).

This complexity makes such value judgments difficult. Halonen (2012) says there

are varying views as to whether the economic impacts have been clear yet,

especially as there is not only economic but social value to calculate. As Huijboon

and Van den Brook (2011) conclude:

many policy makers also recognise that the precise economic impact of open data

for their country, and specific sectors or organisations, remains largely unclear.

There was, and is now to an extent, a lack of further study in relation to valuing the

use of open data. The recent paper Generatingvalue from open government data

(Jetzel and Avital et al. 2013) asserts that:


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the complexity of the open data landscape is blurring the boundaries between

economic markets and social networks, and the concept of economic and social

values will have to be re-thought, Jetzek et al ( 2013).

Additional complexity manifests itself through Recommendation 9 (Shakespeare

,2013). As citizens pay for the generation and upkeep of this data, they should be

able to benefit from its value (either directly as a first line data user or indirectly

through improved efficiencies, economic growth and social value). As the

Shakespeare review says:

Data that is derived from the activity of citizens must be seen as being at least co-

owned by them and returning value to them and thusA company working with

government should be willing to share information about activity in public-private

partnerships,(Shakespeare, 2013).

This has been given further credence with the publication of Statistics and Open

Data report by the PublicAdministration Select Committee (PASC, 2014). Tom

Steinberg, author of the influential The Power of Information in 2007, (Great Britain

Cabinet office, 2007), a major contributor to the debate regarding the influence of

technology on information and civic engagement, is quoted as saying:

Open data will only become widespread if its provision is tied to the procurement of

information systems. (PASC, 2014).

The ODI goes further, stating that the provision should be in every government

contract whether IT or not (PASC, 2014), a logical step, in parallel with the concept

of freedom of information. This could be implied through the use of licences, but it

has not until recently been considered when looking at data publication. This lack of

consideration for opening up private sector data originating from PSI re-use

businesses is further illustrated in the paper Eight Business ModelArchetypesfor

PSI Re-Use, (Ferro and Osella, 2013). The business models concentrate on data

elaboration and value proposition, but do not seem to consider there should be a

payback in terms of opening up the resultant data. For businesses based on open

source philosophy, this could be taken as a given, but this seems unlikely as it is a


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new concept for some of the more traditional sectors that will be affected by such

requirements.

Commercial/Private sector

The value of openness and sharing is not confined to the concept of re-using PSI.

As a result of worldwide economic conditions there is a push to innovate and create

competitive advantage. The two underlying (as well as underused) assets that can

be harnessed for companies are data and intellectual property (IP). Collaborations

and the sharing of IP are increasingly seen as ways to create value; this does not

mean losing control, more a question of balancing the IP portfolio, (Tapscott and

Williams, 2010 p30). Data, the production of data via digital interactions, the trackingof devices and objects via sensors, and use of information systems has grown

exponentially over the last 5 -10 years and is set to increase further with the

development of the internet of thingsand the internet of services. Commercially,

data is part of the information assets of a company, although there is still some

debate over how to value information. This has lead to a new field called

infonomics, the economics of information. Leading technology consultancies now

offer advice on valuing the data an organisation holds (Searchcio.techtarget.com,

2013).

The private sector experiences the same constraints over budgets and need for

efficiencies as the public sector. Worldwide recession has meant companies have

had to search for new strategies to fertilise growth. This, coupled with a change in

the relationships organisations have with their customers through the rise in social

media and participation, has meant there is far more focus on sharing and openinnovation. According to Gartner's research:

'seeking competitive advantage through direct interactions with customers, partners

and suppliers, open data is the solution', (Gartner.com ref).

Rigby and Zook (2002, p88-93), argue to improve speed, cost and quality of

innovation, companies should open up their innovation borders to vendors,

customers and even competitors. This will increase, theimport and export of novel

ideas.


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However, they also say, 'The propensity foropen-market innovation varies across

industries', (Rigby and Zook, 2002, p88-93) and so it would with open data strategies

and public/private partnerships.

2.3 OPEN DATA - opening up process

When considering how and what is to be opened, Zuiderwijk et al., (2012) refer to

the open data process, open data being less a product, rather an on-going process

that encounters many socio-technical impediments, both human and technological.

Already, there can be seen a move away from the technology, the methods of how to

be open, to the more complex world of openness and sharing. Recent studies have

shown this by considering drivers, barriers, enablers and myths around opening up

data, Janssen et al. (2012), Van Veenstra and Van Den Broek, (2013) and Zuiderwijk

et al. (2012).

Jetzek and Avital et al. (2013) review of literature on re-use, found current literature

focuses mostly on the economic value of open data. They go on to say that opening

up government data has a disruptive aspect, emphasising the transformation from a

closed to an open interconnected world. Previously private companies and public

existed within their own administrative boundaries, and relations between them

are/were based on traditional market behaviour, rules and regulations, (Jetzek and

Avital et al. 2013).

When this relationship is changed, due to governments becoming open:

connections between the public and the private as well as economic and social

dimensions begin to emerge,(Jetzek and Avital et al, 2013).

They consider that to value open data, it must be viewed as multidimensional. Citing

Sarker et al (2012), Exploring value co-creation in relationships between an ERP

vendor and its partners: a revelatory case study. Such references to the

implementation of information systems is further validated by the statement

referenced earlier from Tom Steinberg, that, Open data will only become widespread


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if its provision is tied to the procurement of information systems, (PASC, 2014).

The ubiquitous use of information systems within organisations is studied not only

from a technical view point but also from a people perspective. Open data initiatives

are a new phenomena, as Jetzek et al (2013) state, though the value generated by

opening up data (government data in particular), has been widely discussed by

public bodies and other stakeholders, little attention has been paid to this

phenomenon in academic literature.

The open data movement is complex, involving many participants from different

organisations; there may be insight to be gained from studying literature and case

studies on information systems implementation in microcosm. As Lassinantti (2013),

states, to acquire knowledge about people involved in process of developing an

information system (regardless of role) is seen as essential. A deeper understanding

of groups involved in the open data initiative will increase our knowledge.

Lassinantti (2013) compares the open data initiative with the implementation of an

information system; the construction of an information system in itself is a social act

and so, therefore, is the opening up process.

The participants, stakeholders and beneficiaries involved in open data are many,

making the landscape far larger than that of an organisation, even a global company.

The most recent literature from Janssen et al (2012), Zuiderwijk et al (2012) and

Martin (2013) look at the barriers and impediments in the opening up process. Allthree studies reviewed the current and as Zuiderwijk et al (2012) state, limited

literature, to compile their questionnaires. Zuiderwijk identifies 118 impediments,

Janssen 57 and Martin narrows down his from 70 to 33, many of the barriers are

similar depending on the perspective of a data publisher or data user point of view.

Huijboom and Van den Broek (2011), when comparing international strategies

identify ten high level barriers and although as Zuiderwijk et al (2012), comment that

barriers and impediments can change as, policies and infrastructures are created all

of these studies show that even though the barriers listed can be numerous,


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examined from the different perspectives of data user and data publisher , all lie

within the three themes of people, processes and technology. Appendix 4 illustrates

this point further.

Reports and studies to date have concentrated on the process of opening up

government data and have considered the data user to a limited extent. This has its

drawbacks, Martin (2013), concludes that one of the limitations of his study was the

academic bias of his sample and that the open data community, itself, is hard to

identify. This situation is further facilitated when there is no feedback mechanism. If

you do not know who is using your data, you cannot fully identify the stakeholders

involved, how big the community is or who it is made up of?

This lack of feedback was considered to be a reason why user needs and

findability issues had not yet been considered by data publishers (Janssen et al.,

2012 ) and was highlighted by Halonen (2012), who quotes Worthy et al (2011) that,

data publishers simply do notknow who uses their data at the moment. True, this

relates to freedom of information requests, but is nevertheless apt.

Vickery (2011) in his review of the market for PSI in the European Union illustrates

the value chain for open data as show below in figure 2.

Figure 3: Value Chain PSI re-use (Vickery, 2001, OECD, 2006)


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This in reality is a far too linear process and does not recognise the value of

feedback from various stakeholders involved, although it does show the pervading

role of technology.

Accepting the potential value of the final product this simplification does not

acknowledge the fact that no one organisation or cohesive partnership is in control of

the whole process. This is before the impact of having the private sector involved in

public/private partnerships. Appendix 6 adapts the value chain to show where

private and public sector organisations interact with the process. This in itself is still

simplified, as it does not show the nuanced relationships that have and would evolve

nor does it indicate where feedback would benefit the process. It does show the

emerging complexity, there are a lot of data flow arrows. AsDavies (2011), in his

paper Open Data. Infrastructure and Ecosystems states, open data initiatives

involve diverse stakeholders such as bureaucrats seeking policy innovation,

transparency activists, technologists with interest in the computerization of

government and companies seeking economic gain and involves people from across

the political spectrum.

Davies goes on to analyse the success and effectiveness of the International Aid

Transparency Initiative (a multilateral open data initiative), where there are incentives

to encourage data publishing to common standards and efforts have been made to

ensure tools are available to interpret and visualise the data published. This has led

to more political support and demand for further data and metadata, countering the

premise put forward by Robinson et al. (2008), that governments should focus solely

on the provision of datasets (Davies, 2011). Leading from this study, is the assertion

that inert publishing of data, without any peripheral activities will not yield the full

benefits so often promoted by the open data movement. This is substantiated by the

Jertzek et al study (2013), they state that the build it and they will come approach

will only succeed to a marginal extent unless other enabling factors are present.

These are openness, resource governance, capabilities and technical connectivity.

This was recognised by the Open Knowledge Foundation (anon profit organization


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promoting open knowledge, including open content and open data) through one of

the founders, Rufus Pollocks blog in 2011,( Pollock, 2011) where he laid out the

disadvantages of a linear data processing model, showing why the ecosystem

approach is more beneficial. See figure 6 below.

Figure: 4 Ecosystem (Pollock, 2011

This ecosystem is somewhat simplistic as it does not consider the task of making the

source data available. However, the issues relating to the process are the same for

both data publishers and data users (an organisation can be both). The problems

and issues concerning openness and open government data apply to both public

and private sector organisations alike and the most important of these will be

considered in the final sections in this chapter.


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2.4 Openhow far?

The openness part of open data may, in the longer term, be deemed far more

important and difficult to adjust to; justifying a study of the socio technical issues

involved. The concept of being open in the context of the open data movement is

closely linked with the open source movement, (Chignard, 2013, Halonen 2012).

The open source way has risen out of the success of the open source movement,

which is unquestionably tied to the change in social structures around software

development and communities. As Neus and Scherf ( 2005, pp. 215--225,), state:

Asopen-source software becomes accepted worldwide, open-source collaboration

and development methods arealso gaining greater momentum.

There are five elements of the open source way; open exchange, participation,

rapid prototyping, meritocracy and community (opensource.com, 2014b). Neus and

Scherf (2005), further describe such collaboration as:

a meritocratic philosophy that invites feedback from everyone. Encourages testing,

feedback, and quick evolution of solutions.

But open exchange is not the same as open data. There are many instances where

sharing, joint ventures and collaborations result in benefits for those involved.

According to Henkel et al (2013) there is a growing field of literature that addresses

the, potential advantages of open innovation over closed innovation. Their study

shows the reasons for being open are for competitive advantage, the successful

strategy is selective openness,diametrically different from the open by default

policy adopted by the G8 charter and understandably so. This raises the question of

the goals and strategies of those involved. Evgeny Morozov in his book, To Save

Everything Click Here quotes Chris Kelty, (a UCLA anthropologist) that:

thereis still debate and confusion about the merits and meanings of openness

even among those who have done most to promote open. If openness is a means

to achieve something rather than an end, then what are the goals and who sets

them?.


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If an organisations goals can be served by selective openness or making

information or data available in a form that is not fully open but serves its purpose,

should that not be acceptable? Information derived from data can help governments

achieve accountability and transparency without it being in machine readable form.

Commercial organisations can be selective, and whilst at present studies have

shown the public sector has been too (Peled, 2011), this is not what is implied by the

open by default policy. In the UK, public procurement of private sector services

results in relationships where those involved have differing goals and agendas,

making an open by default policy far from straight forward.

2.5 Openthats all?context and provenance

Current literature is dominated by the analysis of the process of opening up data and

how this can be achieved. Yet there is a growing request for metadata (appendix 5)

and contextualization to accompany datasets.

As Dawes (2012), points out, data that is now being considered valuable was in all

probability created for purposes other than external or unplanned use. Dawes goes

on to contend that such administrative data would not be managed in a way that

external potential stakeholders might expect. Such data could lead to

misunderstandings, when not accompanied by contextual information about the

social economic setting it was gathered in, technically, without any metadata. The

principle of open data is that it is available without restriction for re-use, and this re-

use is therefore, unplanned.

The call from the open data community is, it doesnt matter if the information is

imperfect, with gaps, this can be sorted if need be. However, if the use of such data

grows then potential inaccuracies may breed further inaccuracies; interpretations

could be used irresponsibly, which the data provider may not be comfortable with.

The potential for this increases with the more datasets made available and the ability

to combine and analyse. In complex ecosystems of open data flows, there is also

the question of who is that data provider?


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Furthermore Dawes (2012), says raw open data creates problems as well as

benefits, stating that out of context, data loses meaning, relevance and reliability.

Metadata is, therefore, essential but platforms such as data.gov.uk promote the

assumption large, structured raw data sets are intrinsically better than processed

data, (Dawes, 2012). In the US where the open data movement has gained

perhaps greater momentum, this has lead to further consideration and study of

context within the open data landscape. In The dynamics of using open government

data ,(Helbig et al., 2012) recognise:

thesignificance of context, particularly in terms of the actors and their interests in

the governance of government data and access.

Thus there should be consideration of the dynamics of following an open data

initiative and making the data fit for reuse. The study goes on to highlight the

complexity of data creation, ideas of primary and secondary use, introducing the

concept of an information polity in order to understand how stakeholders (existing,

new and future) interests are shaping and are shaped by new information flows and

technologies. Whilst contending additional context makes the data more fit for

reuse, contributing to value creation and increasing value, it recognises this requires

additional effort and capability, (Helbig et al., 2012).

Dawes (2012), concludes open data presents problems, despite its promised

benefits. Apart from technical and managerial challenges there still remain policy

concerns, just as when considering information, of confidentially, security and

authenticity. The goals and needs of the data creator have to be balanced with those

of secondary users.

2.6 Open cultural dimension

Lakomaa and Kallberg (2013), state, the voluntary dissemination of data isa political

decision.


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The open way in regard to data may have grown within the discipline of software

development, but this is a far cry from the systems and processes that have been

developed to govern a city, local authority or country. Systems and processes,

indeed, that some see as being developed to be closed, precisely to avoid openness

and transparency, (Jetzek et al., 2013).

Whilst the many diverse commercial organisations in the UK may not want to be

described in similar terms, they are just the same, organisations with cultural identity.

Culture is a complex system of shared beliefs, values, language, customs,

behaviour, and artefacts that the members of a group use to cope with their

environment and with one another, (Neus and Scherf, 2005).

Neus and Scherf (2005), single out openness and transparency as the core of the

open source model. Transparency is also a major theme of open government and

open data is an enabler, but not the only one.

As Peled (2011), emphasizes by quoting Mahoney (2000), the Open Data Program

(in the US), promotes an imaginary world in which organisations and people happilyand altruistically share data and applications.

Returning to the question of goals, control and social economic settings of the very

organisations and departments that are the data providers, for whose benefits are

they are opening up and whose goals are being achieved?

Peled (2011), goes on to describe the situation in the US in respect of the data.gov

platform and federal agencies involved usage of datasets. His comments though are

apt for any government and set of public sector organisations. Each of them has

their own agenda, some more powerful than others and some of this power will be

seen to rest in the information held in datasets homed by years of internal

development ,(Peled,2011).

Those running these bodies, know when and how to release data, stories andforecasts as part of their efforts to increase their autonomyand reputation.(Peled,


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2011).

In Halonens (2012), study of opening up spend and salary data in local authorities in

the UK, the message is clear; this was done purely to meet a legislative obligation for

transparency.

Peled (2011), further reports that analysis of the datasets and usage on data.gov

show most (US) agencies did the minimum required. Since its inception, 5 of the

169 participating agencies accounted for 99.37% of all datasets.

The open data process, (Zuiderwijk et al., 2012), is thus far more than a technical

process of making machine readable data available via a platform or website. There

are cultural and political considerations as well as operational. Peled (2011), also

states that a majority of datasets were geographical in nature. One of the UK

government agencies using data.gov.uk is the Land Registry. In their recent

lunchtime lecture at the Open Data Institute How tobuild an open data centric

organisation(2013), they confirm one of the major problems in becoming such an

organisation is culture. Their data strategy ambition includes:

Maximisingbenefit and providing assurance through data, for the public, private

sector and our ownefficiency and capability.

To accomplish this they recognise that open data is a culture; internally they need

positive engagement, (How to build an open data centric organisation, 2013).

It is difficult to separate the cultural and political aspects from opening up data;

operationally there has to be investment in people as well as process. Therefore,

there has to be value placed on those within the organisation who are involved in

opening up and maintaining data and the relationships necessary to get the most

value from it. Whilst there is a fund of academic literature on change management

and cultural change, especially within commercial organisations, as yet there is

significantly less about managing the change to an open data culture. In the Royal

Societysreport Science as open enterprise, (Boulton et al., 2012), there are

recommendations about the valuing of opening up data and how communicating

such data is very important. Amongst the recommendations is one for such values

to be embedded within research organisations, accompanied by financial


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recognition, (Boulton et al., 2012).

2.7 Openresources, feedback and risk

It is increasingly recognised, that to gain value, data creation requires more than just

the uploading some datasets. As Davies (2011), says, thesimplistic freeing of

datasets for open data is likely to be ineffective in driving the economic growth and

political accountability hope for.

Operationally, resources and commitment are required from people within an

organisation. In order to devote resources in times of austerity,value has to be

gained from the outcome. Such value has to be measurable, true for both the public

and private sectors.

Proponents of open data cite the large economic and social value that is placed on

the re-use of data. However, both Deloitte who compiled by the BIS (2013), report

and Jetzek et al. (2013), consider that social value is difficult to calculate andforecast. The BIS (2013), report contends it is difficult to measure or predict values

because of the unpredictable nature of innovation; wider societal value is even more

challenging as it is not typically measured in monetary terms (BIS,2013). Jetzek et

al.( 2013), introduces four enabling factors for valuing outcomes, efficiency,

innovation,participation and transparency,but then go onto state, though they will

all generate economic and social value, they will do so differently, (Jetzek et

al.,2013).

If it is acknowledged on a macro level that valuing this resource is difficult then how

much more so will it be operationally, if the only values considered are empirical and

expressed in terms of currency. As Janssen et al., (2012), state there is, no way to

predict and calculate the returnof investment and that the main challenge is that

open data has no value initself; it only becomes valuable when used.


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In order to maximise the re-use value, data has to be contextualised and arguably

even marketed. There is a perceived risk involved in allocating resources to such

an initiative and bureaucratic organisations are risk-averse,(Janssen et al., 2012).

In private sector organisations, more entrepreneurial in approach, such risk could

possibly be mitigated by the winning of contracts.

The perception of risk, however, can be mitigated by feedback as well as

governance; the perception of value can be enhanced by feedback, operationally

and strategically. As reflected in current literature, by the studying of open data in

terms of organizational theories and the development of ecosystems (Zuiderwijk and

Janssen, 2013, Janssen et al., 2012, Davies, 2011,Helbiget al., 2012 , and Ubaldi,2013). Ubaldis (2013), study for the OECD Open Government Data: Towards

Empirical Analysis of Open Government Data Initiatives, goes some way to

addressing the overall complexity by including organisational and cultural changes.

2.8 Openanonymisation and misuse

No less important are the issues of privacy and security. Throughout all studiesthere is the assumption that the data being used is non personal, which is critical for

the acceptance of the opening up of government data by the ultimate data providers,

the public.

A significant amount of data that could have potential value will have personal

identifiers, if only because as Dawes (2012), states the majority of the information

held in databases considered valuable was not intended to be opened.Aside from

the cost of making this information anonymous, there is the more difficult question of

how anonymous. For as Ohm (2010), states, research and the study of re-

identification, a subsection of computer science, has revealed a tension, one that

undermines the publics acceptance of digital technology, data can be useful or

perfectly anonymous but never both, (Ohm, 2010).

While the Shakespeare review (Shakespeare, 2103) recognised the need to


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anonymise data, it calls for a pragmatic view, claiming that in the UK there is

currently:

an unrealistic degree of expectation of any data controller to perfectly protect all our

data - an attitude that inhibits innovation no method, including traditional non-

digital information storage, is proof against determined wrong-doers,(Shakespeare,

2013).

Acceptance that there can be misuse of open data brings into question just who is

accountable? Janssen et al (2012) commented: Although the use of open data

looks like collective accountability, it is likely that if something happens society will

expect intervention from government and will hold it responsible. This quote relates

to processing accuracy but it also holds true for privacy.

The ultimate data provider is the public and there are costs involved in losing its trust

and confidence. Ross Anderson ( Professor of Security Engineering at Cambridge

University), gave a recent lecture at the ODI Why anonymity fails(2014), in which

he cited research that showed if the public lose confidence in medical confidentiality,

they will not seek early treatment, indeed sometimes no treatment at all. This would

surely happen with other public sector organisations. If the public start to disengage

and lose trust, open government loses its effectiveness. Could this be the price of

transparency?

Whilst it is repeatedly emphasised that open data is non-personal data, there may be

too much faith in computer sciences ability to anonymise data; as Ross says

succinctly, pseudonymisation does not protect privacy, (Why anonymity fails,2014).

Studies have shown there is a lack of awareness of the difference between open

data and data sharing amongst the public and of the attitudes of the public to the

potential benefit of open data, (Sciencewise, 2013). Research about the publics

relationship with data has shown that concern over the lack of control over their (the

publics) personalinformation and how it is used,(Sciencewise, 2013 p 8),is


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compounded by two problems. The fact that due to advances in data analysis and

tracking the question of what is or is not personal information is becoming blurred

and the increased number of large datasets available, effectively anonymised and

then published, making re-identification easier, (Ohm, 2010).

Whilst Rosss lecture (Whyanonymity fails, 2014),was primarily concerned with the

health data of the UK, the same problems relate to private sector databases and

datasets. As the private sector becomes more involved in open data, there is a

question over who is accountable for privacy issues - the organisation helping to

create the data with its interaction with the public data providers or the public

organisation, which contracted the work. Furthermore, the private sector also usessocial networking as a strategic tool. Zhou and Pei et al., (2008) conclude,

Social network data is much more complicated than relational data, privacy

preserving in social networks is much more challenging.

The public in general is more willing to trust organisations that are open about how

their data is used (including being sold) and the risks involved, than those

organisations which are not open about what they are doing, (Sciencwise, 2013).

Recent surveys have revealed a marked reluctance for data to be sold for

commercial reasons; the preference being for such data to be used for the benefit of

all, (BIS, 2013). In the UK, this issue is at the forefront of the debate over

care.data, and the proposed extraction of general practitioners records (why

anonymity fails, 2014). It is possible that the next six months will produce a change

in policy and push for more training and education, for data publishers and the

public.


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Chapter 3

3.1 Methodology

The review of the literature and the landscape of the open data movement to date in

the previous chapter show this is a relatively new field of study, particularly when

considering the additional complexity introduced by Recommendation 9,

(Shakespeare, 2013). Thus, this study can be seen as exploratory in nature, the

focus being on gaining insight and familiarity in the subject area, highlighting areas

that would merit further investigation at a later stage, (Collis and Hussey, 2009).

In the proposal, when looking at information systems research for reference and

considering the cultural and social aspect of the open data initiative, the proposed

research was considered to be interpretive in nature. That being said, due to the

limitations of resources, the new area, the size of the study and the researchers

recognised influence on the approach to the question, it should, in fact, be

considered to take pragmatism as its philosophical approach. The approach is

focused on getting the best from the tools that are available, recognizing that no

single approach is perfect, (Denscombe, 2010).

The subject does not sit within one discipline and thus cannot fall under a positivist

philosophical definition that,itrests on the assumption that social reality is singular

and objective, (Collis and Hussey, 2010).

This is an approach, which is being used in other studies regarding open data, where

it is being treated as emerging phenomena (Janssen et al., 2012, pp. 258--268,

Davies 2010). This paper is an exploration/enquiry that is, aprocess that helps to

clarify, inform, stimulate and provoke, (Davies, 2010, quoting Skolnick, 1995 p, iv).

Furthermore, in this new area of study there is not, a wealth of literature from which

to define a theoretical framework and a hypothesis which lends itself to deductive

research,(Saunders et al., 2009). In consequence, therefore, it lends itself to be


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more inductive in nature, where, general inferences are induced from particular

instances, (Collins and Hussey, 2010).

As the purpose of the study is to, primarily describe a situation, phenomenon,

problem or eventit is thus qualitative research, (Kumar, 2005). This can be clearly

shown in table 1 below adapted from Kumar (2005).

Approach to enquiry Unstructured, flexible and open

Purpose of investigation Not to quantify a variable or situation

but to describe the issue, barriers, etc

Measurement of variables Description of variables rather than

measurement or classification

Sample size Few cases or samplessamples size

not used to highlight issues/situation

and areas of further investigation.

Focus of inquiry Multiple issues derived from looking

at particular topic, not related to size

of sample.

Research value Authenticity required but not value

freeresearchers perspective leads

to paths chosen

Dominant research topic Aim to explore experience, meanings

and perceptions

Analysis of data Narratives and observation data to

indentify themes and issues and

describe these

Communication of findings Descriptive and narrative in nature

Table 1 : Features of qualitative research methodologies adapted from Kumar ( 2005 p17,18)

Quantitative research is not suitable for this study because it relies on developing

metrics that can be used to describe objects or relationships under study, (Cornford

and Smithson, 2006).


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3.2 Method

The previous chapter illustrated where Recommendation 9, (Shakespeare, 2013) sits

in relation to the open data movement in the UK and shows how complex the issues

are surrounding open data.

Several objectives have been met in chapter 2. The review was carried out by

searching on BCU library databases, notably the ABI/INFORMS Global database

and Google Scholar. The search queries that proved more successful were those

that mentioned open data in relation to transparency and government; there was

less success in trying to extend research to non-governmental issues or data, using

the general term open data, in part due to the generic use of the word open. This in

turn highlighted that those studies most appropriate could still only be found when

linking the term technology to the term open and government when carrying out

searches. Due to the nature of the open data community and its associations with

other agendas, such as smart cities, it should be noted some sources were blogs by

those involved in either or both agendas.

3.3 Data collection

E-Mail

In addition to conducting a literature review to gain an understanding of open data, it

was also proposed to ascertain how far local government had considered this

proposal; a reasonable way to do this was to ask a set of specific questions via e-

mail.

There are 99 local authorities of varying sizes that are deemed fully open by the

website OpenlyLocal, a website devoted to opening up information and data on all

local governments to aid transparency, (Openlylocal.com, 2014). This provided

access to a specific set of authorities, some of whom were (randomly) chosen to

contact. E-mail was considered the most effective method of communication in thisinstance, because it is less time consuming than either telephone calls or interviews.


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Initially, as the proposal stated, it was the intention to carry out Freedom of

Information (FOI) requests, asking a few concise and specific questions regarding

the recommendation (appendix 7). However, on looking at the guidelines for such

requests, this approach was deemed too formal; the e-mail might not reach the

people who are at present engaged with open data and thus restrict the replies that

might be forthcoming. In order to e-mail as effectively as possible, therefore, each

authorityswebsite had to be reviewed, the appropriate pages found and the correct

e-mailaddresses obtained (although this was no guarantee of response). Initially, e-

mails were sent to randomly selected authorities within the 99. Among this group is

a mixture of large and small authorities. Where it was indicated that an FOI requestwas required, where only feedback regarding datasets was requested or no details

were given at all, no e-mail was sent. 36 authority websites were analysed regarding

open data, plus 3 websites of authorities that had won funding through the ' Open

Breakthrough Fund '(appendix 5) who were paradoxically not on the fully open list. A

total of 15 e-mails were sent.

After reviewing this initial e-mail trial, a second tranche of e-mails was sent to a

further 25 authorities at the beginning of April. This time, the FOI route was used

where there was no specific e-mail address or feedback request on the open data

webpage. Of this new selection, the smaller authorities were omitted, due to their

limited scale of activity. There remained, therefore, in this second tranche several

routes for e-mail correspondence.

All replies were analysed to determine any themes or issues raised in response to

the questions. The results are detailed in the next chapter.

The approach was fairly rough and ready in relation to gauging responses. There

was a time issue. Direct responses, if given, came fairly swiftly, whereas FOI

requests had an inherent delay; there is a 20 working day time limit for first

responses to FOI requests. The decision not to do FOI requests was justified in the

early stages of research, especially where authorities had open data departments


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and specific contacts. However, as already indicated, having a direct e-mail contact

or dedicated web address was no guarantee of response.

The use of specific questions has its advantages; as indicated it is not expensive and

a greater number of authorities can be reached. However, there are disadvantages

too. Due to lack of time and resources, only one section of the open data community

was contacted in this way, local government, thus possibly limiting the type of

response. The respondents are tied to answering the specific questions and

response rates can be low, (Kumar, 2005).

The time frame of the FOI requests meant that e-mails were sent out during

continuing research. The questions asked were, to some extent, a leap forward, a

far more generic question about the open data movement itself could have been sent

to all local authorities using this route. However, the author feels that this would

have led to the research lacking depth, been a major exercise in terms of time and

resources and would not have fitted well with the question posed.

Interviews

In addition to the above e-mail research, a number of unstructured interviews took

place,14 in all, in the period from January 2014 to beginning of May 2014.

The unstructured interview was chosen as an additional method of data collection as

it opened up possibilities of talking to a wider range of individuals either involved inthe open data community or who worked in an area dealing with data analysis,

communication and manipulation. That being said, the characteristics of this group

are varied and the research has had to rely on the serendipitous nature of contacts

to obtain the opportunity to carry out these interviews.

There are a number of advantages of an in depth interview; it is useful when

discussing complex issues (which this is), the subject can be discussed in depth,

questions are less likely to be misunderstood and a wider section of a community


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can be asked. However, such interviews are time consuming, can be lead by the

bias of either the interviewee or interviewer, or both, and much depends on the

quality of the interaction, (Kumar, 2005).

The purpose of the interviews was to obtain unique information and interpretation of

the open data process held by those persons interviewed and to find out from those

who worked on open data projects or with data what their experience was, which the

author was unable to observe herself, (Stake, 2010).

The sample of interviewees was varied. Some could have been considered to beexpert. Others were connected through working with data and technology and had

an interest in the possibilities of open data and how it might affect their working life

and, by nature of their experience, had valuable insights. This lead to problems in

analysing the interview data as the nature of the interviews differed. Problems arise

in mediating between the input of the interviewer (in this case the author), the aims

of the research and style of the interaction that took place, (Flick, 2002).

The questions in unstructured interviews evolve during the course of the interview. It

is a process of open discovery; one interview can influence the questions and

outcome of the next and so much could depend on the order in which the

participants are interviewed and the effect on the interviewer, (Collis and Hussey,

2009).

As this paper is exploratory in nature, the unstructured interview was considered an

appropriate method to use to identify themes and issues, which could be compared

to those found in current literature. This could then highlight avenues of further

research or add weight to the further discussion in relation to the question posed.

Alternative


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An alternative approach would have been to organise focus groups to discuss open

data. However, time and resources were not sufficient. Further opinions could also

have been gained using social media, such as LinkedIn, and posting a

questionnaire. The research question posed is a restrictive factor, however, as a

general questionnaire would have to be aimed at people who do not know about the

concept of open data and additional information required to facilitate a specific

question. It was felt this would make a questionnaire too wordy, and the

disadvantages of such a method would be magnified; that the response rate would

be low and there would be a self-selecting bias, as in any community there are those

who answer questionnaires and those who dont, a systematic bias, (Wright, 2005).

There is an on-line community on the data.gov.uk platform, but on reviewing this, it is

mostly populated with questions about specific datasets and technical problems and

none of the posts get many replies.

It would perhaps, have been more beneficial to develop links to one specific authority

and develop a case study considering the opening up process. However, this would

have taken time and was not within the scope of this project.


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Chapter 4

4.1 Analysis of e-mail responses

Of the 40 e-mails sent, 21 responses have been received, a 52.5% response rate.

This is a good response rate for such a small sample but it should be noted that 17

requests went via FOI route, where a response is required. In addition, the number

of replies bears no correlation to the breath of the answers to the questions asked.

As exploratory research into a new phenomenon, the results do present a (limited)

snapshot of the current situation. When the question asked requires an opinion,

there is no requirement under the Freedom of Information Act to respond; it was

refreshing to note, therefore, that some did.

The responses were varied; much depended on the route the e-mail took. Many of

the replies from FOI departments were short and curt. Those that were sent to, or

reached, someone involved in open data in some way, elicited fuller responses.

Most of the responses were concerned with obligations of the specific authority

under the theme of transparency; of the 20 replies, 4 specifically referred to the Local

Government Transparency Code (appendix 5). Two of the larger authorities referred

to the forthcoming directive regarding, EU procurement (appendix 5) feeling this

would cover open data.

If this small sample reflects the overall view of all local authorities, then the stance

taken by the Shakespeare review, (Shakespeare, 2013) and indeed the subsequent

PASC review, (PASC, 2013) that legislation is not required regarding procurement

may well prove ineffectual. Two respondents indicated this policy/ recommendation

was really only for central government. In times of austerity, conceptual ideas

regarding potential efficiencies and possible economic benefit for a locality/region willnot be embraced unless there is a specific requirement to do so.


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All of the fuller replies concurred this recommendation was very complex, where

there were diverse stakeholders both outside and within the organisation. What can

be seen from the variety of responses is knowledge of the open data initiative is far

from universal; some councils are looking forward proactively to the implications of

such a major policy whilst others are reactive. It cannot be assumed that just

because central government is pushing for such an agenda, it will be uniformly

adopted. Councils are not heterogeneous; the complex layers of local government

will have an impact on approaches. The approaches are in relation to transparency

issues in the main, with accountability and economic growth playing far from equal

roles.

However, the number of replies and full responses may be considered a far from

sufficient sample; in order to gain more insight, more quantifiable questions should

be asked, and the statistics should be further manipulated to consider the size of the

authority replying.

In relation to the question about the procurement process, only one authority had

added an open data policy requirement. Some replies indicated that the new

transparency code would help with this; only one reply stated they had been looking

at procurement before it became the topic of the review. One authority replied there

would be quite naturally objections from the private sector regarding commercially

sensitive information, whilst another, stated until they (the local authority) had

understood their role with regards open data, engaged with the community and

developed a process, it would not be logical to move onto procurement.

It also seems that there may be some confusion as regards how far reaching this

recommendation is. There is already under the transparency code a requirement for

tender contract details to be openly available, which is to be expanded in the new

code. Contract details are only part of what is covered by Recommendation 9,

(Shakespeare, 2013), as further evidenced by the draft procurement document

recently put on-line for consideration by The ODI, (The ODI, 2014, GitHub, 2014).


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Those who recognise there may be issues of commercial sensitivity presumably

realise an open data policy goes further than publishing the tender agreement;

others clearly think that publishing tender contracts is all that is required.

The subject of standards was only addressed in some of the fuller answers received.

Two replies mentioned the work done by LeGSB, the Local e-Government

Standards Body, that has been set up to promote e-standards and sees such

standards as underpinning, 'efficiency, transformation, and transparency of Local

Public Services in the UK', (Legsb.i-network.org.uk, 2014). Part of the larger

iNetwork, (iNetwork, 2014) a community of public sector organisations, their 2014/14

programmes includes connected procurement, which could well include theimplications of open data and Recommendation 9, (Shakespeare, 2013).

At present, therefore, compliance with format is seen to be the main criteria to meet.

Emphasising, what can be gleaned from this small sample, that consideration of

standards has not yet become an issue for debate, as data sharing and open data

itself is still relatively new. How it is going to work effectively is not a matter of major

concern at present. This is a generalization of something quite complex, bringing

together the processes and standards of varying departments with different goals

and cultures within an authority. In only one reply, however, was the innovative

nature of open data and the change management required referred to.

4.2 Analysis of interviewskey themes

A total of 14 interviews and two e-mail responses were analysed, further details

shown in table 2, on the next page.

Apart from the relatively small sample, there is clear bias as the majority of those

questioned were already engaged in working with open data.


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Unstructured interviews - method8 Face to face

2 Skype

4 Telephone

2 Additional e-mail responses

Unstructured interviews - interviewee description7 Public sector

9 Private sector10 Involved with open data in some capacity

2 Working with data/ data analysis2 Not directly involved but interested in open data initiatives

2 No connection with open data at all.

Table 2: Method and description of unstructured interviews.

Some strong themes emerged from the interviews, compiled under the following

headings, notjust the technology, riskstandards and qualityand finally culture .

In reality the themes overlap, as has been recognised in other studies, such as Carla

Boninasrecent report on business models, challenges and opportunities and the

value of open data, (Bonina, 2013).

Not justabout the technology

In some ways this could be seen as a rallying cry for those who wish to increase

engagement with opendata across organisations. Those interviewed who worked

with opening up data felt the technological factors relating to the actual release of

data, through a platform or website, were not such a problem. Rather, the issue is

context and findability, with the question of control and ownership preventing furtherforays into the opening up process.Recognised in both sectors and emphasised

effectively in a presentation by Anders Quiztau of IBM, (Quitzau, 2013). An

indication, that mainstream global IT companies have recognised the increased

interest in opening up and have developed products to facilitate the process.

Both private and public sector interviewees concluded that sharing information will

mean the breaking down of silos within organisations, which would lead to more

efficiency, but this is difficult to assess or put a value on.


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Those involved in open data considered who controlled the data and in what form,

together with knowledge of what data is available, was just as, if not more important,

than the technology involved. Isolating the concept of open data within the confines

of technology, effectively the IT department and information management was seen

to be a disadvantage. The technology should be seen as a tool, used to make

information more available. The cultural and operational problems were more of a

complication.

Considering the inclusion of the private sector when in partnership or service to local

government, a question raised by two of the interviewees concerned the local

authoritysduty towards the local economy. An open data policy to a large national

or international company may just result in the adoption of a new process; to a small

local firm it would mean an additional complexity or capability they do not have. The

complication being, how far does a local authority facilitate the opening of data held

and generated by a private company? Should there be levels of openness

dependent on the type of tender and size?

In the private sector, being open is an organisational strategy, (van Veenstra and

van den Broek, 2013) and concerns either collaboration or transparency; these are

two very different drivers, as one interviewee commented. More and more

operational data is predicted to become real time with the advent of the internetof

things, (some transport data is already real time). In industries, such as health, the

availability of such data changes how services could be delivered, but they do not

necessarily have to be fully open.

All the interviewees were concerned with how an open data policy would be

measured and what would be the criteria for success. This is unknown territory, for

where there is social good and efficiencies but not necessarily economic growth,

how can this be measured? How would such differing consequences be measured

through key performance indicators? As one interviewee commented, how can this

be integrated into a tender for a service?


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Risk

Those in the private sector not engaged in opening up data, cited risk as the major

factor why companies would not actively pursue an open data policy. Risk includes

losing competitive advantage, especially when considering operational data. An

example cited was environmental data being opened and analysed by competitors to

obtain details about productivity. This is an interesting point to consider, but may be

more a perception or fear than fact. Such perceptions can be a strong influence; the

loss of competitive advantage would be considered a failure. As one interviewee

commented, in a culture where you cannot afford to fail, there will be no culture of

seeking potential. Another interviewee felt that if a firm thought their competitiveadvantage would be compromised with the requirement to open up certain data, they

might not even tender at all. This would be a risk to local government in distorting

the market and compromising competition.

Financial risk is also a factor. Losing competitive advantage would obviously affect a

companys financial situation, and might increase the cost of projects. Much has

been made of the potential of open data, but potential does not lead to a measurable

rate of return. Interviewees in both sectors felt in the current economic climate there

would be a lack of funding. The lack of business models was seen to contribute to

this lack of willingness to invest. Yet economic value is only one of the beneficial

factors associated with opening up data.

Security risks were also a major feature in discussions, in terms of privacy and data

protection. This is a topic that was strongly associated with health care data in

particular. Those engaged in open data projects cited security or data protection as

the main reason departments did not engage in opening. The redacting of data was

considered a cost that may not be justified or was operationally difficult. Two

interviewees who work with the public sector, however, commented that this risk was

somewhat misunderstood; that data protection and privacy were not the same.

Protecting privacy does not necessarily mean that certain elements of data cannot


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well as externally, leading to increased efficiency; as one interviewee stated, there is

information asymmetry within organisations as well as outside. Limited opening up

within an organisation would have benefits. This could lead to the curious effect of

one department opening data, only to find that those who most use the data are from

the same organisation. What could be described as goingoutside to come in,as

was observed by an interviewee engaged in open data projects. Indeed, in some

respects this can be evidenced in the user feedback the Surreyi platform has

received. All of the users quoted came from the public sector, where finding the data

would not have been impossible, the use of the platform made it far easier, quicker

and efficient, (Surreyi.gov.uk, 2014)

Standardisation was considered a problem by the private sector interviewees

engaged in analysing and visualising data and also those engaged in trying to open

up databases within local government. Legacy systems that were contracted to

before the advent of the concept, meant data tied to the system in some cases, not

the provider. Datasets that could be of use with other departments could not be

accessed and merged, there was no interoperability. In fact, this was considered a

problem across the board, by everyone who either analysed data, provided systems

and software to manipulate the data and those who wanted to contextualise and

create metadata.

Culture

The issue of culture is very much tied up with that of the first theme itis not just

about technology. Whilst all those talked to who were involved in opening up data

recognised the aims involved were transparency, accountability and economic

growth, every interviewee also recognised the value of information sharing, whether

open or not.

The premise that information is power is very much embedded within all

organisations. Two interviewees alluded to this problem, not only in relation to


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management but also in terms of how departments are financed. Budgets are

allocated within boundaries; savings lead to a loss of funds to another department, a

lost budget, leading to a negative feeling towards opening up and sharing to create

efficiencies.

Cultural attitudes to valuing the opening up of data also play a part. For several

interviewees, unless there was some benefit to those that facilitated opening up,

either economically or as part of their performance reviews, there would be no

motivation to do so, particularly, where the control or holding onto information had

previously been a way of manipulating power or used in negotiation. This is referred

to in detail by Peled (2011).

Finally, in terms of culture, the matter of trust was discussed by several participants,

trust within an organisation, between departments and trust in regard to the reuse of

data, outside, beyond the organisations sphere of influence. This could only be

gained or strengthened through experience and support (validation). Feedback was

seen as essential for those involved operationally.

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J Carr - Open Data - Public and Private Sector approaches

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