Svein Ølnes
email: sol@vestforsk.no

Beyond Bitcoin Enabling Smart Government Using Blockchain Technology

Keywords: e-Government, bitcoin, blockchain, information infrastructure

The new technology Bitcoin has got a lot of attention since it was presented in late 2008 and implemented early 2009. However, the main attention has been to the currency and not so much the underlying blockchain technology. This paper argues that we need to look beyond the currency and investigate the potential use of the blockchain technology to enable smarter governments by utilizing the secure, distributed, open, and inexpensive database technology. The technology is discussed in the perspective of an information infrastructure to investigate its full potential. After a literature review of Bitcoin publications, with a special emphasis on eGovernment literature, the paper presents a relevant use case highlighting the innovation potential of the new technology. The literature review shows that Bitcoin is absent from the e-Government literature. The use case presented shows that Bitcoin could be a promising technology for validating many types of persistent documents in public sector.

Introduction

Once in a while technological breakthroughs occur that open up a whole new world of possibilities. Internet itself was a breakthrough like this, and the invention of the web, with its HTTP protocol built on top of the Internet the protocols, likewise opened up a new world of possibilities. To many the breakthrough in trustless commerce and payment made possible with the Bitcoin protocol holds a bit of the same potential as the aforementioned examples [START_REF] Andreessen | Why Bitcoin Matters[END_REF]. For the first time in history a system has been made that enables secure transactions to be carried out in an unsecure, unreliable environment like the Internet without the need for a trusted thirdparty. The way this is done is explained in more detail in section two.

Public sector faces a number of challenges, not least in more cost efficient use of ICT and better interoperability between systems, as Codagnone and Wimmer (eds.) states [START_REF] Codagnone | Roadmapping eGovernment Research: Visions and Measurestowards Innovative Governments in[END_REF]. Dawes et al. looks at information boundaries and the necessity of going from "need to know" to "need to share" and suggests public sector knowledge networks [START_REF] Dawes | From 'need to know' to 'need to share': Tangled problems, information boundaries, and the building of public sector knowledge networks[END_REF]. For higher education, which is the sector where the use case discussed in this paper comes from, the accelerating trend of globalization [START_REF] Altbach | Trends in global higher education: Tracking an academic revolution[END_REF] puts even more pressure on finding solutions that are interoperable on a global scale. Proving the authentication of documents is a general issue for public sector and finding smarter solutions that scale globally and is cost efficient can help both cutting public sector costs and increase the quality of these services.

The Bitcoin blockchain has global reach and can be viewed as an open, distributed, and trustless database on the Internet. Trustless means that it requires no third-party to secure transactions; the trust lies in the software only. Bitcoin can be seen as a system for proving ownership both to assets and currencies [START_REF] Böhme | Bitcoin: Economics, Technology, and Governance[END_REF]. It was invented by Satoshi Nakamoto [START_REF] Nakamoto | Bitcoin: A peer-to-peer electronic cash system[END_REF], presumably a pseudonym for a person or a group of persons. The peerto-peer system was released as open source software in 2009 and it enables users to transact directly without an intermediary [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF].

Currently the Bitcoin blockchain is limited to handle a theoretical maximum of seven transactions pr. second [START_REF] Zohar | Bitcoin: under the hood[END_REF] and is therefore not, as yet, ideal for high volume transactions. However, for efficient storing of more persistent objects and assets it is ideal. The low cost of transactions (transaction fees are typically a few cents) combined with a high degree of security makes promises for a cost efficient and secure way of storing assets of various types and in addition achieve a better interoperability due to the open, distributed, and global architecture. This can also comprise public sector assets like certificates, diplomas, licenses and more.

The research objectives of this paper thus is  to give an overview of the Bitcoin literature in general and in e-Government in particular  to study the potential for using Bitcoin technology in public sector services The objectives will be met by first carrying out a thorough literature review related to Bitcoin and then to study the Bitcoin technology in an information infrastructure perspective. Finally a relevant use case from higher education will be explored to shed light on the possible use of this technology in public sector.

Bitcoin is used throughout the paper as a proxy for crypto-based currency systems. Bitcoin is both a distributed infrastructure (the blockchain) and a currency and the paper tries to be consistent in denoting Bitcoin the infrastructure with a capital 'B' and bitcoin the currency with a small case 'b'.

The following section gives a brief explanation of the Bitcoin technology, to the extent necessary for the paper. This is a conceptual paper and the main method of a systematic literature review is described in section three together with a discussion of the use case method. In section four Bitcoin as an information infrastructure and platform for innovation is discussed to investigate Bitcoin's broader potential. A use case relevant for public sector is explored and discussed in section five before, finally, section 6 concludes with open problems and suggestions for further research on the use of this promising technology.

What is Bitcoin?

Bitcoin is a virtual currency connected to a distributed ledger (the blockchain) first presented to the Cryptography mailing list by the posting of a white paper [START_REF] Karlstrøm | Do libertarians dream of electric coins? The material embeddedness of Bitcoin[END_REF] from the author named Satoshi Nakamoto. The white paper was titled "Bitcoin -A Peer-to-Peer Electronic Cash System" [START_REF] Nakamoto | Bitcoin: A peer-to-peer electronic cash system[END_REF]. The Bitcoin system enables users to transact directly on an open and unsecure network, like the Internet, without the use of an intermediary.

Like most innovations Bitcoin also builds upon earlier innovations. David Chaum introduced blind signatures when creating DigiCash, the first digital cash system [START_REF] Chaum | Blind signatures for untraceable payments[END_REF]. Adam Back's HashCash method presented in 1997 [START_REF] Back | Hash cash: A partial hash collision based postage scheme[END_REF] and introduced a hash-based proof-of-Work method also used in Bitcoin [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF]. Wei Dai's b-money [START_REF] Dai | B-money[END_REF] took Back's ideas further and suggested a crypto-anarchy system where full anonymity was the central feature. Finally Nick Szabo presented his idea of Bit gold, a system that comprised most of the previous mentioned systems in a digital gold system that was very close to the final Bitcoin system [START_REF] Szabo | Bit gold. Website/Blog[END_REF].

However, the fundamental problem with avoiding double-spending was still unsolved until the advent of Bitcoin. The problem of establishing trust among untrusted parties, like a transaction between two unknown parties on the Net, is generally known as the Byzantine Generals' Problem and was first formulated by Lamport et al. [START_REF] Lamport | The Byzantine generals problem[END_REF]. The problem was related to computer systems' handling of conflicting information from different parts or components. How can the computer, or in Bitcoin's situation the network, decide which message is the correct one when it gets conflicting messages? Bitcoin has solved this in a proof of concept way.

Bitcoin solved the problem in an elegant way by using the afore-mentioned proofof-work method inspired by HashCash and combined with a consensus based system among the Bitcoin peers [START_REF] Nakamoto | Bitcoin: A peer-to-peer electronic cash system[END_REF]. In Bitcoin the users effectively "vote" with their computing power to prevent double-spending attacks [START_REF] Gervais | Is Bitcoin a decentralized currency?[END_REF]. The security relies on the presumption that the cost of compromising the system must outweigh the profit of doing so.

The most interesting feature with Bitcoin seen from an eGovernment perspective thus is the blockchain technology. Although the blockchain marks the really interesting technology it is crucial to understand the deep interlinking between the currency bitcoin and the underlying blockchain technology [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF]. One cannot exist without the other (ibid.). Even if the blockchain can hold assets other than the currency bitcoin, the currency is the central component in transferring ownership of assets and it is the incentive for the miners who guarantee the security of the system (ibid.).

Bitcoin relies on two fundamental technologies from cryptography: public key cryptography for making digital signatures [START_REF] Schneier | Applied Cryptography-Protocols, Algorithms[END_REF] and hash functions for validation [START_REF] Böhme | Bitcoin: Economics, Technology, and Governance[END_REF]. A Bitcoin transaction is a digital signature which signs a transaction containing the payers address, the recipients address, and the amount (of bitcoins) transferred [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF]. The transaction is propagated to the Bitcoin network, e.g. the nodes comprising all users of the Bitcoin core program, and eventually bundled with other transactions to be included in a block (ibid.). The new block is attached to the blockchain through a mining process where computer power is used to solve a mathematical puzzle, the proof of work (PoW) part [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF]. The blocks can also store other information and instructions and this is where the asset component comes in.

Although the virtual currency itself could have a place in public sector use, this paper looks at the potential use provided by the blockchain technology. Bitcoin provides an infrastructure on which new applications and services can be built. The Internet itself represents an important information infrastructure for permissionless innovation both in private and public sector, and the Bitcoin infrastructure holds many of the same promises in its field, as will be elaborated further on in section four.

The paper is of explorative and conceptual nature and relies on a systematic literature review [START_REF] Briner | Systematic review and evidence synthesis as a practice and scholarship tool[END_REF] of Bitcoin-related papers. In addition to the systematic approach a "snowball" method has also been used (ibid.). For the illustration of potential use of Bitcoin technology in public sector a selected use case with special relevance to public sector has been studied.

It is important to emphasize that the conceptual style of the paper is necessary since the use of Bitcoin is almost non-existent in public sector, something the literature study also shows. The only part of Bitcoin paid attention to by public sector is understandably regulatory questions concerning the currency.

For the Bitcoin status in eGovernment literature the newly updated e-Government Research Library i (EGRL) v. 11.5, was used as the primary resource. The EGRL library has an extensive overview of e-Government related research currently containing 7,899 of predominantly English-language, peer-reviewed work in the study domains of electronic government and electronic governance [START_REF] Scholl | eGovernment Reference Library (EGRL) version 10[END_REF]. For the broader coverage of Bitcoin-related academic publishing the Thompson Reuters' Web of Science and Google Scholar were chosen. Finally the source "Bitcoin Academic Research" compiled by Brent Scott [START_REF] Scott | The Heretic's Guide to Global Finance: Hacking the Future of Money[END_REF] was categorized into major research disciplines. Scott's compilation using well-known literature resources like JSTOR, Science Direct, Springer Link, SSRN, Taylor & Francis, Google Scholar, Wiley Online Library and many more shows a growing number of Bitcoin-related publications.

Tabell 1. The growth of academic Bitcoin publications [START_REF] Scott | The Heretic's Guide to Global Finance: Hacking the Future of Money[END_REF]

Year

No The table below shows a categorization of the papers found using different sources. For the three first sources; the EGRL, Google Scholar, and Web of Science, only search phrases related to Bitcoin/blockchain and e-Government is shown. For the Bitcoin Academic Research source the whole catalogue was categorized into the categories technology, economy, and legal and regulatory. The categories were a result of the screening of the papers. The categorization was done based on the title, the summary of the papers, and the journal. In case of ambiguity the complete paper was downloaded and examined. Searches for "bitcoin" or "blockchain" in the e-Government literature database EGRL 11.5 did not give any results nor did the searches for "bitcoin e-Government" or "blockchain e-Government" in Google Scholar or Web of Science. In addition to "e-Government" the word "eGovernment" was also included.

The categorization of the Bitcoin Academic Research compilation [START_REF] Scott | The Heretic's Guide to Global Finance: Hacking the Future of Money[END_REF] shows that most of the publications listed fall within the fields of technology and economy with an almost perfect balance between the two research fields. There are also quite a few publications dealing with legal questions like regulation and governance. The category "other" contains work in different research fields, e.g. environmental issues, social science etc.

From the literature search we can conclude that Bitcoin and crypto currency technology is absent from e-Government research.

We have also used a case study approach [START_REF] Yin | Case Study Research: Design and Methods[END_REF] and studied a relevant use case to shed light on the possibilities for using Bitcoin technology in public sector services. The use case was chosen because of its high relevance for public sector. The use case method is especially useful in situations where the researcher has little or no control over the object to be studied, and for its usefulness in answering "how" and "why" questions [START_REF] Yin | Case Study Research: Design and Methods[END_REF]). This is the case for Bitcoin in e-Government context where there to date are no obvious use cases to study.

Bitcoin as an Information Infrastructure

In order to be a potential valuable technology for use in public sector Bitcoin needs to be more than a payment solution. The technology needs to be a platform capable to foster innovative derivatives. Kazlan et al. [START_REF] Kazan | Towards a Framework of Digital Platform Disruption: A Comparative Study of Centralized & Decentralized Digital Payment Providers[END_REF] Information infrastructures (IIs) on the other hand represent another level of complexity by combining social and technical dimensions [START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF]. Hanseth and Lyytinen (ibid.) define an information infrastructure as "a shared, open and unbounded, heterogeneous, and evolving socio-technical system consisting of a set of IT capabilities and their user, operations, and design communities". This definition highlights what they call the emerging properties of IIs. In addition they also point to the structural properties, e.g. organizing principles and control. Examples of IIs are Internet itself, electronic market places, EDI, and wireless service infrastructures to mention a few (ibid.). Hanseth and Lyytinen [START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF] point to the considerable benefits successfully constructed and implemented IIs hold, as exemplified by Internet, but also at the potential risks involved in designing such systems, again exemplified by the nation-wide e-health system i UK, the ICT part of the National Health Service (NHS). If Bitcoin can be showed to share some of the core properties of an II we can assume that the potential for far-reaching application, including public sector, is high.

IIs distinguish themselves from traditional classes of IT solutions such as IT capabilities, applications, and platforms by being more complex [START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF]. IIs are thus seen as a more complex unit than platforms. A main difference between an II and a digital platform is the central control of platforms in contrast to the distributed and dynamically negotiated control of IIs (ibid.).

Bitcoin can be seen as an information infrastructure in that it meets the definition. The characteristic properties of an information infrastructure and how these applies to Bitcoin is showed in the table below and discussed in more detail below the table. The table builds on Hanseth and Lyytinen [START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF], p. 3. Because of the openness an II should also be heterogeneous implying that social and technical diversity should increase during the lifetime (ibid.). Bitcoin is a fairly new technology, but already we see great social and technical diversity with applications and platforms like altcoins (more than 3,300 to date3 ), smart contracts [START_REF] Wood | ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER[END_REF], sidechains for reducing the load on the main Bitcoin blockchain [START_REF] Back | Enabling blockchain innovations with pegged sidechains[END_REF], micro payments systems built on top of Bitcoin [START_REF] Poon | The Bitcoin Lightning Network: Scalable Off-Chain Instant Payments[END_REF], coloured coins to represent different types of assets [START_REF] Rosenfeld | Overview of colored coins[END_REF], Bitcoin blockchain for secure domain name handling [START_REF] Ali | Blockstack: Design and Implementation of a Global Naming System with Blockchains[END_REF] and many more digital implementations as well as physical constructions like ATMs.

Also because of the openness IIs should evolve constantly (ibid.). Again Bitcoin, including the blockchain technology, is not mature. However, already in the first seven years the technology has shown a remarkable development from being used by a handful of persons the first year to today's millions of users (nodes) and links [START_REF] Kondor | Do the rich get richer? An empirical analysis of the Bitcoin transaction network[END_REF], high investment rate indicating lots of start-ups, and a continuous expansion also in terms of diversity of components and services added to the technology.

When looking at the structural properties the organizing principle of an II should be a recursive composition of IT capabilities, platforms and infrastructure over time [START_REF] Edwards | Report of a Workshop on 'History & Theory of Infrastructure: Lessons for New Scientific Cyberinfrastructures[END_REF]. The bootstrapping process by experimenting is also evident in the Bitcoin development first designed as a payment method and later having evolved into a range of possible uses. The bootstrapping process for Bitcoin and other crypto currencies is also special since it is both a technology and a financial structure. The system is especially vulnerable in the bootstrapping process due to the proof of work method. It will be relatively easy to compromise such a system in the beginning because of the low requirements for PoW resources. This will also increase the "first mover advantage" because over time the infrastructure will grow more and more robust while competing systems will have trouble bootstrapping.

Finally the structural property of control typical for an II is distributed and dynamically negotiated one [START_REF] Weil | Leveraging the new Infrastructure[END_REF]. Bitcoin is clearly a distributed technology with no central control. The main purpose of its design was to avoid central control in the form of a trusted third-party. It was presented as a peer-to-peer technology from the beginning [START_REF] Nakamoto | Bitcoin: A peer-to-peer electronic cash system[END_REF]. The recent debate over the block size [START_REF] Croman | On Scaling Decentralized Blockchains[END_REF] also shows that no party is in control of changes to be made and that these changes must be negotiated dynamically: miners have their say, full node clients have their say, and core developers also have their say, but none of the groups can dictate the terms. This has been, and is, a very heated debate and the community has not reached a conclusion yet [START_REF] Pilkington | Blockchain Technology: Principles and Applications[END_REF].

The use case presented in the next section will be discussed in light of digital platforms and information infrastructures.

Use Case: Academic Certificates Stored on the Blockchain

Andreas Antonopoulos is one of the most experienced Bitcoin technologists and the author of "Mastering Bitcoin" [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF]. In addition to serving on the advisory board for many start-up companies in Bitcoin technology he is also a Teaching Fellow at the University of Nicosia where he teaches the online courses in digital currencies. After finishing the first teachings of the MOOC-based 4 course "Introduction to Digital Currencies" he decided to store the academic certificates for all the students who successfully completed the course on the Bitcoin blockchain [START_REF]Academic Certificates on the Blockchain[END_REF]. After all, one of the great promises of the blockchain technology is that it can serve as a decentralised, permanent, and utterly secure store for all types of assets, not just as a currency. That is what makes it interesting also for public sector use.

The following basic requirements were set up before the project of storing the academic certificates on the blockchain started: a) the process should involve no other services or products other than the Bitcoin blockchain, b) the process should allow someone to authenticate a University of Nicosia certificate without having to contact the University of Nicosia, and c) The process should allow someone to complete the process even if the University of Nicosia, or more likely their website, no longer existed. The University of Nicosia is a private university, but this use case is just as relevant for a public university.

The process of storing the academic certificates on the blockchain followed these steps [START_REF]Academic Certificates on the Blockchain[END_REF]:

Hash of the individual certificates. A hash of a certificate is at the core of the process. A hash function is a one-way function that takes any arbitrary data as input and produces a string with a fixed number of characters [START_REF] Schneier | Applied Cryptography-Protocols, Algorithms[END_REF]. In Bitcoin the SHA-256 hash function is used [START_REF] Antonopoulos | Mastering Bitcoin -Unlocking Digital Cryptocurrencies[END_REF].

Index put on the blockchain. Instead of storing each individual certificate on the blockchain an index document containing the hashes of all the certificates were created and the hash value of the index document stored on the blockchain. The hash of the index document was entered to the blockchain in an unspendable Bitcoin transaction to serve as the permanent record underpinning the whole approach.

Timing and instructions. The certificates had to be self-verifying the timing of entering of the hashed index on the blockchaincritical.

Public access. The index document containing the hashes of all the individual certificates is published on the University of Nicosia homepage. But if this was all, there would be no use for the blockchain. For the process to be truly decentralised people should be able to find a copy of the index document anywhere on the web and compare it to the index document on the blockchain.

The verification process is carried out in two steps; one for verifying the index document and the second for verifying the particular certificate: Verifying the index document. Ensure that a valid index document from the University of Nicosia is used. The hash of the index document should be the same as the hash stored on the blockchain, in the specified timeframe.

Verify the certificate. Once the index document has been verified, a SHA-256 hash of the certificate (in pdf) should be compared to the hash of the same certificate listed in the index document. If the hash values are similar, the certificate is authentic. Of course, the comparison of the hash values only guarantees the authenticity of the certificate, not that the person who sent the certificate is the same as the person on the certificate. That has to be validated in other ways.

The use case above has shown one possible use of the Bitcoin blockchain technology for public sector. All organizations issuing certificates, licenses etc. could benefit from the new technology, as this use case shows. The use case from the University of Nicosia has pointed to a couple of challenges that should be investigated more in depth in order to arrive at a best practice for storing certificates and licenses on the blockchain.

The Bitcoin technology fits the definition of a digital platform and the characteristics of an information infrastructure can also be found in the technology, as shown in table 3. Its dispersed and distributed "ownership" is in line with the central attribute of an II. Installed base is another key element in an information infrastructure and denotes technical and non-technical elements illustrating the network effects determining the development of the infrastructure [START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF]. The installed base in this case is the organisational, economic, and legal factors governing today's public service II. The legal factors are of special importance, as is also discussed in many of the publications listed in section three. However, the legal and regulatory factors discussed in these papers are mostly about regulating the currency and the payment system. The use case described above, and similar uses of Bitcoin, escapes these worries since the payment part is just a necessary side effect and not the goal itself. That is the case with all use cases belonging to so-called "smart contracts" use of Bitcoin. The currency is used only as a token in these cases.

An information infrastructure without direct Government control might seem scary for public sector. When considering Bitcoin as an interesting technology in e-Government we need to review history and be reminded of the "battle" between global network standards in the end of the 1980s, beginning of 1990s. Governments had the choice between the controlled OSI protocol and the Internet protocol, and most of them chose the OSI protocol. USA's Government OSI Profile -GOSIPbecame the standard for many other nations' OSI profiles, e.g. NOSIP -Norwegian OSI Profile [START_REF] Ness | Tilkoplet -En fortelling om Internett og Forskningsnettet i Norge. Fagbokforlaget[END_REF]. Internet's rise in popularity made it a de facto standard that soon overrun the OSI protocol, not least because the OSI standards struggled to deliver working and interoperable services (ibid.). Internet became the national and international standard for global communication not because of national priorities, but despite them. This is something to bear in mind when considering a technology that uses the same distributed model that Internet itself.

Conclusions and Further Research

This paper has shown that the topic Bitcoin technology is absent from e-Government literature. The major part of academic publishing on Bitcoin has been in the fields of technology, economy, and regulation. Of course, one explanation why Bitcoin and blockchain is absent from the e-Government literature could be that the technology does not have any potential benefit for public sector, but that is hardly likely. At least researchers should provide arguments for why this could be the case.

Bitcoin meets most of the core requirements for an information infrastructure and is thus well positioned to have a broad impact on future digital innovation. The use case detailed and analyzed in the chapter above shows that Bitcoin also has a great potential for use in public sector. Storing certificates on the block-chain is a costeffective way of storing and securing vital information. The use case shows that this is possible for certificates, but also that this could be a promising technology for all types of permanent, or relatively permanent, public documents. Other examples could include contracts of different types (e.g. procurement contracts), licenses (e.g. driving licenses), and many more given its information infrastructure capabilities.

Having a great potential is not the same as having a great success. There are quite a few examples of technologies with great potential nevertheless failing to be embraced and included in the technologies used for everyday service provision.

However, given the promising benefits the Bitcoin technology holds it is important that also researchers in the e-Government field starts to investigate it. There are a lot of questions that need to be answered by doing more research. Among the many research questions are how can the Bitcoin blockchain technology help innovate the development of digital services from public sector? How should the currency and the blockchain part of the Bitcoin protocol be handled by public agencies? Should public sector use a separate sidechain and if so, what would be the major threats to such a strategy? What are the important factors determining the adoption of Bitcoin technology in public sector? And with regard to Bitcoin as an information infrastructure: what is the crucial installed base determining whether Bitcoin will succeed or not in public sector?

These questions are not that different from the questions of public sector's use of Internet and the web in the beginning of the 1990s. Perhaps going back 25 years and looking at how these questions were answered can give us an idea of how public sector should approach the Bitcoin technology.

Tabell 2 .

 2 Categorization of Bitcoin publications from different sources

  define a digital platform as "a proprietary or open modular layered technological architecture that support efficient development of innovative derivatives". Bitcoin is published as open source software and is thus an open technological architecture. A number of alternative digital currencies have been created on the basis of Bitcoin's source code, all with their special features separating them from Bitcoin itself. This shows that Bitcoin is able to support efficient development of innovative derivatives and that Bitcoin as such meets the requirements applied to an open, digital platform.

Table 3 .

 3 Bitcoin as an information infrastructure

	Property	Information	Bitcoin as an II
		infrastruscture
		(in general)
	Shared	Universally and across	Yes
		multiple IT capabilities	Bitcoin is universally shared (one only need an
			Internet connection and download/install a
			wallet to use/take part)
	Open	Yes, allowing unlimited	Yes
		connections to user	Bitcoin is open for any users and offering an
		communities and new	infrastructure for "permissionless innovation".
		capabilities
	Heterogenous	Increasingly	To a certain extent.
		heterogeneous both	Bitcoin has already generated many new
		technically and socially	applications and platforms (thousands of
			altcoins, emerging sidechains, foundation for
			new platforms like Ethereum 2 )
	Evolving	Yes, unlimited by time or	Yes, although it is a bit early to say

An II is shared across multiple communities in a multitude of ways (

[START_REF] Hanseth | Design theory for dynamic complexity in information infrastructures: the case of building internet[END_REF]

and should in principle exhibit unbounded openness by including new components in many, including also unexpected, ways. Bitcoin is universally shared by adhering to the protocols of the web (the HTTP protocol) and is released as open source software. Components added to the Bitcoin network range from several types of wallets (e.g. desktop wallets, mobile wallets, hardware wallets, paper wallets), a range of exchange services (e.g. physical ATMs, online exchange services), and mining components. Everybody can run a Bitcoin full client and such be a peer in the network, or on the other hand one can also use a light-weight version of Bitcoin; typically a mobile wallet. The mining operation of the Bitcoin system is also open although at present it requires specialized hardware in order to gain more than the cost of equipment.

Satoshi Nakamoto: «Bitcoin -A Peer-to-Peer Electronic Cash System»[START_REF] Nakamoto | Bitcoin: A peer-to-peer electronic cash system[END_REF]

Ethereum is a derivative of Bitcoin that focuses on smart, programmable contracts. It uses a separate blockchain with its own currency; named ether[START_REF] Wood | ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER[END_REF]

http://www.cryptocoincharts.info/coins/info

Acknowledgement

Thanks to Satoshi Nakamoto for giving us this radical technology to build on.


Evangelos Kalampokis

Efthimios Tambouris
email: tambouris@uom.gr

Areti Karamanou

Konstantinos Tarabanis

Open Statistics: The Rise of a new Era for Open Data?

Keywords: Open data, statistical data, open statistics, linked data, data analytics

A large part of open data concerns statistics, such as demographic, economic and social data (henceforth referred to as Open Statistical Data, OSD). In this paper we start by introducing open data fragmentation as a major obstacle for OSD reuse. We proceed by outlining data cube as a logical model for structuring OSD. We then introduce Open Statistics as a new area aiming to systematically study OSD. Open Statistics reuse and extends methods from diverse fields like Open Data, Statistics, Data Warehouses and the Semantic Web. In this paper, we focus on benefits and challenges of Open Statistics. The results suggest that Open Statistics provide benefits not present in any of these fields alone. We conclude that in certain cases OSD can realise the potential of open data.

Introduction

Today an increasing number of public authorities, international organisations and even enterprises publish Open Data [START_REF] Kalampokis | A classification scheme for open government data: towards linking decentralized data[END_REF][START_REF] Attard | A systematic review of open government data initiatives[END_REF]. Open Data refers to data that can be freely used, re-used and redistributed by anyone 1 . In the public sector, opening up government data aims to increase transparency and boost economic growth. Indeed, estimates suggest that the potential of Open Data is tremendous [START_REF] Susha | Benchmarks for Evaluating the Progress of Open Data Adoption: Usage, Limitations, and Lessons Learned[END_REF]. For example, a study conducted by the McKinsey Global Institute estimated the global annual economic potential value of Open Data to $3 trillion [4]. Against this general euphoria however, studies reveal that publishing open data does not automatically provide benefits [START_REF] Janssen | Benefits, Adoption Barriers and Myths of Open Data and Open Government[END_REF][START_REF] Kalampokis | Linked open government data analytics[END_REF]. Thus, we are still far from suggesting that the potential of open data has been realised. On the contrary, further research is needed in promising areas.

In this respect, an obvious route for further research is to understand the nature of open data. Policy documents and research in the area suggest that a large part of open data is numerical and, more specifically, concerns statistics [START_REF]European Commission: Guidelines on recommended standard licences, datasets and charging for the reuse of documents[END_REF]. Examples include demographics (e.g. census data), social data (e.g. on unemployment and poverty), economic data (e.g. number of new businesses) etc. In this paper we refer to these as Open Statistical Data (OSD). The fact that OSD is a large part of open data was the main motivation for our research. OSD are numerical hence can be easily processed and visualised while significant knowledge already exists in areas such as statistics and data warehouses.

In this paper, we present Open Statistics as a new field to systematically investigate OSD and the creation of value from them. Open Statistics reuse methods from diverse fields like Open Data, Semantic Web, Statistics, Machine Learning and Data Warehouses. More specifically, Open Statistics use existing knowledge on Open Data (such as processes and formats used to publish open data) as background environment. In this environment, Open Statistics reuse but, more importantly, in many cases redefines and extends existing methods from other areas, e.g. for data integration, analysis and visualisation. As a result, Open Statistics provide benefits that go much beyond what was possible in each separate field. This suggests that Open Statistics can actually constitute a significant field of research that, under certain conditions, could enable realising the full potential of Open Data.

The research work that we present in this paper is exploratory [START_REF] Bhattacherjee | Social Science Research: Principles, Methods, and Practices, Open Access Textbooks[END_REF] as we aim to scope out the magnitude of Open Statistics and to provide and initial understanding about it. In general, exploratory research is research conducted for a problem that has not been clearly defined. It often occurs before we know enough to make conceptual distinctions or posit an explanatory relationship [START_REF] Shields | A Playbook for Research Methods: Integrating Conceptual Frameworks and Project Management[END_REF]. As a result, we include the following activities in our approach:

-Study datasets from two open data portals at different administrative levels.

In particular we focus on the UK's national open data portal The rest of this paper is organised as follows. In section 2 we present the existing situation in OSD. In section 3 we present a major challenge for OSD reuse, namely data fragmentation. In section 4 we outline the data cube model.In section 5 we introduce Open Statistics and show how it is related to other fields of study. In section 6 we illustrate the benefits of Open Statistics while in section 7 we present the relevant challenges. In section 8 we discuss the finding while section 9 presents the main conclusions of the work and directions of future research.

Existing Situation

Today, opening government data is a political priority in many countries worldwide including the USA and the EU. As a result, an exponentially increasing amount of government data is rapidly opening. International organizations (such as the World Bank) also open up their data. A five-star model has been proposed by Tim Berners-Lee to evaluate the maturity of open data 4 .

More specifically, OSD is currently provided by governments and organisations through data portals at the international, European, national or regional level. At the international level, organisations provide OSD related to countries in data portals such as the World Bank data portal5 , the Organisation for Economic Cooperation and Development (OECD) data portal 6 and the United Nations Educational, Scientific and Cultural Organisation (UNESCO) data portal 7 . At the European level, OSD are provided through the official European Data Portal8 and the data portal of Eurostat 9 . At the national level, OSD are provided by the national open data portals (e.g. the data.gov.uk in the UK) but also by the National Statistical Offices (e.g. the Office for National Statistics10 in the UK). Finally, at the regional level, OSD are published by local agencies, cities or even boroughs of cities in local data portals such as the data portal of the city of Brussels11 and the data portal of the Camden borough of London 12 . Finally, data portals also serve as single points of access and, apart from providing data regarding their administrative level, they also provide links to datasets that are published at data portals of lower levels.

Open Statistical Data Fragmentation

As already stated, a large part of open data are numerical thus potentially easy to process and visualise. In reality however studies suggest that open data reuse is limited. In this section, we investigate practical obstacles for OSD reuse. We do not consider obstacles related to legal and organisational issues at the side of the publishers. Instead, we concentrate on the side of the end user, who is interested to reuse open data.

For the purposes of this research, we searched two major open government data portals, namely the UK data portal and the European data portal. In both case, according to our scenario, we were interested to reuse open data about unemployment.

We first searched the UK data portal for datasets using the keyword unemployment. This resulted in 122 results, which provided access to 56 files and 610 links to other portals (e.g. to the UK's Office for National Statistic) and thus to other files. We opened and examined these files one by one and find out that only 13 out of 56 are relevant to unemployment and that 7 out of 13 provide structured numeric values in a machine readable format.

Most importantly, however, those datasets measure unemployment based on different characteristics (also called dimensions). For example, we found datasets for unemployment in different geospatial levels (e.g. in the city of London, in the Camden borough, or in the different wards of Camden), age groups, gender or time duration (e.g. annual, quarterly or monthly unemployment). Relative datasets also measure unemployment using different units of measure (e.g. unemployment rate or thousands of unemployed people). Finally, different datasets may employ different methods for measuring unemployment e.g. based on the UK's Office for National Statistics (OSN) estimations, based on the number of people that claim Job Seekers Allowance (JSA) or based on the International Labour Organization's (ILO) model.

We then searched European data portal using unemployment keyword. This search returned 120 datasets mainly from Eurostat. Again, those datasets describe unemployment using different dimensions and units of measures. Different datasets also measure unemployment in different context (e.g. in the context of education and training or in regional statistics). This also means that these datasets are located in different parts of the portals.

In summary, our research revealed that searching the two open data portals for useful data on unemployment results in large numbers of datasets and links.

We call open data fragmentation the situation where collections of relevant open data are broken down into many pieces that are not close together. This definition is actually an adaptation of the definition of data fragmentation in computing.

Unemployment is not the only case where relevant data are fragmented. In the case of OSD, fragmentation is actually the rule rather than the exception. Therefore, we suggest that in order for OSD (and therefore Open Data in general) to be useful the problem of open data fragmentation has to be sufficiently addressed. We acknowledge that other obstacles already mentioned in the literature are also important. However, in this paper we concentrate on overcoming the obstacle of open data fragmentation.

The Data Cube Model

The study of datasets in both the UK and the European open data portals reveals that (a) OSD can be conceptualised using the traditional data cube (or just cube) model that was initially introduced in Data Warehouses and that (b) different datasets provide fragmented views of a cube.

Although research in data warehouses is active for more than two decades, concepts and systems lack a uniform theoretical basis with regards to models that define data cubes and operations that are performed on data cubes [START_REF] Romero | A survey of multidimensional modeling methodologies[END_REF][START_REF] Tseng | Integrating heterogeneous data warehouses using XML technologies[END_REF][START_REF] Niemi | Multidimensional data model and query language for informetrics[END_REF][START_REF] Datta | The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses[END_REF][START_REF] Chaudhuri | An overview of data warehousing and OLAP technology[END_REF]. In general, however, a data cube is specified by a set of dimensions and a set of measures. The dimensions create a structure that comprises a number of cells, while each cell includes a numeric value for each measure of the cube. Let us consider as an example a cube from Eurostat with three dimensions, namely time in years, geography in countries, and age group, that measures the employment rate. An example of a cell in this cube would define that the percentage of unemployed people between 25 and 49 years old in France in 1999 is 10.2 % (Figure 1). This conceptual cube could have been created using numeric values from multiple datasets.

Open Statistics

Open Statistics is a field aiming to systematically study Open Statistical Data (OSD). The main idea behind Open Statistics is that we concentrate only on Open Data that are actually statistics. This is a large part of all Open Data but clearly not all Open Data are OSD.

Open Statistics mainly capitalise on existing knowledge on Open Data and mainly Open Government Data. The majority of the existing body of knowledge in those areas is applicable in Open Statistics although in some cases some precaution is necessary. In this environment, methods from three other areas are reused and in some cases redefined. These are Data Warehouses and OLAP, Statistics and the Semantic Web (mostly Linked Open Data).

Open Statistics reuse the concept of data cubes for OSD logical organisation. It shows how data are logically connected and not necessarily how they are physically connected.

Open Statistics also reuse Online Analytical Processing (OLAP) methods, such as slicing and dicing. In some cases however those methods are redefined since OLAP was initially introduced in a close environment. In Open Statistics we have the possibility of performing operations not needed before. For example, searching for similar data cubes in the same or different open data portal is an essential operation to overcome open data fragmentation.

Open Statistics involve analysing OSD with statistical methods, such as Pearson's correlation, linear regression, and logistic regression, and techniques such as panel data analysis and even statistical learning analysis in order to explain or predict phenomena. In the context of Open Statistics the exploitation of these methods and techniques will be redefined.

Finally, Open Statistics capitalise on the Linked Open Data technology (LOD) and more specifically on the LOD implementation of the data cube model, termed RDF Data Cube (QB) vocabulary. This provides the necessary technological infrastructure for Open Statistics.

Open Statistics Potential

Some of the most valuable methods that are used to exploit data include Online Analytical Processing (OLAP), correlation of cross-sectional data, time-series correlation, panel data analysis and creation of predictive models. These methods can also be used to analyse OSD.

OLAP refers to the technique of performing complex analysis over the information stored in a DW. The multidimensional nature of OSD allows performing OLAP on top of them in order to explore and get different views of the data. For example, OLAP can be used to view only selected part of data (slice or dice), to view a reoriented view of the data (pivot) or to navigate among different levels of the data along a specific dimension (drill-down or roll-up).

Cross-sectional data [START_REF] Dielman | Pooled cross-sectional and time series data: A survey of current statistical methodology[END_REF] provide observations of phenomena at a single point of time. Correlation of cross-sectional data can be, hence, used in statistics to measure and interpret the extent to which two measured variables are related to each other within a single point of time. Linear regression is the mostly used method to explore the correlation between two measured variables. Crosssectional data correlation can be used to assess possible associations between different phenomena described by OSD e.g. unemployment rate and poverty rate in the UK in 2015.

Correlation can be also used to measure and interpret the relationship between measured variables over time. In this case, correlation is applied in data that are modeled as time-series. OSD can be easily formulated as time series data as they usually measure the same phenomenon at successive time intervals. Time-series correlation can then be applied in order to explore the relationship between different phenomena over time e.g. unemployment rate and poverty rate in the UK over the last ten years.

Panel data [START_REF] Hildreth | Combining Cross Section Data and Time Series[END_REF] (or longitudinal data) can be used to model multi-dimensional data over time. Panel data are able to contain observations of multiple phenom-ena over multiple time periods. Panel data can be used on top of OSD to explore how a measured variable changes over time. For example, panel data can be used to explore the relationship between unemployment rate in all countries of Europe and the poverty rate in all countries of Europe the last ten years.

Predictive models are created and assessed in the context of predictive analytics in order to make empirical predictions using data and statistical or data mining methods [START_REF] Shmueli | To explain or to predict?[END_REF]. In general, the goal of predictive models is to predict the output of a variable value (Y) for new observations given their input values (X) based on historical data. OSD can be used as historical data for the creation as well as the assessment of predictive models.

According to our view Open Statistics introduce two types of OSD exploitation: the problem-driven approach and the data-driven approach.

The problem-driven approach follows the traditional data exploitation paradigm that aims to solve a well-defined problem. In this case, one of the main challenges is to discover the appropriate data and Open Statistics can support this task. For example, a problem-driven type of scenario could be the following: "I would like to explore a phenomenon". In this scenario, if we consider as an example the phenomenon of unemployment in European countries, the first requirement towards exploring unemployment would be to discover all relevant OSD. These can be datasets that measure unemployment from different European countries and in various time periods, provided by a single or various data portals. Relevant OSD can be then combined to provide a single view of unemployment and then analysed using different methods of analysis to produce interesting results. OLAP analysis, for example, could be used to view unemployment in Italy, Greece and Spain in years 2014 and 2015.

Another problem-driven type of scenarios could be the following: "I would like to explore the relationship between two or more phenomena". For example, we would like to explore the relationship between unemployment and poverty in the countries of Europe. Towards this end, we need again to discover relevant OSD. Once we have the datasets, we can combine them and then apply on them methods such as cross-sectional correlation, time-series correlation or panel data analysis.

As a result, the most important task in problem-driven scenarios is the discovery of relevant data. In the new reality of Open Statistics the vision is to facilitate the discovery of this relevant data. Hence, the main benefit of Open Statistics in this approach is that it will allow the easy and effective discovery of relative OSD that can be then analysed using the methods of analysis described above in order to solve specific problems.

The data-driven approach is a bottom-up approach compelled by OSD. Specifically, this approach aims at identifying unexplored results starting from a dataset at hand. A data-driven type of scenarios could be the following: "I would like to explore phenomena out of OSD". In order to solve this problem, we could start from a single dataset and then search for relevant datasets, combine and analyse them in order to discover possible relationships or other interesting conclusions.

In data-driven scenarios the benefits of Open Statistics can be even greater since the different methods of analysis that can be applied on OSD need to be redefined. Specifically, starting from a specific dataset, OLAP can be used to enhance this dataset by finding relevant datasets (e.g. that measure the same variable in a different year). This will facilitate the inspiration of innovative solutions or unexpected results that were not known before. Moreover, correlation (cross-sectional or time series) could be used to identify unexpected relationships with other datasets. Starting again from a specific dataset, data-driven correlation and panel data in Open Statistics will allow to go bottom-up and identify and create new and, maybe, unexpected relationships with other datasets. Finally, OSD can be used as the basis for the creation and assessment of predictive models. These predictive models could then be reused by different applications, in the same way that open data is reused.

Open Statistics Challenges

This section presents a preliminary analysis of the main challenges towards the vision of Open Statistics.

Data Integration

A big challenge in Open Statistics is related to overcoming the data fragmentation problem. OSD integration is required in order to be able to achieve the vision of Open Statistics. Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data [START_REF] Lenzerini | Data integration: A theoretical perspective[END_REF]. Because, however, OSD can be conceptualised as cubes, the data integration problem in Open Statistics can be though as the problem of combining cubes.

Although cubes integration has being studied in data warehouses literature for more than a decade [START_REF] Datta | The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses[END_REF][START_REF] Agrawal | Modeling multidimensional databases[END_REF][START_REF] Perez | Integrating data warehouses with web data: A survey[END_REF], OSD have introduced new requirements in the area. Traditionally, an organisation had a collection of measures that were important to its operation. These measures were organised in a data warehouse. In Open Statistics, however, data providers make available for reuse in an ad-hoc manner multiple datasets that can actually comprise parts of a bigger cube with multiple measures, dimensions, and hierarchies. On the other hand, however, users may need data that require the integration of these datasets or even the data cubes that can be created by integrating the datasets. Moreover, in most of the traditional theoretical frameworks cubes integration was only presented as part of a generic framework aiming at conceptualise cubes and thus they do not describe in detail cubes integration. As a result, cube integration has to be studied under this new perspective.

An interesting case of OSD integration involve the expansion of an initial cube by using data from other cubes. For example, in terms of our first scenario, we can expand a dataset about unemployment in European countries in different years by reusing cubes with unemployment data in lower geographical level. This Fig. 2. Cube integration that enables the expansion of an initial cube will result in a new cube with data of unemployment in two levels of geography (Figure 2).

A second interesting case of OSD integration involves the creation of a cube from the intersection of two other cubes. For example, in terms of the same scenario, we integrate two cubes with the same dimensions but with different values of dimensions. The resulted cube contains only the intersection of these values as presented in Figure 3.

These types of cube integration pose some interesting requirements that need to be further analysed and formally defined.

Data Analysis

Data analysis challenges are mainly related to data-driven scenarios where automatic processing of data is required. All different statistical analysis methods and techniques should be studied in the context of cubes and specific requirements that would enable automated and massive analyses should be defined.

Moreover, different analyses could present controversial results for the same phenomenon depending on the statistical methods and/or the data that have been employed. For example, [START_REF] Chiricos | Rates of crime and unemployment: An analysis of aggregate research evidence[END_REF] reviewed 68 studies about the relationship between crime and the unemployment rate and he found that only less than half of these studies have found positive significant effects of the unemployment on crime rates. So, it is important statistical analyses and models to also open up and connect to OSD [START_REF] Kalampokis | Towards a Vocabulary for Incorporating Predictive Models into the Linked Data Web[END_REF].

Technologies

Linked data technologies has been early proposed as the most effective way for opening up data on the Web [START_REF] Bizer | Linked data -the story so far[END_REF]. In the case of OSD this is particular true Fig. 3. Cube integration that enables the intersection of two cubes as it will not only facilitate data integration but also enable the realisation of data-driven scenarios that require automatic data processing [START_REF] Tambouris | Processing Linked Open Data Cubes[END_REF].

The RDF Data Cube (QB) vocabulary [START_REF] Cyganiak | The RDF Data Cube Vocabulary. W3C Recommendation[END_REF] is a W3C standard for publishing data cubes on the Web using the RDF (Resource Description Framework) and the linked data principles. The core class of the vocabulary is the qb:DataSet that represents a cube. A cube is connected to a qb:DataStructureDefinition which in turn contains a set of components that can be a qb:DimensionProperty, a qb:MeasureProperty or a qb:AttributeProperty. The first one defines the dimensions of the cube, the second the measures, while the third structural metadata such as the unit of measurement. Finally a cube has multiple qb:Observation that describe the cells of the cube.

At the moment, a number of statistical datasets are freely available on the Web as linked data cubes. For example, the European Commission's Digital Agenda provides its Scoreboard as linked data cubes. An unofficial linked data transformation of Eurostat's data 13 , created in the course of a research project, includes more than 5,000 linked data cubes. Few statistical datasets from the European Central Bank, World Bank, UNESCO and other international organisations have been also transformed to linked data in a third party activity 14 . Census data of 2011 from Ireland and Greece and historical censuses from the Netherlands have been also published as linked data cubes [START_REF] Petrou | Publishing census as linked open data: a case study[END_REF][START_REF] Meroo-Peuela | Linked humanities data: the next frontier? In: A Case-study in Historical Census Data[END_REF]. Moreover, many official efforts launched by governmental organisations (owning the data) are using the QB vocabulary to publish their data as linked data cubes. For example, the Scottish Government, the UK Department for Communities and Local Government, the Italian National Institute of Statistics, the Flemish Govern-ment, the Irish Central Statistics Office and the European Commission's Digital Agenda have published their data using the QB vocabulary.

Although all the above efforts use the same vocabulary, they often adopt different practices, thus hampering the data integration. The result is the creation of cubes that cannot be integrated despite the use of linked data technologies [START_REF] Kalampokis | Challenges on Developing Tools for Exploiting Linked Open Data Cubes[END_REF]. Interoperability conflicts that hamper data integration have been extensively studied in the context of relational databases and data warehouses. Examples of such conflicts include naming, structural, data scaling, data precision, and data representation conflicts [START_REF] Tseng | Integrating heterogeneous data warehouses using XML technologies[END_REF][START_REF] Kim | Classifying schematic and data heterogeneity in multidatabase systems[END_REF][START_REF] Batini | A comparative analysis of methodologies for database schema integration[END_REF][START_REF] Berger | FedDW global schema architect: Uml-based design tool for the integration of data mart schemas[END_REF]. It is essential, however, to identify all the types of conflicts that may hamper data cube integration in the context of Open Statistics and linked data. Moreover, it is important to come up with and agree on best practices to be followed by statistical data publisher in order to overcome these types of conflicts.

Finally, software tools that support important functionalities related to linked data cubes creation and exploitation have been recently developed [START_REF] Kalampokis | Exploiting Linked Data Cubes with OpenCube Toolkit[END_REF][START_REF] Salas | Publishing statistical data on the web[END_REF]. However, we need to overcome challenges related to performance especially in the case of exploiting cubes from multiple data stores [START_REF] Kalampokis | ICT Tools for Creating, Expanding, and Exploiting Statistical Linked Open Data[END_REF].

Conclusion

An increasing number of public authorities and international organisations publish Open Data. Despite the great expectations of open data movement, studies reveal that publishing open data does not automatically provide benefits. At the same time, policy documents and research in the area suggest that a large part of open data is numerical and, more specifically, concerns statistics.

In this paper, we introduced Open Statistics as a new field to systematically investigate Open Statistical Data. Open Statistics reuse methods from diverse fields like Open Data, Semantic Web, Statistics, Data Warehouses, and OLAP.

Towards this end, we initially studied datasets in both the UK and the European open data portals. We concluded that that (a) OSD can be conceptualised using the traditional data cube (or just cube) model that was initially introduced in Data Warehouses and that (b) different datasets provide fragmented views of a cube.

Thereafter we presented the potential of Open Statistics and we described how OSD redefines traditional statistical analysis methods such as OLAP, panel data, and statistical learning. We also presented challenges related to the achievement of Open Statistics. The challenges were categorised in three categories, namely data integration, data analysis, and technology.

In summary, the results suggest that Open Statistics provide benefits not present in any of these fields alone. We conclude that in certain cases OSD can realise the potential of open data.

Fig. 1 .

 1 Fig. 1. Open Statistical Data modelled as a cube

http://opendefinition.org

http://data.gov.uk

http://www.europeandataportal.eu/

https://www.w3.org/DesignIssues/LinkedData.html

http://data.worldbank.org/

http://stats.oecd.org/

http://opendata.unesco.org/

http://europeandataportal.eu/

http://ec.europa.eu/eurostat/data/database

http://ons.gov.uk

http://opendata.brussel.be/

http://opendata.camden.gov.uk/

http://eurostat.linked-statistics.org

Acknowledgments. This work is funded by the European Commission within the H2020 Programme in the context of the project OpenGovIntelligence (http: //OpenGovIntelligence.eu) under grand agreement No. 693849.


Djoko Sayogo
email: dsayogo@ctg.albany.edu

J Ramon Gil-Garcia
email: jgil-garcia@ctg.albany.edu

Felippe Cronemberger
email: fcronemberger@albany.edu

Determinants of Clarity of Roles and Responsibilities in Interagency Information Integration and Sharing (IIS)

Keywords: Interagency information Sharing, Role Clarity, IIS, Boundary object Track: General e-Government Track -Ongoing Research

Interagency information sharing (IIS) has been identified as a powerful strategy to improve information and services in the public sector. In order to accomplish effective information sharing across organizational boundaries, the definition and clarity of roles and responsibilities are very important, particularly when the number and diversity of the agencies involved is high. However, there are very few studies that analyze the variables that affect this clarity in interagency information sharing efforts. Based on a review of current literature and a national survey conducted in the US, this paper quantitatively explores the determinants of clarity of roles and responsibilities. Consistent with existing literature, we found a significant and positive influence of diversity of participating organizations, the use of boundary objects, and communication skills on the use and emergence of need for clarity of roles and responsibilities in IIS project. Our findings open avenues for future research about the role of clarity of roles and responsibilities, its determinants, and other variables may play in mediating or directly explaining IIS success.

Introduction

Information integration and sharing (IIS) are the foundation of government efforts to develop and execute public policies that are smart, efficient and more responsive to nowadays social problems. IIS often involves collaboration of participants across various domains and beyond the boundary of individuals, units and organizations [START_REF] Dawes | Interagency information sharing: Expected benefits, manageable risks[END_REF].

Working on an IIS initiative within such a collaborative setting might pose challenges for government officials, who were unaccustomed to working collaboratively across their respective agency's boundary [START_REF] Dawes | Interagency information sharing: Expected benefits, manageable risks[END_REF]. The government officials might be more accustomed to the "need to know" as compare to "need to share" culture [START_REF] Dawes | From "need to know" to "need to share": Tangled problems, information boundaries, and the building of public sector knowledge networks[END_REF].

Clear roles and responsibilities enable the building of trust among members of IIS initiatives [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF]. Having clarity on roles and responsibilities in collaborative efforts precipitate the formation of mutual expectations; a clear understanding of what are expected from them and from other participants [START_REF] Thompson | Collaboration Processes: Inside the Black Box[END_REF].

While research has demonstrated the importance of clarity of roles and responsibilities (CRR) in IIS initiatives [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF], very few or even not one have attempted to systematically test the determinants of CRR using quantitative analysis. We adopt Pardo et al. [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF] three determinants of CRR and add three other determinants based on our review of existing studies. The objective of this paper is to examine the determinants of clarity of roles and responsibilities in IIS project using data from the National Survey conducted by the Center for Technology in Government. We tested whether three determinants of CRR identified in Pardo et al. [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF] and other three determinants from the literature truly influence the use or emergence of CRR in IIS project. Hence, this paper addresses the following research question, what are the determinants of clarity of roles and responsibilities in interagency IIS.

The rest of the paper is organized in 5 sections, including the foregoing introduction. Section 2 highlights studies evaluating the influence of clarity of roles and responsibilities on organizational and inter-organizational information sharing and performance. Section 2 also presents the main hypothesis and the preliminary model used for this study. Section three describes our research methodology, including the data distribution, variable measurement and analysis technique. Section 4 discusses the results from the statistical analysis. Finally, Section five offers some concluding remarks and suggests areas for future research about this topic.

Determinants of Clarity of Roles and Responsibilities

Clarity of roles can be defined as "…the presence [or absence] of adequate role-relevant information due either to restriction of this information or to variations of the quality of the information … [or] the subjective feeling of having as much [or not as much] role-relevant information as the person would like to have [START_REF] Lyons | Role clarity, need for clarity, satisfaction, tension, and withdrawal[END_REF]. Consequently, role ambiguity arises when a person is not aware of what the expectations of such role are [START_REF] Kahn | Organizational stress: Studies in role conflict and ambiguity[END_REF] or from poor communication practices [START_REF] Schaubroeck | A Field Experiment Testing Supervisory Role Clarification[END_REF].

Studies have found the great importance of clarity of roles and responsibilities in an interorganizational setting where several organizations or agencies must interact with each other. Lack of clarity regarding roles and responsibilities hinder interagency collaboration [START_REF] Meyer | Police-led partnership responses to high risk youths and their families: challenges associated with forming successful and sustainable partnerships[END_REF][START_REF] Sloper | Facilitators and barriers for co-ordinated multi-agency services[END_REF] and hamper an effective communication in interagency collaboration [START_REF] Dickerson | How Collaborative the Collaboration? Assessing Interagency Collaboration within a Juvenile Court Diversion Program[END_REF][START_REF] Hocevar | Building Collaborative Capacity: An Innovative Strategy for Homeland Security Preparedness[END_REF]. On the other hand, clarity of roles and responsibilities could positively affect the success of collaboration in multi-agencies setting such as IIS project [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF]. Having clear sense of what should be done for achieving common goals through collaborative effort gives ideas to participants about what they need to do and what they can expect from other participants [START_REF] Thompson | Collaboration Processes: Inside the Black Box[END_REF].

Clarity of roles and responsibilities are crucial in multi-organizational collaborations because individuals who accustomed to work within their respective boundaries have to traverse the border and interacts with other boundaries. These "people at the boundary" often feel that they "sort of belong and sort of don't" in between the boundaries [START_REF] Tanggaard | Learning at trade vocational school and learning at work: boundary crossing in apprentices' everyday life[END_REF]. Thus, having clarity of roles and responsibilities alleviate the burden for the "people at boundary" in interactive circumstances.

Despite the positive effect of clarity of roles, a systematic assessment of the determinants of clarity of roles and responsibilities is not so well understood, particularly in IIS setting. An initial proposition of the determinants of clarity of roles and responsibilities was suggested by Pardo et al. [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF]. They propose a three determinants of clarity of roles and responsibilities in interagency information sharing, namely: past experiences, diversity of participating organizations and exercise of formal authority. Past experiences in the collaboration provides indication of the participant's expectations about collaboration [START_REF] Jonker | Looking Through the Eyes of Others: assessing mutual expectations and experiences in order to shape dialogue and collaboration between business and NGOs with respect to CSR[END_REF]. Acknowledging and acting on the differences among the participants facilitate the creation of clarity of roles and responsibilities in the IIS project [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF]. Sensitivity to the different interests of the participating organizations help the project leaders to delineate roles and responsibilities that minimize potential conflicts. Similarly, interagency collaboration entail variety and distributed power and authority relationships. Given the diversity of the agencies involved, agency had no authority to mandate the roles and responsibilities of other agencies. As such, ensuring efficient collaboration necessitate a judicious way to exercise formal authority [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF].

In addition to the three determinants proposed by Pardo et al. [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF], studies have identify three other determinants of clarity of roles and responsibilities and interorganizational information sharing: (1) extent of boundary object use [START_REF] Kegerise | Keys to successful collaboration[END_REF][START_REF] Nidumolu | Interorganizational information systems and the structure and climate of seller-buyer relationships[END_REF], (2) degree of respect for autonomy of participating organizations [START_REF] Thompson | Collaboration Processes: Inside the Black Box[END_REF] and (3) collaboration, coordination, and communication skills [START_REF] Casey | Partnership -success factors of interorganizational relationships[END_REF][START_REF] Hardy | Discourse and Collaboration: The Role of Conversations and Collective Identity[END_REF][START_REF] Luna-Reyes | Knowledge sharing and trust in collaborative requirements analysis[END_REF] . Due to the crossing of boundaries, the use of boundary object is key to generate shared understanding and commonalities [START_REF] Thompson | Collaboration Processes: Inside the Black Box[END_REF]. Boundary objects are necessary to establish and maintain clear roles and responsibilities [START_REF] Kegerise | Keys to successful collaboration[END_REF] and by doing so, it becomes critical for the success of interorganizational information system [START_REF] Nidumolu | Interorganizational information systems and the structure and climate of seller-buyer relationships[END_REF].

Boundary Object use

Diversity of participating organization Past Experiences

Collaboration and communication skills

Respect of Autonomy

Exercise of Authority Clarity of Roles and Responsibilities

Fig. 1. Research Model

Fear of losing agency identity and autonomy create a major barrier for interagency cooperation [START_REF] Hoban | Barriers to interagency cooperation[END_REF]. Thus, the participating agencies will strive to protect their interest and to maintain their identity [START_REF] Hoban | Barriers to interagency cooperation[END_REF]. Presumably, respect to the autonomy of the participating agencies induce willingness to cooperate which can lead to success in IIS collaboration. Finally, collaboration and communication skills are important in generating clarity of roles and responsibilities and lead to success of IIS. Communication and collaboration skills are paramount because learning each other's objectives, roles and constraints constitutes the first starting point in inter-organizational initiatives [START_REF] Luna-Reyes | Knowledge sharing and trust in collaborative requirements analysis[END_REF]. Clarifying and achieving the agreed upon roles and responsibilities can be achieved through intensive conversations among the participants in the collaboration process [START_REF] Hardy | Discourse and Collaboration: The Role of Conversations and Collective Identity[END_REF]. Subsequently, the agreed upon roles and responsibilities must be communicated and coordinated to avoid ensuing ambiguity [START_REF] Casey | Partnership -success factors of interorganizational relationships[END_REF]. Based on the review of the literature, we proposed a model in figure 1

Research Methodology

Data and Data collection

This study analyzes data from a national survey conducted by the Center for Technology in Government (CTG) in April 2008. The use of older data should not be a problem considering that this study aims to test theory, hence it is expected that the relationship among the variables is generalizable and stable over time. The original random-sampled dataset consists of 171 responses. After data cleaning, the regression analysis was based on 158-160 responses, with about 7-8% of the responses being dropped from the analysis due to missing values.

3.2

Variables and Measurement

In this study, all variables or sub-variables were derived from extensive review of literature from information science, information system and public administration and policy studies. We use Boolean search by combining keywords of interagency information Sharing and role clarity to search academic databases such as Academic Search Complete, Scopus or Web of Science. We use variations of synonyms for the keyword role clarity to include clarity of roles and clarity of responsibilities.

All variables or sub-variables in this study were measured in a 7-point Likert scale, ranging from "Not at all (1)" to "To a great extent ( 7)" Due to the variation in 7-point scale, we regarded the variable as continuous variable. The summary of data is provided in Table 2 and the description and measurement of each variable is provided below: The reliability of the resulting variables was examined using Chronbach's alpha values (Table 2). As mentioned previously, all the Chronbach's alpha values were above 0.70, representing acceptable levels of reliability. We ran multivariate regression analysis to test the causal relationship of the determinants to the clarity of roles and responsibilities variable. We used robust regression to account for the possible heterogeneity issue.

Results: Testing the Determinants of Clarity of Roles and Responsibilities

Building from the case studies on the Public Health and the Criminal Justice information sharing network, Pardo et al. [START_REF] Pardo | Clarity of roles and responsibilities in government cross-boundary information sharing initiatives: Identifying the determinants[END_REF] posit three determinants of clarity of roles and responsibilities in a cross-boundary information sharing initiative. We add additional three determinants based on our review of the literature. Our first analysis was to evaluate the extent to which these six determinants influence the clarity of roles and responsibilities in a IIS initiative. ** Significant at 0.05 Table 3 shows that three variables emerge as significant and positive predictors of clarity of roles and responsibilities. The results indicate that the use of boundary object is positively and statistically significant in influencing the clarity of roles and responsibilities in an IIS project (tvalue = 3.20; pvalue = 0,002). The coefficient for the use of boundary object is 0.1919. Because the use of boundary object is a composite variable, we have to interpret it in terms of increase or decrease in standard deviation. The predicted effects of the use of boundary object is an increase of 1.5597 * 0.1919 = 0.299. An increase of one standard deviation in the use of boundary object will increase clarity of roles and responsibility in IIS project by 0.2335 standard deviation (0.299 / 1.282). The standard deviation of the use of boundary object (1.5597) and clarity of roles (1.282) was derive from the descriptive statistics in table 1.

The same transformation was used for interpreting the rest of the composite variables. The collaboration, coordination and communication skills [colcom] was also found to be a significant predictor of clarity of roles and responsibilities in IIS project with (tvalue = 3.98; pvalue = 0,000). One standard deviation increase in the collaboration and communication skills will bring clarity on roles and responsibilities in IIS project up by 0.4069 standard deviation. The influence of diversity of participating organizations is positive and significant for bringing clarity of roles and responsibilities in IIS project. If diversity of organizations participating in the initiative increases by one standard deviation, the likelihood of fostering clarity of roles and responsibilities among the participants increases by 0.1853 standard deviation. This result indicates that the participants gauge the needs for clarity on roles and responsibilities of the project based on the numbers and diversity of the participants in the IIS project collaboration.

Comparing the three significant variables, the results in table 3 (see beta column) indicate that collaboration and communication skills are the most dominant predictors with beta value of 0.3986, followed by the use of boundary object (0.2263) and the diversity of participating organization (0.1812). Based on the beta results in table 3, the other three non-significant variables have a very low magnitude of beta coefficient. The results further authenticate the significance of the three variables -use of boundary object, coordination and communication skills, and diversity of participating organizations -to predict the need to have clarity on roles and responsibilities in the IIS project.

5

Concluding Remarks and Implications

Concluding Remarks

Our analysis results strengthen the importance of the use of boundary object, communication and collaboration skills, and diversity of participating organization for the use and emergence of need for clarity of roles and responsibilities in IIS project.

Our results demonstrate the strong influence of using boundary object to determine the use and need for clarity of roles and responsibility. The findings suggest that the use of boundary object in the IIS project influences the participant need to have clarity in roles and responsibilities. The use of boundary object facilitate the creation of shared understanding among the participants. As such, the use of boundary object is very instrumental in bringing about clarity and acceptance among the organizations involved in the IIS project.

Our regression results suggest that the likelihood of framing clarity of roles and responsibilities among the participants increases with an increase in the diversity of organizations participating in IIS project. Thus, we posit that participants judge when and how much clarity of roles and responsibilities are needed early in the collaboration from their assessment on the diversity of organizations participating in IIS project. Presumably, during the process of framing and setting of the IIS project's goals, the participants gauge and correlate the numbers and diversity of participants with the likelihood of success. Based on their evaluation, the participants assess the needs for clarity of roles and responsibilities to help them achieved the IIS project's goals. Further research is needed to ascertain the connection between diversity of participants, clarity of roles and success of IIS project.

Our findings also strengthened the importance of communication and collaboration skills in bringing clarity of roles and responsibilities in the IIS project. The intensity of communication is crucial so that the diverse perspectives and interests of the participants can be accommodated and the agreed upon roles and responsibilities is communicated and coordinated to avoid ensuing ambiguity [START_REF] Casey | Partnership -success factors of interorganizational relationships[END_REF].

Research and Practical Implications

The main finding of this study implies implications for future research as follows.

1. Our findings indicate that clarity of roles and responsibilities as variable possess unique characteristics. Clarity of roles can emerge as independent predictor as well as mediating variables in a relationship. For that, it is necessary re-evaluate the significance of clarity of roles and its determinants by considering other variables such as leadership, communication, organizational capacity to the model. Future research could test the relationships using non-linear methods such as structural equation modelling or partial least square.

2. Our findings also point to the possible connection between clarity of roles and its determinants to the likelihood of achieving success of IIS project. For instance, in effort to correlate between the diversity of participating organizations with the likelihood of IIS success, the participants might decide on the need to have clarity of roles. Such research thus could ascertain whether the effect of clarity of roles is mediated by other variables in determining success for IIS projects.

3. Our result also signifies the importance of diversity of participating organizations which presumably affect the likelihood of IIS project success. Public managers could use this knowledge to evaluate when and how deep role clarity is needed for IIS project through the assessment of the numbers and diversity of the participants.

6

  above connecting the determinants of clarity of roles and responsibilities to the success of IIS project. Likewise, based on extant studies, we propose the hypotheses as follows. H1: Past experiences significantly influence the clarity of roles and responsibilities in IIS initiatives. H2: Boundary object use significantly influences the clarity of roles and responsibilities in IIS initiatives. H3: Collaboration and communication skills significantly influence the clarity of roles and responsibilities in IIS initiatives. H4: Diversity of participating organizations significantly influences the clarity of roles and responsibilities in IIS initiatives. H5: Exercise of formal authority significantly influences the clarity of roles and responsibilities in IIS initiatives. H6: Respect of autonomy significantly influences the clarity of roles and responsibilities in IIS initiatives.



  a. Independent Variables  Exercise of formal authority [auth] measure whether leaders and/or participants misused the power of their official positions. Collaboration and communication skills [colcom] measures the extent to which communication within the IIS initiative was effective. Diversity of participating organization [dive] measures the extent to which the organizations participating in the initiative were diverse. The use of boundary object [boun] is a composite variable measuring how valuable: a) written materials, b) the use of prototypes, c) charters, and d) stories (of personal experiences) were in the initiative. Respecting the autonomy of participating organization [resp] is composite variable measuring: a) presence or absence of interference from other organizations, b) respect for the specific limitations of the organization, and c) respect for the specific needs of the organization involved.  Past experiences [exp] is composite variable measuring whether participants had previous positive experience working together as a group. b. Dependent Variables a. Clarity of roles and responsibilities [crr] measures the extent to which the roles and responsibilities of organizations participating in the IIS project were clear to the participants.

Table 2 .

 2 Means and Chronbach's alpha

	Variables	abb	µ	std dev	ii-cor 1	α
	Clarity of roles and	crr	0.012 1.2821	1.011	0.8070
	responsibilities
	The use of boundary object	boun	0.004 1.5597	1.798	0.7798
	Respecting the autonomy of	resp	0.003 1.5437	1.408	0.8617
	participating organizations

Table 3 .

 3 Regression Result for Clarity of Roles and Responsibilities

	Variables	abb	Coeff	Beta	SE
	The use of boundary object	boun	0.1919 0.2263	0.0600 **
	Previous experience	exp	0.0525 0.0053	0.0688
	Communication and collaboration skills	colcom	0.3270 0.3986	0.0822 **
	Diversity of participating organizations	dive	0.1459	0.1812	0.5017 **
	Exercise of authority
	Respecting autonomy of participating	auth	-0.0684	-0.0626	0.0956
	organizations	resp	0.0462	0.0556	0.0688
	Constant		-0.7041		0.3362
	N				159
	R2				0.367
	F(6,152)				13.86

Acknowledgements

This work was partially supported by the National Science Foundation under Grant No. ITR-0205152. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.