OPEN DATA DEVELOPMENT OF COUNTRIES: GLOBAL STATUS AND TRENDS. Esmeralda Florez Ramos

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1 OPEN DATA DEVELOPMENT OF COUNTRIES: GLOBAL STATUS AND TRENDS Esmeralda Florez Ramos Technische Universität Berlin, Faculty of Economics and Management, Chair of Innovation Economics Fraunhofer Institute for Oen Communication Systems FOKUS, Innovation and Technology Transfer ABSTRACT Oen data lays a key role for governments strategy to deal with challenges of the future. It has the otential to imrove ublic sector s transarency, engagement of civil society, and economic growth. This aer contributes to answering the questions: Can oen data have an imact on innovation? Under which condition is this the case? Which data can be used to assess the rogress on a country level? Which countries are successful with oen data? How successful are the government actions to suort economic develoment through oen data? The exloratory analysis investigates the relationshi between oen data readiness and measures on imact, and on changes in oen data develoment level and the influence of the country s level of ICT develoment, transarency and freedom. This aer also takes a secific look at economic imact scores and their correlation with government initiatives for training and innovation on oen data. It was found that success on oen data at the country level is based on good levels of ICT develoment, freedom and in the interest of becoming more transarent. There are indications that countries with low ICT develoment do not rofit from oen data, but the evidence is limited, due to the small number of countries observed. There is a strong correlation between suort for entrereneurshi & business readiness and economic imact. However, the relationshi between the develoment of these indicators during the time of the study and the measured imact is unclear. Keywords Oen data, status, trends, Oen Data Barometer, imact. 1. INTRODUCTION Oen data lays a key role for governments strategy to deal with challenges of the future. It has the otential to imrove ublic sector s transarency, engagement of civil society, and economic growth through new oen data business. In the information age in which we are living having access to quality data imlies an advantage to make better-informed decisions, to lan better strategies, to roduce better innovative ideas and new insights, and to find more suitable solutions for comlex roblems. For these reasons the concet of oen data, which is data that can be freely used, modified, and shared by anyone for any urose [27] has been adoted by governments around the world. This aer is art of a research on the oen data imact on innovation. The motivation behind this aer is to contribute to answering the questions: Can oen data have an imact on innovation? Under which condition is this the case? Which data can be used to assess the rogress on a country level? Which countries are successful with oen data? How successful are the government actions to suort economic develoment through oen data? This research is lanned to have two hases, the first hase resented in this aer is on the global oen data status and develoment over last four years. The second hase of the research will further deeen the analysis of the main observations resent in this aer to comrehend the relationshis between the different indicators. The analysis resented in this aer is on the relationshi between the indicators of oen data readiness and the oen data imact. Changes in the level oen data develoment are also analyzed by comaring the rank ositions of the countries and considering other indicators such as country s level of ICT develoment, transarency and olitical rights and civil liberties of individuals. Without going into in-deth econometrics this aer also analyses the correlation between the level of oen data readiness for entrereneurs & business of a country and the measure for economic imact. This measure includes the level of available training on the use of oen data and the suort for innovation with oen data offered by governments. This exloratory analysis is done at a global level using secondary data from the historical datasets of the Oen Data Barometer (ODB) of the World Wide Web Foundation , and other reliable sources such as the ICT Develoment Index (IDI) 2016 by International Telecommunication Union (ITU), Freedom in the world status by the Freedom House; Corrution Percetions Index (CPI) by Transarency International; as well as the Gross National Income (GNI) er country given by the World Bank. For the last 4 years, the ODB has rovided data that scores and ranks the countries level of readiness for oen data initiatives, imlementation of oen data rograms, and the imact that oen data has on business, olitics and civil society. The historical data of the ODB with it latest released /CFP1768P-ART 2017 ITU 21 Kaleidoscoe

2 2017 ITU Kaleidoscoe Academic Conference early this summer allows making the first observations of the global oen data develoment trends such as the one resented in this aer. Studies on oen data have been focused on oen data initiatives [2] [17], imact and value creation through oen data [7] [15] [16], oen data for innovation and growth [1] [19] [24] [28], oen data business models [18]. There are not many studies on oen data trends, because of the novelty of the toic and the few reliable historical data about oen data. Studies on different secific subjects of oen data develoment are from major institutions such as the ODB. This year s study of the ODB itself focuses on the changes of the general and regional ranks, on the datasets ublished, and on the imact rank [20]. Although the ODB has ublished four editions of datasets, it was found that only a few studies have used the datasets of the ODB. Those using this data have used it for reference or a comlementary secondary data [6] [13] [14] [23]. [3] used extensible the datasets of the ODB second edition for their study. This aer is organized as follows: the first art deals with the current global status of oen data, the second treats the develoment of oen data over the last four years, and the third art resents a secific analysis on oen data entrereneur & business readiness and the economic imact. In contrast to other benchmarks, such as GODI, that focuses on datasets, the ODB contains indicators for both inuts and oututs of oen data. It is unique in the way that it also rovides indexes for the imact, and suorting factors. The structure of the data of the ODB is as shown in Figure 1. The overall ODB rank is based on a global score. The global score is the sum of the scores of the sub-indexes readiness, imlementation, and imact. These scores are scaled from 0 to 100. In each sub-index, the score is created from comonents, three in each sub-index. For examle, in the sub-index imact, the comonents are olitical, economic and social. At the same time, each comonent is built on indicators. Most of these indicators are based on rimary data, while five indicators are based on secondary data. An overview of the ODB sub-indexes, comonents, indicators and weights are shown in Table DATA The data used for the analysis resented in this aer are datasets of the four editions of the ODB from the years 2013 to 2016 [10] [20]. The World Wide Web Foundation roduces the ODB in collaboration with the Oen Data for Develoment (OD4D) network, and with the suort of the Omidyar Network. The number of countries included in the ODB has increased from 77 to 115 over the four years. These datasets are oen and available to use by anyone. Primary and secondary data is used in the ODB. The rimary data are a eer-reviewed exert surveys on oen data olicy, imlementation and imacts, and a government selfassessment on the oen data imlementation and imact. Secondary data from the World Economic Forum, World Bank, United Nations e-government Survey and Freedom House was selected to comlement the data [21]. In the last years a number of other benchmarks on oen data aart from the ODB have aeared, such as the Global Oen Data Index (GODI), run by the Oen Knowledge Network, which is an annual benchmark for ublication of oen government data [9]; and the Oen Data Readiness Assessment (ODRA), which is roduced by the World Bank s Oen Government Data Working Grou [22]. Each of these benchmarks has different scoes and uses a different aroach in order to understand the various elements of oen data as well as, metrics and methodologies affecting their fluctuation. However, the alicability of each benchmark varies deending on the situation [11]. The ODB was selected for this research because it considers the comlete ath from the readiness for oen data initiatives; imlementation of oen data rograms, to the imact of oen data on business, olitics and civil society. Fig. 1. Structure of Oen Data Barometer data. In each of these sub-indexes the ODB focuses on a) government s readiness (olicy and actions), civil society and citizens readiness, business and entrereneurs readiness; b) datasets availability based on the Oen Data Charter rinciles [5] and it looks at the datasets for innovation, social olicy, accountability; and on the c) olitical, social, and economic imacts. The insightful analysis of the ODB together with the goal-oriented measure can be used to observe the relationshi between readiness, imlementation and the imacts of oen data. However, the ODB benchmark should be taken as an aroximation rather than on exact measures because the data is subjective (selfassessment and surveys) [11]. The scores used for the analysis are those normalized by the ODB [20]. To comlement the analysis, this aer includes additional secondary data. The Corrution Percetions Index (CPI) reared by Transarency International ranks and scores countries based on the ercetion of the level of corrution of the country s ublic sector. The CPI is used widely as an indicator of corrution [29]. The Freedom in the world status by the Freedom House evaluates the state of freedom of countries [8]. The category Free, Partly Free, or Not Free assigned to a country is determined by the combination of the levels of olitical rights and civil liberties 22

3 Challenges for a data-driven society by individuals in the country. Data from the Global Innovation Index (GII 2017), was used as a measurement of innovation [25]. The ICT Develoment Index (IDI) 2016 by the International Telecommunication Union (ITU) [12] measures the ICT develoment of the countries based on eleven indicators contained in the categories ICT access, use and skills. Table 1. Oen Data Barometer indicators and weights. Sub-index data (%) scale wgt. Readiness Government olicies 1/4 Oen data olicies/strategies Oen data management Imortance of ICT to government s vision Government actions 1/4 Oen government initiative City/region freedom running oen data initiatives Government on-line service index s Entrereneurs & business 1/4 Availability of training on oen data Suort for innovation through oen data Firms level of technology absortion s Internet users s Citizens & civil Society 1/4 Right-to-information law Legal/regulatory framework for rotection of ersonal data Engagement of civil society and IT rofessionals with government regarding oen data Political freedoms and civil liberties s index Imlementation Innovation 1/3 Social olicy 1/3 Accountability 1/3 Imact Political 1/3 Government efficiency and effectiveness Transarency Social 1/3 Environmental sustainability Inclusion of marginalized grous on olicy making and access to government services Economic 1/3 Country s economy (ositive) Entrereneurs successful use of oen data to build new business in the country Note: Primary data (), secondary data (s). More details on the ODB research methodology under htt://oendatabarometer.org/4thedition/methodology/ 3. OPEN DATA GLOBAL STATUS AND TRENDS 3.1. Global status of oen data For the analysis on the global status of oen data, the 115 countries included in the 4th edition of the ODB were considered. The analysis is based on the geograhical regions and on the income categories based on the Gross National income (GNI) given by the World Bank. The regions are North America, South Asia, East Asia and Pacific, Middle East & North Africa, Latin America & Caribbean, Euroe & Central Asia and Sub-Sahara Africa. The income-level categories are high-income, uer middleincome, lower middle-income, and low-income. The WB gives the following definitions of the levels for the current fiscal year, high-income economies are those with a GNI er caita of $12,476 or more; uer middle-income economies are those with a GNI er caita between $4,036 and $12,475; lower middle-income economies are those with a GNI er caita between $1,026 and $4,035; low-income are those with a GNI er caita of $1,025 or less in 2015 [30] Regions and GNI based analysis An overview of the ODB rank 4th edition is shown in Figure 2. From this heat ma, one observes that the oen data rank follows exected results regarding regions and income levels of countries. The countries at the to of the ODB rank are the United Kingdom (UK), Canada, France, the United States of America (USA), Australia, Jaan. The to ten countries according to the ODB rank 4th edition are shown in Table 2. Table 2. To ten countries according with the ODB 4th edition rank and scores. Country Rank Score Readiness Imlem. Imact UK Canada France USA Korea Australia New Zealand Jaan Netherlands Norway The average OBD rank er region reflects the current global economic trends, in which East and South Asia are the most dynamic regions of the world, and the low-income countries still being left behind [30]. Figure 3 that there is a wide difference in erformance of countries within the same region. An analysis of the countries income level hels to understand the difference between an in each region. In the East Asia-Pacific region, Australia, New Zealand and Jaan are scoring significantly higher than the other countries of the region, which are in the lower-middleincome category as exected. However, the Philiines is a lower-middle income country and ranks (22), one lace higher than Singaore (23), a high-income country. Also, the Philiines and Indonesia (38) scored better than uer middle-income countries like China (71) and Malaysia (53). In the Middle East and North Africa region, high-income countries like the United Arabs Emirates (59) and Bahrain (74) did not score much better than those lower-middle income countries like Egyt (85) and Morocco (79) and were worse than Tunisia (50). In the Latin America and Caribbean region, Mexico stands out, ranked (11). 23

4 2017 ITU Kaleidoscoe Academic Conference In the Sub-Sahara Africa region, Kenya (35) ranked better than the uer-middle income countries. Burkina Faso also did better than the mean of the uer-middle income countries. Fig. 4. Relationshi between scaled imlementation and readiness scores with measures of imact scaled 1 to 100 (best). Countries groued by level of GNI. Fig. 2. Heat ma ODB 4th ed. rank (2016) from 1 (best) to 115 (worse). Fig. 5. Relationshi between scaled imlementation and readiness scores with measures of new business density score 1 to 100 (best). Countries groued by level of GNI. Figure 3 ODB rank 4th_ed analysis of countries groued by geograhical regions Oen data readiness, imlementation and measures of imact Figure 4 shows that there is, in general, a higher level of readiness than imlementation by the countries, while there is a clear correlation between readiness, imlementation and the measures of imact. Further, low-income countries do not show any imact regardless the level of readiness and imlementation. One of the weaknesses of the ODB in assessing imact and innovation of oen data is that it relies on exert survey results only. Indeendent measures of innovation are given for instance in the GII [26]. While there is not one canonical measure of innovation, for the urose of this aer New business density er country of the GII, which refers to new registrations er thousand oulation years old in 2014 is found to be more aroriate for the case of oen data as other measures such as atents. Figure 5 shows the relation between the imlementation and readiness scores. It reveals a more comlex relationshi than the one shown by the ODB imact in Figure ODB rank and countries level of freedom, transarency and ICT develoment For this first art of the analysis, the influence of the level of ICT develoment, ublic sector transarency, and the level of olitical rights and liberties of each country on the rank of countries on the develoment of oen data, are considered. In the grou of high-income countries, it is ossible to see how the level of freedom is more related to the ODB rank than the levels of ICT develoment and transarency (Figure 6). For instance, Qatar, South Arabia, United Arab Emirates, Bahrain rank high in the IDI index and transarency, but have a low level of freedom and a low ODB rank. The countries in the uer-middle income grou are scoring badly in transarency (between 20-60), and together with the level of ICT develoment, it seems not having any relationshi with the ODB rank. Regarding the level of 24

5 Challenges for a data-driven society freedom in this grou, it is ossible to see a slight correlation with the ODB rank. The excetion is Russia, which ranks well, desite having low levels of freedom and transarency. The level of freedom among these countries is quite diverse since there are different kinds of governments found in this grou. Countries with low freedom scores are China, Belarus, Thailand, Jordan, Kazakhstan, and Russia, where Russia ranks better in the ODB than the others. Fig. 7. Relationshi between the ODB rank 2016 from1(best) to 115 (worse) with level of Freedom Free (F), Partial Free (PF), No Free (NF) Global oen data trends Fig. 6. Relationshi between current ODB rank from 1 (best) to 115 (worse) with level of freedom from 1 to 100 (very free), level of transarency from 1 to 100 (very transarent), and ICT develoment rank 1 (best) to (to); relationshi between freedom from 1 to 100 (very free) with level of transarency from 1 to 100 (very transarent) - (bottom). Countries groued by level of GNI. Democracies rank comaratively good in the ODB. Venezuela is a secial case scoring badly in both transarency and freedom, which is a reflection of the current olitical crisis in the country. Other countries such as Ecuador, Paraguay, Mexico and Colombia are democracies scoring as free countries, but they have roblems with transarency. Exect for Mexico these countries rank middle in the ODB. The case of Mexico with a good ODB rank could be read as if the country were investing in oen data to imrove its transarency. Lower middle-income countries are doing similar to uer middle-income ones. They are also relative worse than the uer middle-income countries in both transarency and freedom. However, there is a wide variation in the freedom status among the countries. For instance, India and Tunisia are free, but Yemen and Vietnam are considered not free. This grou of countries is also ranking low in the ICT develoment index, yet it is ossible to observe that similar to the other income grous, the level of freedom is related to the level of ODB. Countries in the low-income grou are similar in terms of freedom and transarency ranking similarly to the lower middle-income countries. Regarding the ICT develoment, these countries are far behind, scoring the worst in the IDI index. This low ICT develoment is really influencing the ODB rank of these countries since they have limitations in the use of data. For the analysis on the trends of oen data, only the original 77 countries included in all editions of the ODB were considered. Here the focus is on the changes from 2013 to 2016 in the ODB rank as well as, in the readiness, imlementation, imact and the relationshis scores. Fig. 8. Changes in the ODB rank, imact, imlementation, readiness scores from 2013 to 2016 averaged er region. Positive values reflect an imrovement of the rank, negative a decline. (to); ODB 1st ed. rank 2013 and ODB 4th ed. rank 2016 regional averages (bottom). From Figure 8 it is ossible to observe that East Asia & Pacific and Latin America & Caribbean had a big imrovement in readiness and imlementation esecially in comarison to Euroe. East Asia & Pacific is the one region with the biggest imrovement in the imact, although having lower imrovement in imlementation than Latin America & Caribbean. Euroe & Central Asia had no changes regarding readiness, and it has gone down in the ODB rank. One reason for this could be that the region started already with a highlevel of readiness for first ODB rank in

6 2017 ITU Kaleidoscoe Academic Conference It is ossible to see in Figure 9 that the Scandinavian countries that used to be at the to of the ODB ranking lost rank, because of imlementation and readiness sub-indexes. In the grou of the uer middle-income countries, Mexico and Russia are having the highest levels of entrereneurs & business readiness and economic imact. However, the level of economic imact is middle-low. In general, it is ossible to observe that there is a relation on entrereneurs & business readiness and the economic imact in this grou of countries, the higher readiness is, the higher imact is. Excetions exist like Malaysia, that yet having an uer middle level of entrereneurs & business readiness resents almost no economic imact. Fig. 9. Relationshi between change in imlementation and readiness scores and the measured imact scaled from 1 to 100 (best) (to); Change in ODB rank from 2013 to 2016 vs ODB rank 2013 (bottom). Rank is from 1 (best) to 77 (worse). Negative change ODB (y-axis) imlies imrovement in rank. Countries groued by level of GNI. 4. ECONOMIC IMPACT THROUGH OPEN DATA ENTREPRENEURSHIP This art of the analysis investigates the correlation between the level of oen data readiness for entrereneurs & business of a country and the measure of economic imact considering only the indicators on the countries level of available training on the use of oen data, the suort for innovation with oen data offered by governments, and the measure for economic imact of the ODB for 2016 and the change from 2013 to Relation between oen data entrereneurshi and the economic imact Fig. 10. Relationshis between measures of economic imact scaled 1 to 100 (best) with: countries level of available training on the use of oen data, the suort for innovation with oen data offered by governments from 1 to 10 (best) (uer left-middle); imlementation scaled from 1 to 100 (best) (uer-left); entrereneurs & business readiness scaled from 1 to 100 (best) (bottom). Countries groued by level of GNI. The lower middle-income countries have a lower level of entrereneurs & business readiness and economic imact. However, similar to the uer middle-income grou, there is a relation between readiness with imact. For the majority of the low-income countries based on the ODB, there is no economic imact excet Neal with a very low imact of (16/100). All high-income countries have a middle or high level of entrereneurs & business readiness, excet Hungary with a low level, and the majority of the countries in this grou resent some level of economic imact. However, for many of those countries with middle level of entrereneurs & business readiness the economic imact is very low (Figure 10). Interesting cases are Singaore, Sweden, Italy and Belgium with a high level of entrereneurs & business readiness, but a low economic imact. From the data, Sain has the highest economic imact of the high-income countries, although having just a middle entrereneurs & business readiness. Uruguay, United Arab Emirates (UAE), Portugal and Chile, desite having similar levels of entrereneurs & business readiness as Sain are observing almost no economic imact. The UK and Korea are following Sain on the level of economic imact, and both have a high level of entrereneurs & business readiness. 26 Fig. 11. Comarison of develoment over years imlementation, readiness citizens & civil society, entrereneurs & business readiness, economic imact for countries: Sain, Sweden and the United Kingdom.

7 Challenges for a data-driven society The case of Sain is analyzed further using Figure 13. Sain resents the highest change over the four years in the economic imact, although not having an equally high entrereneurs & business readiness. Moreover, as mentioned other countries such as Italy and Ireland with higher readiness do not achieve half of what Sain does. However, from observing Figure 11 it is not ossible to determine the indicators causing this big imact Develoment of economic imact scores from 2013 to 2016 In this art, the analysis is on the changes in the entrereneurs & business readiness and the economic imact. As can be seen in Figure 12, it is not ossible to conclude that changes in imlementation and readiness during the time of the study has led to changes in the economic imact, as there is no obvious relationshi between the change in the sub-indexes and the overall economic imact measure. From this observation, one could draw three ossible conclusions. The first is that the time of four years is not long enough time to actually notice a direct influence on the economic imact through these measures, the second is that the measures themselves have been ineffective, and the third that the fact that countries started from very different levels has been more imortant to what they have done during these four years than the recent develoment, esecially for those countries that started at the to of the rank back in For countries to be successful in oen data, they have to not only have a good ICT develoment level but also a good level of freedom and will of becoming more transarent. That is esecially true for countries in the Middle East, which could start already rofiting from oen data since they have the ICT develoment and economical means yet do not seem to have the interest. Oosite cases are countries in Latin America like Mexico, that although being an uer middleincome country it seems to invest in oen data to imrove the transarency. There are indications that countries with low ICT develoment (ICT access, ICT use, and ICT skills) do not rofit from oen data, but the evidence is limited, due to the small number of countries observed. The current status shows that there is a correlation between entrereneurs & business readiness and economic imact. However, it is not ossible to see that changes in entrereneurs & business readiness during the time of the study have an obvious relationshi with changes in the economic imact. To measure innovation is very difficult. When relacing the ODB imact score with an indeendent measure, the new business density er country, a more comlex relationshi is observed. As can be exected this high level measure is influenced by many other factors. There is wide room for further research in this area. Further study should investigate whether the time frame of four years too short to notice influence on the economic imact through these measures, the measures themselves have been ineffective, or different starting levels have been more imortant in further develoment than actual changes during the four years of observation. REFERENCES [1] A. Abellá-García, M. Ortiz-De-Urbina-Criado, and C. DePablos-Heredero, The Ecosystem of Services Around Smart Cities: An Exloratory Analysis, resented at the Procedia Comuter Science, vol. 64, , [2] A. Ojo, E. Curry, and F. A. Zeleti, A tale of oen data innovations in five smart cities, resented at the Proceedings of the Annual Hawaii International Conference on System Sciences, , Fig. 12. Relationshis between changes in measure of economic imact scaled 1 to 100 (best) and change in countries level of available training on the use of oen data, suort for innovation with oen data offered by governments from 1 to 10 (best) - (uer left-middle); imlementation scaled from 1 to 100 (best) (uer-left); entrereneurs & business readiness scaled from 1 to 100 (best) - (bottom). Countries are groued by level of GNI. 5. CONCLUSIONS Oen data rank follows the regional and income level ranks as exected. However, even within grous with comarable income levels, there are big differences in oen data imlementation, readiness and imact. [3] C. Shen, Z. Riaz, M. S. Palle, Q. Jin, and F. Peña-Mora Oen Data Landscae: A Global Persective and a Focus on China In: Janssen M. et al. (eds) Oen and Big Data Management and Innovation. Lecture Notes in Comuter Science, vol Sringer, Cham, [4] Cagemini Consulting, The Oen Data Economy Unlocking Economic Value by Oening Government and Public Data, [5] Data Charter rinciles htt://oendatacharter.net/ [6] D. Beneventano, S. Bergamaschi, L Gagliardelli, L. Po, Oen data for imroving Youth Policies IC3K Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2,

8 2017 ITU Kaleidoscoe Academic Conference [7] Euroean Commission, Creating Value through Oen Data: Study on the Imact of Re-use of Public Data Resources - Digital Agenda for Euroe - Euroean Data Portal, [8] Freedom House, Freedom in the World Status, 2017 htts://freedomhouse.org/reort/freedom-world/freedomworld-2017 [9] Global Oen Data Index (GODI), Oen Knowledge Network htts://index.okfn.org/about/ [10] Historical data Oen Data Barometer 1st 2nd 3rd editions htt://oendatabarometer.org/ [11] I. Susha, A. Zuiderwijk, M. Janssen, and A. Grönlund, Benchmarks for Evaluating the Progress of Oen Data Adotion: Usage, Limitations, and Lessons Learned Social Science Comuter Review, Vol. 33(5) DOI: / , [12] International Telecommunication Union, ICT Develoment Index (IDI) [13] J. Cranefield, O. Robertson, G. Oliver, Value in the mash: Exloring the benefits, barriers and enablers of oen data as ECIS 2014 Proceedings - 22nd Euroean Conference on Information Systems, [14] JN. Lee, J. Ham, B. Choi Effect of Government Data Oenness on a Knowledge-Based Economy Information Technology and Quantitative Management, Procedia Comuter Science, 91 (2016) (ITQM 2016), 2016 [23] T. Davies, F. Perini Researching the emerging imacts of oen data: revisiting the ODCC concetual framework The Journal of Community Informatics, 12(2), (Secial issue on Oen Data for Social Change and Sustainable Develoment), , 2016 [24] T. Jetzek, M. Avital, and N. Bjorn-Andersen, Data-Driven Innovation through Oen Government Data, J. Theor. Al. Electron. Commer. Res., vol. 9, no. 2, , [25] The Global Innovation Index 2017 Reort. Indicator New business density [26] The Global Innovation Index Reort 2016 (9th Edition). The Global Innovation Index Concetual Framework. [27] The oen definition htt://oendatabarometer.org/oen-data/ [28] The World Bank, Oen Data for Economic Growth - Transort and ICT Global Practice., Jun [29] Transarency international, Corrution Percetions Index (CPI) ndex_2016 [30] World Economic Situation and Prosects (WESP), [15] K. Granickas, Understanding the Imact of Releasing and Reusing Oen Goverment Data, Euroean Public Sector Information Platform EPSI latform, Toic Reort No. 2013/08, [16] M. Da, D. Balta, W. Palmetshofer, H. Krcmar, and P. Kuzev, Oen Data. The Benefits Das Volkswirtschaftliche Potenziel für Deutschland, [17] M. Foulonneau, S. Martin, and S. Turki, How oen data are turned into services? Exloring Services Science, Sringer International Publishing, , [18] Magalhaes, C. Roseira, and L. Manley, Business models for oen government data, resented at the ACM International Conference Proceeding Series, vol January, , 2014, [19] McKinsey&Comany, Oen data: Unlocking innovation and erformance with liquid information, Oct [20] Oen Data Barometer 4th edition Data, World Wide Web Foundation. Datasets and reort. htt://oendatabarometer.org/4thedition/reort/ htt://oendatabarometer.org/4thedition/data/. [21] Oen Data Barometer 4th edition Methodology, World Wide Web Foundation htt://oendatabarometer.org/4thedition/methodology/. [22] Oen Data Readiness Assessment (ODRA), World Bank, Oen Government Data Working Grou htt://oendatatoolkit.worldbank.org/en/odra.html 28