**3. 3D ultrasound reconstruction process**

This section explained the 3D ultrasound reconstruction process in detail. This process is achieved from the use of 2D ultrasound probe with linear array. Based on [6], the standard workflow of the 3D ultrasound reconstruction is data acquisition stage, data preprocessing stage, volume reconstruction method stage, and 3D visualization stage. **Figure 4** shows the overall process of 3D ultrasound reconstruction.


*4.4.2 Mean time to repair (MTTR)*

The MTTR is the average time taken to complete the repair of each breakdown, restore the plant(s) to functional use and resume production. The shoter

**69**

**Figure 8.** *Plant reliability.*

**Figure 7.**

the performance would improve.

*Harnessing the Multiple Benefits of a Computerised Maintenance Management System*

the MTTR, the better. This is because the MTTR influences the duration of the downtime of machines in the production line. Similar to other factors, the monthly and annual averages for 2017 exceeded the benchmark of 1.5 hours, as is evident from **Figure 6**. Similarly, in 2018 the average in September is marginally above the benchmark of 1.35 hours. However, the monthly performance in January, April, May, June and July was impressive. It was hoped that, in the last quarter of the year,

*DOI: http://dx.doi.org/10.5772/intechopen.93732*

*Total duration of downtime of plant equipment.*

#### *Harnessing the Multiple Benefits of a Computerised Maintenance Management System DOI: http://dx.doi.org/10.5772/intechopen.93732*

**Figure 7.** *Total duration of downtime of plant equipment.*

*Operations Management - Emerging Trend in the Digital Era*

of breakdowns was the same as the benchmark set for 2018. It was hoped that in the remaining months of 2018, the plants would record a lower number of breakdowns. Another concern was the length of time it takes to conclude repairs or known as MTTR.

The MTTR is the average time taken to complete the repair of each breakdown, restore the plant(s) to functional use and resume production. The shoter

**68**

**Figure 6.**

*Mean time to repair (MTTR).*

**Figure 5.**

*Total number of breakdowns.*

*4.4.2 Mean time to repair (MTTR)*

the MTTR, the better. This is because the MTTR influences the duration of the downtime of machines in the production line. Similar to other factors, the monthly and annual averages for 2017 exceeded the benchmark of 1.5 hours, as is evident from **Figure 6**. Similarly, in 2018 the average in September is marginally above the benchmark of 1.35 hours. However, the monthly performance in January, April, May, June and July was impressive. It was hoped that, in the last quarter of the year, the performance would improve.


In the regression specification for health service delivery and OGD, slightly differentiated relationships between variables emerge. First, when disaggregating between provision and outcomes, OGD is positively and significantly correlated with health outcomes but not provision. Second, when controlling for accountability, the relationship between OGD and health provision remains insignificant, and the relationship between OGD and health outcomes remains significant. This would imply that in terms of health outcomes, levels of accountability and OGD can independently have an important effect, whereas accountability – and not OGD – is an important factor for provision. Finally, the interaction effects of accountability are tested with respect to the relationship between OGD and health service delivery, and no significant effect is found (not shown).

#### SITUATING OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS

## *Premise 4: Higher levels of OGD directly enable improved service delivery, excluding the effects of accountability*

To test the final premise, service provision and outcomes are regressed against OGD, omitting the role of accountability as suggested above with respect to the sectoral differentiation, but testing alternative control variables such as the Public Management condition and the Client Power condition. First, in the education sector, OGD is estimated to have a stronger correlation with education provision than outcomes, which may reflect the time needed for policy to translate into results; however, it is worth highlighting that both relationships are significant. Second, no evidence supports the claim that either Public Management or Client Power has relevance with education provision or outcomes. Finally, even controlling for these conditions, the relationship between OGD and service delivery in the education sector does not change in a meaningful way with respect to the coefficients.

Drilling down deeper, strong associations are found between OGD and certain aspects of education service delivery. As mentioned, when education service delivery is regressed on the OGD education index, a positive and significant association is found in terms of provision. Importantly, the positive and significant correlation between education provision and OGD is strongly driven by indicators linked to quality and management of education provision. In terms of outcomes, when education service delivery outcomes are regressed on the OGD education index, a positive and significant association is found in terms of certain outcomes as well. For instance, the association between OGD and education completion is only significant for primary levels of education, whereas

#### **Jelenic** From theory to practice

it is insignificant for secondary and tertiary completion.

In the health sector, OGD displays associations which are heterogeneous. First, OGD is found to be positively associated with health outcomes, but there is not such statistical evidence of an association with health provision. Second, with respect to health provision, Public Management capacity appears to be a more important determining factor than OGD (see column 5). Likewise, when controlling for the public management condition, the OGD coefficient linked to health outcomes remains significant, but slightly declines, suggesting that the impact of OGD on health outcomes (see column 6) is partly driven by changes in the index of Public Management, although both are independently significant. Finally, when controlling for the client power condition, this relationship remains unaltered, suggesting that this condition has little impact on the relationship between OGD and health service delivery in the countries included. In summary, it can be shown that overall, public management plays a role in health provision and outcomes, while OGD seems to further contribute to the outcome channel but not provision.

At a disaggregated level, a strong association is found between OGD and certain aspects of health service delivery. As seen in the previous table, OGD and health provision are not significantly correlated; however, there is a significant association between OGD and sub-indexes related to immunisations, including DPT and Hepatitis B. No correlations exist for other health provision indicators including measles immunisation and provision of anti-retroviral treatments. With respect to specific outcome indictors, it should be noted that the OGD index is significantly correlated with the index of health outcomes, as well as with child mortality outcomes and WHO disease prevention statistics.

#### SITUATING OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS

## Conclusions

## *Principles and generalisations inferred from the results*

With respect to the four original premises put forth above, and the various regression analyses carried out, a number of generalisations can be drawn with respect the effects of OGD. Importantly, while certain relationships may hold in each of the premises analysed, when taken together, larger conclusions may be drawn with respect to relationships between variables. Accordingly, these initial conclusions can help to bolster the empirical evidence base for the various public sector theories advocated in the literature as well as to highlight areas for future research on the topic.

## Premise 1: Higher levels of OGD make government more accountable

With respect to the first premise, this analysis confirms a strong positive association between OGD and accountability in the countries surveyed over the period. When controlling for other contextual factors such as the levels of political freedoms, civil rights, and access to information (e.g. publicity condition) as well as political accountability, including the presence of formal electoral mechanisms (e.g. political agency condition), this analysis likewise finds these factors significant, independent of OGD. This suggests that *all three factors* can be considered important elements in improving government accountability, in line with the premised theory. *As such, while OGD is necessary for improved accountability, it is not sufficient, as publicity and political agency must also be included – thus confirming the earlier theoretical and empirical contributions.* Even when using other accountability indexes – for instance, related accountability indices prepared by the World Bank and African Development Bank – these relationships hold, thus reinforcing the validity of this claim.

## Figure 2. Effects of OGD on accountability

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### Premise 2: More accountable governments enable improved service delivery

With respect to the second premise, this analysis provides evidence that accountability – in particular, those governments exhibiting higher levels of accountability – correlates with improved service delivery; however, there are differentiated effects across education provision and outcomes and health provision and outcomes. This is an important finding in and of itself, as it highlights the fact that sectoral specificities between the health and education sectors – in terms of how decisions are made, how services are rendered, and how clients consume these services – have a strong determining effect. Another important specification highlighted by the research is the importance of differentiating between service provision, which may be more readily governed by public policy decisions and implementation, versus service outcomes, which may be influenced by a myriad of other contextual factors and take years to materialise.

To be sure, in the education sector, this analysis finds no correlation between levels of accountability and education provision and outcomes. Even when controlling for levels of public sector management capacity, which is an important tool for governments to translate their accountability structures and practices into improvements in service delivery, this initial analysis finds no association. Returning to the literature, there can be a number of important explanations for this seemingly counterintuitive finding. For instance, in the education sector in particular, there are a number of sector-level political economy factors which may confound the impacts of accountability and public management capacity. These include, among others: (i) the potential for excludability, which affects the power relationships between those who demand access to education (e.g. students, parents, etc.) and those who control access to those services (e.g. school administrators); (ii) principal-agent asymmetries, whereby parents, as agents, make decisions for their children, who are the 'rightful' principals of the service; (iii) the fact that education is a 'merit' good, whereby its consumption is compulsory for most clients (e.g. students themselves); (iv) education outcomes often require 'co-production,' which means that frontline providers and recipients (e.g. students and parents) both need to invest their time in achieving outcomes; and (v) issues related to information asymmetries and visibility, whereby it is difficult to measure the quality of education inputs (e.g. curriculum and instructional quality), which can have knock-on effects with respect to the political salience of policy decisions. All of these – and other – sectoral level dynamics may explain why a positive association with accountability or public management in the education sector is not apparent in the sample selection of countries and years studied. However, this finding should not be interpreted to suggest that government accountability is not an important determining factor in the delivery of education more broadly, as accountable institutions remain *sine qua non* for ensuring efficacy and efficiency of the public sector.

#### SITUATING OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS

Conversely, in the health sector, public accountability appears to have a significant association with service provision and outcomes. However, when controlling for levels of public sector management capacity, which is an equally important determinant in how services are delivered, the results become more nuanced. In particular, it would appear that accountability is a more important condition for health provision, whereas public management capacity seems to absorb the effect that accountability has with respect to health outcomes. These differentiated effects between health provision and outcomes may likewise have some grounding in the literature related to sector-level political economy. For instance, a number of characteristics make health service delivery significantly more 'murky' than other sectors, including, among others: (i) the difference between preventative and curative services, the latter of which may dominate, as many health services are consumed on an 'emergency' basis and do not involve continual monitoring; (ii) the presence of information asymmetries whereby patients do not have the same knowledge of the quality of service inputs as healthcare providers; (iii) the high level of individual discretion in providing health services, whereby providers are required to make complex decisions, which are difficult to monitor; and (iv) the professional dominance of healthcare providers, who are able to better politically organise in ways that allow them to resist strict government control and regulation. These – and other – sectoral characteristics may go a long way in providing explanations as to why health provision is more associated with public management capacity and accountability, whereas health outcomes have a strong linkage with public management but not accountability. While the intricacies of these relationships are outside the scope of this paper, these findings indicate a need for future qualitative political economy analysis at the sector level.

## Premise 3: Higher levels of OGD make governments more accountable, which subsequently enables improved service delivery

With respect to the third premise, this analysis provides evidence that accountability can play an important role in translating OGD into improved service delivery, but again, there are important distinctions between education provision and outcomes and health provision and outcomes. As mentioned above, the principal-agent relationships of accountability in the education sector may differ significantly from those in the health sector, especially where responsibilities are delegated to head of household as opposed to the eventual consumers of these services. Likewise, the nature of service delivery can have important determinants regarding how accountability affects provision and outcomes, given, for instance, differences between how access, quality, and oversight may translate into achievements in the education sector and how preventative and curative services may alter monitoring, oversight, and compliance in the health sector.

#### **Jelenic** From theory to practice

In the education sector, the findings suggest that OGD is positively and significantly correlated with both provision and outcomes. Importantly, these relationships maintain their significance when controlling for accountability, suggesting that the link between OGD and education service delivery is independent from levels of accountability at the country level. Returning to the finding noted above, accountability does not appear to be a significant condition in intermediating the relationship between OGD and education service delivery, which suggests a direct effect of OGD on provision and outcomes. Concretely, this means that the present analysis finds no evidence of the 'longroute' to service delivery in the education sector, whereby OGD fosters increased accountability, which then leads to improved service delivery. Rather, this may mean that policymakers can use OGD simply as a management tool – outside a democratic accountability process – to make top-down policy decisions that affect service delivery in education in the countries concerned. Alternatively, this may mean that citizens are able to directly influence service delivery from frontline providers using social (non-formal) accountability mechanisms, including collective engagement through parent-teacher committees, participatory budgeting and oversight exercises, or direct citizen pressure on service providers such as petitions and protests. Both of these alternate 'shortroute' hypotheses are tested subsequently under the fourth premise.

Figure 3. Effects of OGD on education provision and outcomes

Conversely, in the health sector, OGD is not associated with improved service provision, but it is significantly correlated with improved outcomes. When controlling for the effects of accountability on this relationship, the analysis finds that it has an independent relationship with respect to service provision but works in tandem with OGD with respect to health outcomes. This would therefore suggest that there may be evidence of the 'long-route' to service delivery in the health sector, whereby OGD fosters increased accountability, which then leads to improved service delivery – with the caveat that 'service delivery' is conceptualised on the basis of outcomes, not provision. Again, the reasons for these differentiated effects are likely vast and varied and would likewise require a level of qualitative analysis outside of this initial statistical estimation. Future research on this topic should thus work to parse out the sector-level details to provide more adequate explanations supporting these associations.

Figure 4. Effects of OGD on health provision and outcomes

Premise 4: Higher levels of OGD directly enable improved service delivery, excluding the effects of accountability

With respect to the fourth premise, this analysis finds differentiated effects of public sector management capacity and client power (e.g. social accountability) mechanisms. Again, these dynamics may be more largely related to the differences in how services are planned, executed, and evaluated in the sectors concerned. These differences are also linked to particular aspects with respect to provision, which may be more easily controlled by public policy and execution than outcomes, which represent the long-term effects of service delivery policies and implementation.

In the education sector, additional testing of other enabling conditions indicates that neither public management capacity nor client power (social accountability) affects the relationship between OGD and education service delivery. OGD is found to have a more positive correlation with education provision than outcomes (although both are significant), which may reflect the time needed for policy to translate into results. For their part, client power and public management capacity appear to have little influence on these results, suggesting that some key explanatory gaps remain in the education sector, which may have several interpretations. First, in the absence of any additional control or intervening variables, it may suggest a direct relationship between OGD and education service delivery, meaning that OGD is an important determinant in the education sector. Conversely, it may suggest other lurking variables, since education provision and outcomes are likely to be intimately intertwined with other contextual factors such as family income, access disparities between urban

#### **Jelenic** From theory to practice

and rural areas, as well as other cross-sectoral issues such as infrastructure, nutrition, as well as conflict and gender dynamics. Finally, it may suggest certain political economy dynamics, including rent seeking, clientelism, patronage, and other forms of policy capture, which, as noted above, can distort principal-agent relationships between citizens and public officials. Again, while the present analysis does not attempt to answer these questions, this suggests the need for additional future quantitative and qualitative research that delves deeper into sectoral level service delivery dynamics.

As noted above, in the health sector, the findings suggest a positive association between OGD and health outcomes, but not provision. Importantly, the analysis finds that part of the impact of OGD on health indicators is driven by changes in the index of public management, although not client power, which appears to have a direct and important impact on both health provision and outcomes. Accordingly, the findings point to the role that public management can play as a predictor of better health provision and outcomes, while such a relationship is not apparent in education (as was also demonstrated in Premise 2). This finding must also be taken in context with previous findings on the importance of accountability, which likewise has differentiated associations between health provision and outcomes. On the aggregate, these findings suggest that accountability and public management capacity – but not OGD – impact health provision, whereas OGD and public sector management capacity – but not accountability – impact health outcomes. Finally, as in education, client power does not seem to play a role in health provision and outcomes, which is a counterintuitive finding. Thus, future research may need to better conceptualise this variable or employ methods to better specify the effects of client power.

## Limitations

Although this research has considerable promise, there are a number of limitations which should be acknowledged, including, most importantly, that this analysis only claims to be an *initial* assessment of the relationship between the variables. While it would be ideal to have more years of data – and more observations included in the dataset – the analysis uses data that are *currently* available, as OGD only started to be measured in 2012/2013. In this regard, OLS regressions are instructive in teasing out initial associations between variables; however, as more data become available, increasingly more sophisticated estimations can be performed in the future. For instance, it would be ideal to include a country fixed-effects estimation as it would demonstrate that the results are not driven by omitted variable bias, which are countryspecific and do not change over time. Unfortunately, including country fixedeffects estimation at this point in time would lead to a significant loss of degrees of freedom to estimate the parameters of interest. As such, there is an inherent trade off between unbiasedness/consistency that would be provided by the fixed-effects estimation versus being able to detect parameters using this initial OLS estimation.

Second, given the fact that OGD is a rather recent phenomenon, it is difficult to suggest a purely *causal* relationship between variables. While a lag of nine months has been introduced between the availability of OGD statistics and changes in accountability and service provision, it is likely that these changes may take more time to materialise. Accordingly, the present analysis only purports to provide evidence of associations between variables, to help support or refute existing theoretical propositions. Relatedly, challenges exist with certain indicators and it is necessary to ensure that there are no significant issues of endogeneity and simultaneous causality. For instance, more accountable governments *may* be more inclined to support an OGD initiative in the first place, which would reverse the causal relationship. As such, it is difficult to argue at this early stage whether OGD precedes accountability or accountability precedes OGD. Further quantitative and qualitative methods will need to be employed (e.g. process tracing, case study analysis, and qualitative comparative analysis) to establish a higher degree of causal certainty in the future.

Finally, there may be difficulties extrapolating the relationships demonstrated in the sub-Saharan context to other countries, particularly upper-middle-income and high-income countries. To be sure, the analysis finds the coefficient relating OGD and accountability to be of a significant magnitude, which is due primarily to the low levels of OGD prevalent in the sub-Saharan African region. For this reason, one cannot expect the same gains from OGD in countries with already high levels of accountably and service delivery as would be possible in country contexts with relatively low starting points. This is precisely the reason why the present study omits other regions and focuses on a sample of countries in sub-Saharan Africa, a place where OGD has the greatest potential for improving accountability and service delivery.

## Recommendations and future research

Given that this paper seeks to present an initial assessment of OGD, accountability, service delivery, as well as some of the other relevant 'conditions' as gleaned from the theoretical literature, it is perhaps too early to put forth any substantive recommendations on what needs to be done to better enable OGD to reach its full potential. In its place, the initial findings presented here suggest a number of streams of future research that need to be pursued, including, inter alia: (i) deeper sectoral level analysis in education and health to better understand key provision and outcome dynamics as well as their linkages to accountability relationships; (ii) more robust understanding of relationships that do not manifest themselves statistically – such as the client power condition and related social accountability mechanisms – which ostensibly have a key

#### **Jelenic** From theory to practice

role in the impact of OGD; (iii) deeper country-level analysis using qualitative methods to establish typologies of country behaviour, which can help to provide key explanations for the performance of OGD, accountability, and service delivery across different contexts; (iv) more research and recommendations for sub-national OGD, which is where most frontline service delivery takes place (e.g. hospitals, clinics, schools, etc.); (v) more granular analysis of the end-users of OGD as well as the outputs of OGD use (e.g. dashboards, visualisations, journalism, etc.); and finally, as more years of data become available, (vi) the introduction of more robust statistical methods (e.g. fixed-effects models) as well as more sophisticated qualitative methods (e.g. process tracing and qualitative comparative analysis) in order to strengthen the causal links between OGD, accountability, and service delivery.

#### SITUATING OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS

# Annexures to Chapter 10

*Annex. 1: Regression Specifications*

Premise 1: Higher levels of open data availability make government more accountable

*Accountabilityi = α + β1 OGD Averagei + β<sup>2</sup>* log *GDPi + β3 Political Agencyi + β4 Publicityi + ε<sup>i</sup>*

Premise 2: More accountable governments enable improved service delivery

*Edu.Provisionsi = α + β1 Accountabilityi + β<sup>2</sup>* log *GDPi + β3 Public managementi + ε<sup>i</sup> Edu.Outcomesi = α + β1 Accountabilityi + β<sup>2</sup>* log *GDPi + β3 Public managementi + ε<sup>i</sup> Health Provisionsi = α + β1 Accountabilityi + β<sup>2</sup>* log *GDPi + β3 Public managementi + ε<sup>i</sup> Health Outcomesi = α + β1 Accountabilityi + β<sup>2</sup>* log *GDPi + β3 Public managementi + ε<sup>i</sup>*

Premise 3: Higher levels of open data availability enables improved service delivery, taking into account the effects of political accountability

Premise 4: Higher levels of open data availability enable improved service delivery, excluding the effects of political accountability

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## *Annex. 2: Indexed Indicators*

## Accountability Index (including indicator sources)

#### Adjusted Accountability Index

#### Sub-Indicators removed for endogeneity

Source: Mo Ibrahim Index of African Governance Indicators 2017

## Service Delivery Indices (including indicator sources)

Source: Mo Ibrahim Index of African Governance Indicators 2017

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## Conditional Indicators

Source: Mo Ibrahim Index of African Governance Indicators 2017

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### *Annex. 3: Summary Statistics*

## Country Observations by Year (n=86)

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### REFERENCES

Arrow KJ (1951) *Social Choice and Individual Values*. USA: Yale University Press

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#### SITUATING OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS

Olson M (1965) *The Logic of Collective Action: Public Action and the Theory of Groups*. Cambridge, MA: Harvard University Press

Open Democracy Advice Centre (2003) Turning the right to information law into a living reality: Access to information and the imperative of effective implementation. Cape Town: Open Democracy Advice Centre. https://www.humanrightsinitiative.org/ programs/ai/rti/international/laws\_papers/southafrica/Calland%20-%20Turning%20 FOI%20law%20into%20living%20reality%20-%20Jan-03.pdf

Open Data Charter (2015) International open data charter. https://opendatacharter.net/ wp-content/uploads/2015/10/opendatacharter-charter\_F.pdf

Open Society Justice Initiative (2006) *Transparency and silence: A survey of access to information laws and practices in 14 countries*. New York: Open Society Institute

Pandey P, Goyal S & Sundararaman V (2008b) Public participation, teacher accountability, and school outcomes: Findings from baseline surveys in three Indian states. *Policy Research Working Paper* No. 4777. Washington, DC: World Bank Group

Peisakhin L & Pinto P (2010) Is transparency an effective anti-corruption strategy? Evidence from a field experiment in India. *Regulation & Governance* 4(3): 261–280

Reinikka R & Svensson J (2011) The power of information in public services: Evidence from education in Uganda. *Journal of Public Economics* 95(7-8): 956–966

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## About the authors

**Michael Cañares** is the managing consultant at Step Up Consulting and leads several data for development projects globally, namely, research on open contracting and inclusion in Africa and Asia funded by HIVOS, data-based road asset management capacity building for UNDP in the Philippines, labour market information for ILO in Myanmar, results measurement on road governance projects in Vanuatu and labour market data project feasibility for Indonesia funded by GIZ.

**Markus Christian** is a researcher at Sinergantara. He holds a master's degree in development studies from Bandung Institute of Technology and has conducted research on basic services and their relation to gender and human rights and other development issues. His particular interest is in understanding the contribution of technology, especially ICTs, to government-people relationships and on how the conception and adoption model is being applied in various ICT initiatives.

**Pieter Colpaert** is a post-doctoral researcher at Ghent University, IDLab – IMEC. His team researches public web APIs and open data. They also maintain a couple of APIs themselves, such as the Linked Dataset of the 4 public transport operators in Belgium. In 2012, he co-founded Open Knowledge Belgium, an umbrella for organisations sharing the common vision of open knowledge.

**Doyinsola Dina**, at the time of writing, was the data researcher and analyst of the Open Data Research Centre, School of Media and Communication, Pan-Atlantic University. Her experience in data research and journalism, account planning and strategy, and media planning roles in academic, media and advertising industries where she interacted with data is pivotal to her research prowess. She holds a master's in Media and Communication from the Pan-Atlantic University.

**Natalia Domagala** leads on data ethics policy at the Cabinet Office, Government Digital Service in the UK. She previously advised on open government and open data policies for the Department for Digital, Culture, Media and Sport in the UK and implemented open data challenges for 360Giving. She has research experience in anthropology, gender, civic tech, and economic development. Natalia received her MSc in Local Economic Development from the London School of Economics and her BA in Anthropology and Media from Goldsmiths University.

**Patrick Enaholo** holds a doctoral degree in media and communication from the University of Leeds, UK. His research interests include digital/social media and open data with particular focus on their cultural significance in society. He is currently a member of faculty at the Pan-Atlantic University in Lagos, Nigeria, where he also heads the Open Data Research Centre, a research unit focusing on the impact of data on development in developing contexts.

**Edson Carlos Germano** is a professor and programme coordinator at FIA Business School, Brazil. He has a degree in Mechanical Engineering and a PhD in Business Administration from the University of Sao Paulo (USP), Brazil. With 15 years of experience in the architecture, development and implementation of IT solutions, his research interests include information systems, open government data, information security, public management, open data and its impact on society.

**Jack Hardinges** is a policy advisor at the Open Data Institute. He works across a number of projects at the ODI to develop, test and communicate policy related to data and technology. Jack joined the ODI in July 2014 and, as a co-author of Open Data Means Business, Open Enterprise, and a number of other reports, he has helped to develop the evidence base for the economic, societal and environmental impact of open data.

**Michael Christopher Jelenic** is a public sector specialist working in the World Bank's Governance Global, where he has contributed to lending and analytic projects in over 25 countries. His governance work likewise includes researching the impacts of open government, open data, transparency, and public accountability mechanisms as well as providing countries with technical assistance and capacity building support in the implementation of public financial management and public administration reforms.

**Therese Karger-Lerchl** is a senior economist at Vivid Economics, where she advises private and public sector clients on urban development strategies. When at the Open Data Institute, she focused on using open data to improve public services in cities. Therese previously worked at the South African National Treasury, KPMG and GIZ. She holds an MSc and BSc in Economics, from Barcelona Graduate School of Economics and Maastricht University, respectively.

**Bert Marcelis** is a system developer working for Samtrafiken in Stockholm, Sweden. He completed his master's in Information Engineering Technology at Ghent University where he was given the TomTom Best engineering thesis of 2018. He also works as a volunteer at the iRail APIs and is an advocate of open data.

## **About the authors**

**Miranda Marcus** works for the Open Data Institute. She leads the R&D Programme, an applied interdisciplinary programme combining economics, policy, technology and design to support trustworthy data-driven innovation in the public and private sectors. She is a digital programme manager specialising in agile delivery and digital strategy. Her background is in design and digital anthropology. Her personal research field focuses on the impact of engineering practices on medical artificial intelligence applications.

**Julio Paciello** is the president and director at Centro de Desarrollo Sostenible in Paraguay. He is a computer engineer with more than 15 years of professional experience in projects of software development, e-government, open data and ICT consultancy. He is also a professor at the National University of Asunción, with many scientific publications.

**Juan Pane** is the chief innovation officer at Centro de Desarrollo Sostenible in Paraguay. He has a PhD in Computer Science from the University of Trento, Italy and works as a consultant in open data and transparency for the World Bank, USAID, OAS and PAHO in Paraguay. He is also a lecturer and researcher for open data related topics at the National University of Asunción. His work has been published in many scientific papers and journals.

**Ed Parkes** is Director at Emerging Field, a data strategy and innovation consultancy. Having worked in data strategy in UK central government with organisations such as Ordnance Survey and the Met Office, he now works with social and public sector organisations to help them understand the opportunities to use data. He has worked for the Cabinet Office, Nesta, the Open Data Institute and the Government Digital Service.

**Nicolau Reinhard** is a senior professor of Management at the School of Economics, Administrations and Accounting of the University of São Paulo (USP), Brazil. His research interests include management of IT function, use of IT in public administration and IT implementation and impacts. Professor Reinhard has a degree in Engineering, a PhD in Management, and has also held executive and consulting positions in IT management in private and public organisations.

**Julián Rojas** is a PhD researcher at Ghent University, IDLab – IMEC. His work focuses on researching publishing strategies and web interfaces for linked open data. He mainly works on the mobility domain and is currently maintaining the linked open datasets for the main four public transport operators in Belgium. He is an advocate of open data and a main contributor of the open source route planning library Planner.js.

**Camila Salazar** holds an MSc in Applied Social Data Science from the London School of Economics and Political Science. She has experience as a data analyst in open data initiatives, training and research projects across Latin America and has worked as a data-driven journalist for international media organisations.

**Ilham Cendekia Srimarga** is a researcher and director at Sinergantara. He holds a master's degree in Development Studies and a bachelor's degree in Informatics from the Bandung Institute of Technology. He has conducted research on issues related to open data, ICT and development, governance, and public policy. He is also a practitioner of ICT and governance, which includes work on developing data revolution strategies in governance and in the social sector.

**Violeta Sun** holds a bachelor's degree in Business Administration. She received her master's and PhD degrees in Business Administration from the University of São Paulo, Brazil. She is currently a professor in Information Systems at the University of São Paulo. Her main research interests include project management, information technology management, IT infrastructure, IT governance, management systems in health and computer applications in public administration.

**Mathias van Compernolle** joined the Research Group for Media, Innovation, and Communication Technologies at Ghent University in 2013. He holds a bachelor's degree in social work and a master's degree in Public Administration. He is currently working on his PhD concerning open data and e-government within smart cities. He functions as policy and methodology lead at Smart Flanders. As an open data enthusiast on the board of Open Knowledge Belgium, he keeps track of open data policies in Belgium. Alongside this he lectures politics and organisation studies at Artevelde University College.

**François van Schalkwyk** is a post-doctoral research fellow at the Centre for Research Evaluation, Science and Technology (CREST), Stellenbosch University. François holds master's degrees in higher education studies (University of the Western Cape) and in publishing studies (Stirling University, UK), and a doctoral degree in science and technology studies (Stellenbosch University, South Africa). François's research areas include critical data studies, higher education studies and scholarly communication.

**Roza Vasileva** is a PhD candidate in Digital Economy with a focus on open data and cities at the Horizon Centre for Doctoral Training, University of Nottingham, UK. Roza has been an ICT and Innovations Consultant to the World Bank since 2012. She has supported open data and digital government projects in over a dozen countries and conducted Open Data Readiness Assessments (ODRA) following the World Bank standard diagnostic methodology.

## **About the authors**

**Ruben Verborgh** is professor of Decentralised Web Technology at IDLab, Ghent University, and a research affiliate at the Decentralized Information Group of CSAIL at MIT. Additionally, he acts as a technology advocate for Inrupt and the Solid ecosystem wherein people and organisations control their own data. He aims to build a more intelligent generation of clients for a decentralised web at the intersection of Linked Data and hypermedia-driven web APIs.

**Eveline Vlassenroot** holds a bachelor's and a master's degree in Communication Sciences. Having completed additional courses in Information Management & Security, she joined the Research Group for Media, Innovation, and Communication Technologies (www.mict.be) at Ghent University in 2017. She is involved in projects related to e-government and web archiving.

#### **SITUATING OF OPEN DATA: GLOBAL TRENDS IN LOCAL CONTEXTS**

**Open data and its effects on society are always woven into infrastructural legacies, social relations, and the political economy. This raises questions about how our understanding and engagement with open data shifts when we focus on its situated use.**

**To shed light onto these questions,** *Situating Open Data* **provides several empirical accounts of open data practices, the local implementation of global initiatives, and the development of new open data ecosystems. Drawing on case studies in different countries and contexts, the chapters demonstrate the practices and actors involved in open government data initiatives unfolding within different sociopolitical settings.**

**The book proposes three recommendations for researchers, policy-makers and practitioners. First, beyond upskilling through 'data literacy' programmes, open data initiatives should be specified through the kinds of data practices and effects they generate. Second, global visions of open data implementation require more studies of the resonances and tensions created in localised initiatives. And third, research into open data ecosystems requires more attention to the histories and legacies of information infrastructures and how these shape who benefits from open data flows.**

**As such, this volume departs from the framing of data as a resource to be deployed. Instead, it proposes a prism of different data practices in different contexts through which to study the social relations, capacities, infrastructural histories and power structures affecting open data initiatives. It is hoped that the contributions collected in** *Situating Open Data* **will spark critical reflection about the way open data is locally practiced and implemented. The contributions should be of interest to open data researchers, advocates, and those in or advising government administrations designing and rolling out effective open data initiatives.**

**AFRICAN MINDS**

**SITUATING OPEN DATA**

Edited by Danny Lämmerhirt, Ana Brandusescu, Natalia Domagala & Patrick Enaholo

GLOBAL TRENDS IN LOCAL CONTEXTS

**OPEN DATA**

SITUATING


Pleura - A Surgical Perspective *Edited by Alberto Sandri*

Published in London, United Kingdom

### *Supporting open minds since 2005*

Pleura - A Surgical Perspective http://dx.doi.org/10.5772/intechopen.95744 Edited by Alberto Sandri

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*3.2. Modeling the Notification Message Structure*

As stated in the Main Components section, the notification generator can build customized notifications and plan their delivery by using the information stored in the non-structured database. Notifications are dispatched to the proper smart devices thanks to the notification dispatcher and the MQTT broker. In addition, the recipient devices also have the technical ability to send acknowledgement notifications to the dispatcher (if required).

To build a flexible and scalable system, the notification message structure has been modeled to be independent of the notification mechanism, the application's context and the target device.

Notifications are encapsulated within MQTT messages and therefore, both, the notification devices and the notification dispatcher should implement the MQTT stack and operate as MQTT clients. While the notification devices use an embedded lightweight version of the MQTT client which can be loaded into the memory of the microcontroller; the notification dispatcher, for its part, implements a full-featured standalone client.

Since the non-structured database and the logic that governs the notification generator and the notification dispatcher work with JSON data, the notification has also been modeled as a JSON object which can be enclosed in the MQTT message, instead of using plain text. The JSON syntax provides a flexible mechanism to build a general notification scheme that can be adapted to many application's contexts and notification devices.

The use of this notification model is very valuable. When the notification is defined and queued to be delivered, the generator does not know which device would be used to deliver the notifications. Therefore, a flexible format allows storing the notification content independently to other metadata. Moreover, the same notification can have content in different formats (e.g., audio, text, and figure) and that information would be used depending on the device that is selected to deliver the notification.


**3. Circadian rhythm disruption affects therapeutic effects and toxicity of xenobiotics in the liver**

**Table 1** gives a few examples of how the disruption of circadian clock could affect drug effect and toxicity. Most of the examples used genetic models with disruption of circadian clock genes or administration of drugs at different times.

Carbon tetrachloride is a commonly used hepatotoxicant. In SD rats, administration of CCl4 in the afternoon showed more toxicity than administrated in the morning, the increased toxicity was accompanied by the lowest hepatic GSH levels in the afternoon [36]. Acute CCl4 toxicity was increased in Per2−/− mice. At the 12-h time point after CCl4 treatment, more vacuolations were observed in the liver tissues of Per2-null mice as compared to wild-type (WT) mice, and at 24 h after CCl4 treatment, more severe hepatic necrosis was evident than that occurred in WT mice. A deficit of the Per2 gene enhanced Ucp2 gene expression levels in the liver leading to reduced ATP and increased production of toxic CCl4 derivatives. The absence of Per2 also caused an increased expression of Clock gene [37]. Per2-null mice were not only sensitive to CCl4 -induced acute hepatotoxicity, but also to CCl4 -induced chronic toxicity and fibrosis. CCl4 caused much more severe liver fibrosis and activated hepatic stellate cell (HSC) in mPer2 null mice as compared to WT mice. Per2-null mice exhibited less efficiency in fibrosis resolution and apoptosis resistance in HSC. Transfection of Per2 cDNA into CCl4 -exposed HSC restored apoptosis sensitivity with up-regulation of the TRAIL-R2/ DR5 signaling pathway [38].

was no difference of acetaminophen toxicity between Per2-null and WT mice, but at 20:00 when the Per2 expression is highest, Per2-null mice had less liver injury, with less Cyp1a2 expression to bio-activate acetaminophen [40]. In another study, acetaminophen toxicity is greater at Zeitgeber time (ZT)14 than at ZT2, and clock-deficient mice are resistant to the toxicity at ZT14, with prolonged pentobarbital sleep time (PBST), indicating the reduced activation of acetaminophen [41]. Use Bmal1 mutant mice (Bmal1fx/fxCreAlb), the acetaminophen toxicity at ZT12 was decreased, along with decreased APAP protein adducts and altered acetaminophen metabolism kinetics (increased AA-Gluc), possibly due to decreased NADPH-cytochrome P450 oxidoreductase gene expression and activity at ZT12, as compared to WT mice [42].

**Drug/toxicant Animal models Chronotoxicology References**

Carbon tetrachloride Per2−/− mice Acute toxicity increased in Per2−/− mice [37]

Acetaminophen KM mice 18:00 toxicity >6:00 [23] Acetaminophen Per2−/− mice Toxicity decreased in Per2−/− mice [40] Acetaminophen Clock−/− mice Toxicity decreased in Per2−/− mice, with

levels

Per2−/− mice

prolonged PBST

induction of Cyp1a1

induction of Cyp1a1

metabolic enzyme genes

apoptosis tolerance

to low level of GSH at ZT8

Cyp1b1

fibrosis

Per1−/−/Per2−/− mice Lost diurnal variation in bile acid

ZT17

half-life

adducts, altered APAP metabolism

Circadian Clock Gene Expression and Drug/Toxicant Interactions as Novel Targets…

Abolished diurnal variation of TCDD

Abolished diurnal variation of B[a]P

[36]

19

http://dx.doi.org/10.5772/intechopen.74597

[38]

[41]

[42]

[43]

[44]

[45]

[46]

[47]

[48]

[49]

[51]

[52]

Carbon tetrachloride SD rats 18:00 toxicity >6:00, with lowest GSH

Carbon tetrachloride Per2−/− mice Chronic toxicity, fibrosis increased in

Acetaminophen Bmal1fx/fxCreAlb mice Reduced toxicity, reduced protein

Dixon (TCDD) Per1Idc,Per2Idc, Per1/Per2Idc mice

Benzo[a]pyrene Clock mutant (Clk/Clk)

Cholestyramine diet restricted feeding

mice

**Table 1.** Circadian clock gene expression as novel targets in toxicology.

Dixon (TCDD) Per1Idc,Per2Idc mice, cells Increased TCDD induction of Cyp1a1,

Bile duct ligation Per2−/− mice Increased BDL-induced liver injury and

Isoniazide Swiss mice Isoniazid hepatotoxicity at ZT1 > ZT9,

Chlorozoxazone Wistar rats Diurnal variation in CYP2E1 affect its

Diethylnitrosamine (DEN) Clockmut mouse hepatocytes Decreased DEN metabolism and

Cadmium ICR mice Toxicity at ZT 8 > ZT 20, corresponding

Alcohol Per1−/−, Per2−/− mice Less susceptible to alcohol toxicity [50]

Acetaminophen hepatotoxicity also displays diurnal variations. When given acetaminophen in the afternoon, toxicity was greater than that given in the early morning [23, 39]. At 8:00, there

**Table 1.** Circadian clock gene expression as novel targets in toxicology.

*Diurnal variation of hepatic Phase-II metabolism gene/proteins*. Glucuronide and sulfate conjugations are major Phase-II pathways in the biotransformation and elimination of a wide variety of endogenous compounds, drugs, and other xenobiotics. Diurnal variations of these Phase-II reactions were reported in the 1980s [32]. Consistent to the variation in the conjugation reactions, the expression of Ugt1a5, 2a3, 2b34, 2b36 and UDP-gpb, as well as Sult1a1, 1a5, and Sult5a1, all show diurnal oscillations [20]. Hepatic GSH has the trough at dusk [30], and the activities of GSH S-transferase [33] were lower at the dark phase and the expression of Gst1a1/1, Gst1a4, Gstm2, and Gstt1/2 display diurnal rhythms which are generally lower in the dark phase [20]. *Diurnal variation of hepatic Phase-III efflux transporters*. P-glycoprotein is the major efflux pump in the liver, and its expression shows circadian variation together with the diurnal expression of Abcb1 [34]. In addition to P-glycoprotein, hepatic multidrug-resistant protein 2 (MRP2), breast cancer resistant protein (BCRP) also show circadian oscillations [35]. Diurnal variations in hepatic mRNA expression of multidrug-resistant gene 1a (Mdr1a), Mrp2, and Bcrp were

Diurnal variation of hepatic Phase-I, Phase-II, Phase-III, and the nuclear transcription factors would affect the xenobiotic metabolism when administered at the different times of the day

**Table 1** gives a few examples of how the disruption of circadian clock could affect drug effect and toxicity. Most of the examples used genetic models with disruption of circadian clock

Carbon tetrachloride is a commonly used hepatotoxicant. In SD rats, administration of CCl4 in the afternoon showed more toxicity than administrated in the morning, the increased toxicity was accompanied by the lowest hepatic GSH levels in the afternoon [36]. Acute CCl4

vacuolations were observed in the liver tissues of Per2-null mice as compared to wild-type

that occurred in WT mice. A deficit of the Per2 gene enhanced Ucp2 gene expression levels

absence of Per2 also caused an increased expression of Clock gene [37]. Per2-null mice were

late cell (HSC) in mPer2 null mice as compared to WT mice. Per2-null mice exhibited less efficiency in fibrosis resolution and apoptosis resistance in HSC. Transfection of Per2 cDNA

Acetaminophen hepatotoxicity also displays diurnal variations. When given acetaminophen in the afternoon, toxicity was greater than that given in the early morning [23, 39]. At 8:00, there

treatment, more severe hepatic necrosis was evident than

caused much more severe liver fibrosis and activated hepatic stel-

treatment, more

derivatives. The

to impact their efficacy and toxicity, the time really matters [15].

**toxicity of xenobiotics in the liver**

18 Circadian Rhythm - Cellular and Molecular Mechanisms

(WT) mice, and at 24 h after CCl4

not only sensitive to CCl4

toxicity and fibrosis. CCl4

DR5 signaling pathway [38].

into CCl4

genes or administration of drugs at different times.

**3. Circadian rhythm disruption affects therapeutic effects and**

toxicity was increased in Per2−/− mice. At the 12-h time point after CCl4

in the liver leading to reduced ATP and increased production of toxic CCl4

also evident [20, 35].

was no difference of acetaminophen toxicity between Per2-null and WT mice, but at 20:00 when the Per2 expression is highest, Per2-null mice had less liver injury, with less Cyp1a2 expression to bio-activate acetaminophen [40]. In another study, acetaminophen toxicity is greater at Zeitgeber time (ZT)14 than at ZT2, and clock-deficient mice are resistant to the toxicity at ZT14, with prolonged pentobarbital sleep time (PBST), indicating the reduced activation of acetaminophen [41]. Use Bmal1 mutant mice (Bmal1fx/fxCreAlb), the acetaminophen toxicity at ZT12 was decreased, along with decreased APAP protein adducts and altered acetaminophen metabolism kinetics (increased AA-Gluc), possibly due to decreased NADPH-cytochrome P450 oxidoreductase gene expression and activity at ZT12, as compared to WT mice [42].

In Per1, Per2-deficient mice, the ability of AhR ligand dioxin (TCDD) to induce the Cyp1a1 and Cyp1b1 was enhanced, especially with targeted interruption of Per1 [43]. TCDD induction of Cyp1a1 was 23–43 fold greater during the night time (ZT18) than at the day time (ZT6) in WT mice. However, the diurnal variation in the TCDD induction of Cyp1a1 expression was abolished in Per1ldc, Per2ldc, and Per1ldc/Per2ldc mutant mice, suggesting that Per1, Per2 and their timekeeping function in the circadian clockworks mediate the diurnal variation in TCDD induction of Cyp1a1 [44]. Clock mutant Clk/Clk mice failed to show typical oscillation of AhR expression, and BaP (an AhR ligand) induction of Cyp1a1 was disrupted [45].

In Per2−/− mice, bile duct ligation (BDL)-induced liver injury and fibrosis was increased, along with increases in TNFα, TGFβ1, Col1α, and TIMP1 in livers of Per2-null mice as compared to WT mice [46]. In Per1−/− and Per2−/− mice fed on 2% cholestyramine diet, and/or restricted feeding (phase-shift peripheral clock), liver bile acid levels were increased, and the nuclear receptors CAR and PXR were activated, together with the increased serum enzyme AST levels, indicative of liver damage. In these Per1−/− and Per2−/− mice, the circadian expression of key bile acid synthesis and transport genes, including Cyp7a1 and Ntcp, was lost [47].

The hepatotoxic potential of antituberculosis drug isoniazid varied when it was administered at ZT1, ZT9, and ZT17, and the toxicity was highest when isoniazid was given at ZT1 [48]. Chlorzoxazone is a CYP2E1 metabolized drug, and its kinetics and half-life were altered with the diurnal variation of CYP2E1 activity. The value of chlorzoxazone half-life in plasma of the light phase group was significantly longer than the dark phase group, with an increase of 6-hydroxychlorzoxazone production [49]. Acute alcohol-induced higher toxicity at ZT13 than ZT1 when Per1 and Per2 were highly expressed. Per1−/− and Per2−/− mice were less susceptible to alcohol hepatotoxicity, especially in Per1 null mice. Per1 null mice had decreased expression of peroxisome proliferators-activated receptor-gamma and its target genes related to lipid metabolism such as Srebp1, fatty acid synthase (Fas), CD36, diacylglycerol O-acyltransferase 2 (Dgat2), AP2, and adipsin [50]. In primary hepatocytes isolated from Clock mutant Clk/Clk mice and WT mice, diethylnitrosamine (DEN) induced apoptosis and cell death were reduced in Clock-deficient mice, probably due to decreased DEN metabolism [51]. Cadmium hepatotoxicity is independent of metabolic activation; while its mortality was high at ZT8 than ZT20 when the hepatic GSH level was lowest [52].

producing a Parkinson-like syndrome, but it also produces liver injury. In an attempt to examine the effect of Mn on the central and peripheral clocks, rats were given Mn 1 and 5 mg/kg, ip, every 2 days for 1 month, and the hypothalamus and liver were removed to examine the clock gene expression (**Figure 2**). The results showed that Mn-induced aberrant expression of circadian clock genes in both hypothalamus and liver, and liver was more sensitive to Mn-induced decreases in clock gene Bmal1, Per1, and increase in Dbp, indicating that both central and peripheral clocks could be disrupted by drugs/toxicants [53]. Another example is chronic alcohol administration. Chronic alcohol consumption produced disruption of circadian clock gene expression in both central (hypothalamus) and peripheral tissues (liver and colon) [54], and the liver appeared to be more susceptible than brain in alterations of metabolic genes and core molecular clock disruption. In addition to the fatty liver and affected the diurnal oscillations of metabolic genes (alcohol dehydrogenase 1, carnitine palmitoyltransferase 1a, Cyp2e1, Phosphoenolpyruvate carboxykinase 1, pyruvate dehydrogenase kinase 4, Ppargc1a, Ppargc1b and Srebp1c), the diurnal oscillations of core clock genes (Bmal1, Clock, Cry1, Cry2, Per1, and Per2) and clock-controlled genes (Dbp, Hlf, Nocturnin, Npas2, Rev-erbα, and Tef) were altered in livers from ethanol-fed mice. In contrast, ethanol had only minor effects on the expression

**Figure 2.** Neurotoxicant manganese intoxication produced aberrant expression of circadian clock genes in both central

Circadian Clock Gene Expression and Drug/Toxicant Interactions as Novel Targets…

http://dx.doi.org/10.5772/intechopen.74597

21

of core clock genes in the suprachiasmatic nucleus (SCN) [55].

(hypothalamus) and peripheral (liver). Adapted from Li et al. [53].

**chronopharmacology**

examples including our work in the field.

**5. Drugs affect circadian clock gene expression as a novel target of**

Many drugs/toxicants could affect central and peripheral circadian clock gene expression as targets of chronopharmacology and chronotoxicology [10]. **Tables 2** and **3** provide some

Thus, alterations of diurnal oscillations would affect drug metabolism, efficacy, and toxicity. On the other hand, drugs could target circadian clock gene expressions to produce biological effects, which will be discussed below.