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Public Data Analytics: Community Problem Solving

VOLUME 2 of the OCDex Public Data Analytics Series

Data science and analytics has demonstrated its power in informing decision-making and problem-solving. Data can reveal trends and insights that would have otherwise been obscured. It can give decision-makers key information needed to craft effective and optimal solutions to organizational problems. It can help predict potential bottlenecks and challenges, so that organizations may come prepared when it happens. Data science and analytics is a sought out
skill in the digital age.

The Covid-19 pandemic and its resulting limitations on mobility has forced many transactions and communications to migrate from the physical space to the digital space. This sudden global digitalization resulted in an increase in data produced and a subsequent increase in the potential game-changing insights that these data may be hiding.


While many in the private sector have been seen leveraging the power of data for business insights and maximization of revenue, the public sector is yet to catch up in terms of digitalization and data utilization, especially in developing countries. The power of data would especially help communities and local governments in coming up with efficient, effective, and inclusive policies and solutions to problems.


The aim of the 2022 OCDex project run is to bring data scientists and analysts together, and demonstrate how analysis of government data can be used to help solve problems in local communities. The project aims to demonstrate how it can help inform local policymaking and project planning, and how citizens and researchers can participate and help their respective local government units in overcoming community challenges hand-in-hand. This handbook hopes to convince local governments and authorities to invest in good data housekeeping and integrate data science and analytics into their decision-making.


This handbook features how academics and data enthusiasts used public data to help inform solutions to various community problems such as healthcare, inclusivity, and accessibility for persons with disabilities, fairness, and transparency in public procurement, and ensuring enough supply of utilities. Lastly, this handbook presents a replicable model of cooperation between local governments and their local researchers and data enthusiasts toward the effective use of data science and analytics for community building.

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For more information, questions, suggestions, and submissions, please e-mail learning@layertechlab.com

Reflections: How analysis of government data can help LGUs, NGAs, and local communities

Comment

Author: Roben A. Juanatas (CCIT – National University)

Analysis of government data, in my opinion, has the ability to bring about considerable change for the LGU or community. Local governments are particularly enthusiastic about promoting this new approach to community engagement. Many local governments have begun to see the value of analyzing government data for more open and transparent operations. The study of government data can assist the LGU in staying connected, informed, and up-to-date with their community’s day-to-day operations. 

Furthermore, this trend may aid the LGU in continuing to deliver and make decisions that are in the best interests of the community. It also opens up new possibilities for local government applications, boosts community interest, and can lay the groundwork for new technology innovation and economic progress. Furthermore, data analysis can provide relevant facts, which can serve to bring a community together and empower them to create the future.  

Finally, it is not simply the simplification of the community’s operations and proving progress toward strategic priorities that fosters community confidence through data analysis. It is important in a variety of government areas, including education, employment, manufacturing, agriculture, and criminality, to name a few. The information gathered in LGU can be used to develop strategic policies and provide insights to make better judgments. 

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: rajuanatas@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Data Analytics a way to solve the crisis in education: A local setting approach

Comment

Author: Ramon L. Rodriguez (National University – Manila)

The current pandemic highlights further the problem in the educational sector in the country. Even before the pandemic, the World Bank conducted an assessment of the country’s education system and found that a crisis in education existed. As we know, education is one of the foundations for the success of every community. Can we develop strategies to address this crisis using data analytics in the local settings? The LGU should explore this strategy to develop a concrete solution based on data. Decisions of developing new programs should be data-driven, especially in the local government settings.

If data-driven decisions are highly utilized, many improvements can be made to every LGU, including fiscal adequacy. Suppose the LGU has updated data on the profile of students, households, and problems encountered by every student. In that case, it can be a basis for a new strategy for addressing issues in education. Say, for instance, what support is needed by certain schools and what resources. The data may be available, but it is important to structure it and become ready for analysis. At this point, data analytics plays a significant role.

On the other hand, data analytics can also be used to match the needs of every LGU in terms of job availability on a local and global scale. The matching gap in skills needed in the industry has been highlighted for years, but actions to address this are still not concrete. However, different agencies have undertaken several initiatives but not enough to solve the problem. Almost every LGU in the Philippines has community colleges where locals can enroll. The intention of establishing community colleges is anchored on the principle that education is one of the backbones of community development. Having a community college is a great idea, but we have to make sure the programs offered are sustainable and benefit the family. We also want to avoid underemployment scenarios wherein graduates are employed not in their respective specialization. If we have data on the graduates and the skills needed in the local, national and global, then it is easy for us to match and decide what programs can be offered by schools. The budget for education is allocated per LGU. At the national level, almost 16% of the national budget is for education, but still, we have a crisis in education. The need to use data analytics in addressing issues in the education sector is a must.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: rlrodriguez@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: Data to help Cities and Municipalities

Comment

Author: Nico O. Aspra (Bicol University)

In our generation today, technology has rapidly consumed everyone. It has rooted itself in the core foundation of modern society. With various age groups, even toddlers, access to technology is easy. As such, it has enabled agencies or companies to gather data from their users. With this accessible data, inevitably, advertisers specifically target consumers by their liking through the use of available information to gain more profit. With this in mind, this has revolutionized the advertising world from its traditional delivery to tailor-fitted advertisements. Policymakers can also utilize this strategy to tailor-fit the community’s specific needs. Local government units can benefit through data analytics by collecting and analyzing municipal- or city-wide information regarding a certain topic and thereby utilize this data to address problems or issues accordingly. Before the data even reaches the regional or national level, it can already be organized at the local level. Consequently, data will be more systematic and available at all levels of government, and if the data permits, challenges, and problems can be more easily addressed.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: nico.aspra@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: How do you think data and analytics can help your LGU, NGAs, and/or community and how do you propose ways to do it?

Comment

Author: Gabriel Avelino Sampedro (National University)

In the age of digitalization, everything is done online. Most of the data collected from people are stored in the cloud entities, and the amount of data stored there exponentially increases daily. It can be challenging to organize, manage, and obtain insights from various sizes and varieties of data. One solution for managing massive amounts of data is implementing self-serving, automated solutions to daily operations such as data input and reporting, which can improve efficiency and increase the efficacy of the mission. Data analytics plays a significant role in obtaining insights from our data in managing data. Data analysis is the process of studying data by using analytical or statistical methods in order to discover important information. The goal of this process is to conclude the data. The data analytics process helps us develop a clearer picture of the current situation for decision-makers to provide data-driven solutions to problems. The conclusive findings may come in a summary or an image, like a chart or graph. Showing data visually, which makes the job simpler, is known as data visualization. Data analysis may be done using various methods, including data mining, text analytics, and business intelligence. Data analysts use charts and graphs rather than tables or databases to convey data. It simplifies complex facts and makes it easier for the eyes to take in the information. Furthermore, data analytics may even assist in preventing fraud, waste, and abuse and helping with staffing shortages.

Using the knowledge obtained from the OCDex training, one possible application of using data analytics is for predicting arrival times of mass transportation systems. One of the significant issues in the country is the poor transportation system we have. Train stations encounter very long lines, and not everyone in line will immediately be served. One of the main issues in the system is the uncertainty of arrival times. People would go to train stations randomly, hoping to ride the train. The long wait can be pretty frustrating, and plans made throughout the day can be ruined. Although it will not entirely solve the whole issue, one way to solve this is to develop a system for predicting the arrival times of trains. In addition, providing people with data on the number of people on the platform (through the data from gate entries) can help people make data-driven decisions about their travel. The purpose of the system is to decongest some modes of transport and allow people to consider other options. The solution would use data from the station platform and logs of train operators to develop a machine learning-based model to improve this process.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: garsampedro@national-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflection: The Study of Pandemic Resilience on Impoverished Municipalities

Comment

Author: Shehab D. Ibrahim (Mindanao State University – Iligan Institute of Technology)

Pandemic orders are declared to protect public health. However, some of these orders are more challenging to comply for impoverished or vulnerable groups. Let’s take the staying at home policy as an example. Vulnerable groups have no choice but to go out to work despite the great physical risk.

The researcher will investigate the pandemic resilience of the municipalities with high poverty incidence. Specifically, the researcher will look into the spread of the poverty index across the municipalities in the Philippines, study the correlation between pandemic resilience/ preparedness and social statistics of the municipalities, and determine the important factors (e.g. ICT and healthcare system investments) in developing pandemic resilience and provide data visualizations to aid decision-makers.  The data will be taken from the DOH public open data repository,  OpenStat database from the Philippines Statistics Authority (PSA), and other Philippines open government data repositories.

The researcher plans to create a Dynamic Poverty Heat Map through Geographical Information System (GIS) to show the poverty levels of every municipality. Spatial autocorrelation can also be performed to measure the autocorrelation of municipalities (through its polygon representations). This is to determine the pattern of the spatial position of municipalities and the poverty rate and evaluate if it is clustered, dispersed, or random. Also, the researchers will determine significant attributes from the DOH and OpenStat Database specifically related to Pandemic Resilience and Social Statistics of municipalities. A correlation heatmap can be visualized to show the relationship between these attributes. Finally, the researcher will create a model that will use the Social Statistics attributes as the features (independent variables) and the Pandemic Resilience attribute as the targeted variable (dependent variable). Models that can determine the important predictor variables, such as Lasso and Ridge regression, will be used. This will be helpful in determining the factors that may lead to developing pandemic resilience.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: shehab.ibrahim@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

Accountable Public Management of Funds for Local Government Units

Comment

Author: Rabby Q. Lavilles (Mindanao State University – Iligan Institute of Technology)

The transparency of budget allocation and utilization of public funds among local government units are indicators of good governance at the grassroots level.

The interactions of citizens and government, particularly local government units (LGU), create a connection that helps establish a mutual relationship for a forward-thinking development. One aspect that takes a major role in this healthy relationship is transparency and accountability. Transparency of government spending is based on the intended plans and allocated funds, and the accountability of the authorized government representative to justify the actions they made. These two important attributes helped established trust in government.

While the national government allocations for local funds have been defined by various policies, laws, and guidelines, data for reporting at the local level has a limited assessment of how it performs and is aligned with national priorities. Knowing these priorities and how local government units respond to aligned to national priorities matters in achieving various government programs. For example, the national government allocated local government funds for its priority programs like the Assistance to Disadvantaged Municipalities. The fund is intended to support the basic services for the implementation of their priority programs or projects. For example, in this case, providing basic services such as water systems projects, access roads, or disaster-related facilities. On the other hand, reporting for appropriation and projects of LGU is also reported.

Given the situation, it is imperative that a monitoring tool can be developed to provide alignment of the LGU fund appropriation and the national government spending. Moreover, this is also a proper way to examine if the allocated programs were spent based on their original allocation. Using published LGU data (e.g. https://www.iligan.gov.ph/wp-content/uploads/2020/06/Annual-Budget-Report-2020.pdf), a structured data can be created to organize the uploaded data by the LGU. This activity can be done through volunteer programs such as in a university workshop for open data government. Using data and related analytics tools can be a good way to provide a summary and comparison of various government allocations and LGU’s actual implementation of the program. Although data collection and organization can be daunting, the resulting open data that can be generated will help evaluate citizens on how LGU has been performing in terms of its priorities or mandates. Moreover, this will also create an observing tool for government officials to be aware of government spending and priority.

The power of data and related platforms to establish transparent government spending can be a step toward more accountable local government officials. It is important that citizens will be able to see where their taxes go and how the elected government officials improve the community in relation to government priorities.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: rabby.lavilles@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

Maragondon and Ternate Tourism: Managing Riders and Businesses

Comment

Author: Mark Emmanuel Malimban (National University)

Maragondon and Ternate are municipalities located in the southern part of Cavite. These rural areas are rich in history and culture: Ancestral houses, Churches, and Historical sites can be found here. Mountains and many types of bodies of water are also enjoyed by the locals and tourists.

Bikers and motorists were commonly seen roaming around the vicinity. These groups come in small to big groups mostly coming from other areas and cities. Popular destinations of these riders are the Kaybiang Tunnel and the stretch road of Maragondon-Ternate-Nasugbu with the scenic beaches; with these, a lot of businesses have sprouted in the area which helps the local and LGU.

The increase in riders in the area doesn’t only come with advantages, some unfavorable circumstances were also identified. LGU placed some necessary steps to reduce some of these inconveniences and concerns.

Data analytics can help in developing the policy for government efficiency and resiliency. Bikers’ regulations for compliance with national directives; peace and order structure for tourists especially riders; and management of businesses in terms of investment and promotion. Analysis can also be used as a reference in devising the Disaster Risk Reduction Plan and Local Risk Assessment.

Opportunities should not be wasted, they should be managed well to increase their potential. LGU Policies and regulations should be data-driven to ensure that all perspectives and opinions were considered. Managing and establishing appropriate directives for these bikers and motorists will ensure not just safety but also the progress of the community.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: memalimban@gmail.com or Layertech labs support at learning@layertechlab.com

Reflections: How the Academe can Leverage Data and Analytics to Help LGUs

Comment

Author: Mia Amor C. Tinam-isan (Mindanao State University – Iligan Institute of Technology)

Data analytics has been the talk of the town. It finds its way across agencies (government or private), businesses, or various institutions in discovering valuable information about the existing and overwhelming amount of data. Data in these times exponentially increase and extracting valuable information from these data is essential. Information from the analysis can be used for decision making, coming up with a good marketing strategy, or even in establishing policies and guidelines from a broad test base. However, local government units per se in various parts of the Philippines, have not yet maximized the impact of data analytics. Varying factors might contribute to this such as unorganized data and non-computerized processes.

As part of the academic community, we can implement programs, webinars, and workshops that will empower our LGU to exploit their available data. It is imperative to partner with NGAs, and LGUs, and develop a working strategy for local government digitization. We can propose a simple initiative and start from the automation of LGU processes to organize and ensure the quality and the integrity of data for analysis. We can also venture into partnering with private agencies such as OCDex which has experienced in partnering with LGUs and had already developed numerous government data analytics applications. As of the moment, the College is continuously having a dialog with different offices of LGU-Iligan in crafting MOA for the digitization of the city government.

This article is the author’s reflection on the insight gained from the recently concluded OCDex 2022 Public Data Analytics Fellowship Trainings.

For more information about the article, please reach out to the author: miaamor.catindig@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com

Educated Spending: An Insight on SUCs Utilization of MOOE

Comment

Author: Sittie NB Pasandalanb (Mindanao State University – Iligan Institute of Technology)

Despite the reality of reduced budgets of the education sector especially of state universities and colleges (SUCs), institutions of learning have a good share of the annual National Expenditure Plan of the government. Generally, appropriations of SUCs can be categorized into three: Personnel Services (PS), Capital Outlay (CO), and Maintenance and Other Operating Expenses (MOOE). Of these three categories, the MOOE should be of great interest as this gives insight to how a higher education institution (HEI) of the government utilizes government funds, ergo tax payers’ money.

MOOE is funds to be used for necessities (such as electricity and water) and for activities. HEIs are institutions expected to promote conservation of energy, it is worthy to look into the electricity and water bills of HEIs as these would speak of how HEIs are walking the talk. As employees of HEIs are taxpayers themselves, spending for activities should be examined to determine judiciousness in utilizing government funds, ergo taxpayers’ money. 

There is the disconnect between spending from one’s own pocket to spending from another’s pocket. Most likely, one finds it easier to spend from another’s pocket than one’s own. This begs the question of whether employees in HEIs (taxpayers in HEIs) can connect with the funds allocated to HEIs as taxes they have paid to the government, ergo their money. 

In the case of MSU-IIT, the MOOE for 2021 amounted to Php 297,321,732.24 (from Php 222,402,237.68 in 2020). The question on how the amount was utilized and if the expenses are necessities or mere expenditures to utilize funds allocated by the government begs to be answered. 

This article is a reflection on the OCDex 2022 Fellowship Programme for Researchers

For more information about the article, please reach out to the author: sittie.pasandalan@g.msuiit.edu.ph or Layertech labs support at learning@layertechlab.com