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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

Reflection: Using Data Analytics to Gain Insights from Citizens’ Feedback

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Author: Jennifer Llovido (Bicol University)

Government data is a powerful resource that can influence public opinion, citizen services, economic development, government success, and a variety of other aspects. The government’s goal of transparency necessitates access to and management of data. Government data analysis helps both the public and private sectors acquire insights into the current situation of the state, which acts as a guideline for policymaking. The government’s adoption of technological developments in data storage and improved analytics allows for a much more comprehensive understanding of people. The potential for using data in government to provide more efficient, effective, and trustworthy public services is practically limitless.

Recognizing the importance of data as one of an organization’s most important assets, it is practically worthless without supporting technologies to mine, process, organize and analyze it. The official website of the Local Government Unit of Legazpi provides a feedback and query portal that would foster civic engagement by soliciting feedback and suggestions from the local populations as it extends the consultation processes beyond the traditional face-to-face meetings. The said portal could also be implemented at the level of the various barangays, where Legazpeños would be encouraged to give their feedback and participate in the continuous improvement of public services. It would further promote data-driven decision-making as well as result in the production of quality datasets to encourage researchers and innovators to conduct studies and provide innovative solutions that would help solve issues of the LGU Legazpi. Further, citizen feedback may be visualized into tabulations and graphs that can be used to gain insights, and detect sentiments, trends, and public opinion. The opportunity of maximizing the use of the data at hand by improving visualizations and making it more informative with the application of data analytics is recognized.

As a resident of Legazpi City and a member of the academe, I envision the possible improvement of the LGU Legazpi website with the provision of enhanced data analysis and visualizations of the feedback and query portal data by employing new methods for modeling and analyzing data, including advances in natural language processing and visualization. More meaningful visualization for each question in the portal may be developed and utilized to enhance the presentation of data and effectively share the results back to Legazpeños. The end goal of this is to encourage Legazpeños as well as visitors of the city to give unbiased and useful feedback with the use of cloud computing leading to data-driven governance in the city. This could further improve the policymaking processes as well as make government policies more relevant to citizens at the level of the local government of Legazpi City. Its benefits are intended to benefit a wide range of stakeholders, including the economically and politically disenfranchised. The results are foreseen to provide actionable insights for good decision-making and support the development of evidence-based solutions for solving community issues in Legazpi City.

his 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: jllovido@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflection: The Study of Pandemic Resilience on Impoverished Municipalities

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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

Reflections: Data Analytics for Social Development

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Author: Mary Joy Canon (Bicol University)

Exploiting data through machine learning and analytics has been a trend solution in helping the government and other organizations alleviate pain in terms of social and economic aspects. Tools and methodologies in data analytics are used to generate insights, to recommend actions and more importantly to assist authorities in policy-making and translating these analyses to sound programs which directly benefit the people.  Perhaps, different organizations through their projects have already contributed, through data science, to social development and welfare. Kaggle, for instance was able to predict poverty levels to identify where the highest need is for social welfare assistance. This kind of project wouldn’t have been possible without access to data.

In the Philippines, the aim of social development mandated under the Constitution is to enact measures to protect and enhance the right of the people to human dignity, reduce social and economic inequalities and remove cultural inequities. Open data and analytics offer significant contribution and opportunities for the government and other bodies to create social impact.

Humanitarian Data Exchange of OCHA publicly made available a consolidated dataset on social development from World Bank Open Data. Data covers child labor, refugees, gender issues and disparities with key topics on education, health, labor force participation and political participation. This compilation of data, once processed and analyzed can be utilized in projects for social impact. The analysis can serve as an aid to identify the social issues or concerns that need immediate action by making essential benefits and services more accessible to the people. Data scientists, government officials and social sector leaders can work together to come up with a data-driven solution to take a major step forward in providing social transformation.

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: mjpcanon@bicol-u.edu.ph or Layertech labs support at learning@layertechlab.com

Reflections: Using Data Analytics to Validate Philippines’ occupational gender segregation

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Author: Christian Sy (Bicol University)

The World Economic Forum’s Global Gender Gap Report of 2021 recognized the Philippines as the best-performing country in Asia in terms of gender equality. It ranked 1st in Asia and 17th out of the 156 countries. The Global Gender Gap Index (GGGI) is a significant indicator of gender disparity worldwide. It is useful for tracking the extent of access to resources and opportunities and differences between men and women. It adopts four key dimensions that include 1. Economic Participation and Opportunity, 2. Educational Attainment, 3. Health and Survival, and 4. Political Empowerment.

The Philippines have almost closed the gender gap for educational attainment and health and survival gaps with an index score of 0.999 and 0.979, respectively out of the perfect score of 1. On the other hand, economic participation and opportunity, and political empowerment are trailing with 0.792 and 0.353 index scores. This is primarily because of the gender gap in employment opportunities for women, and statistically, there are too few seats in government-held for women.

With this, we can explore a textual analysis of multi-domain, multi-source, and multi-year articles through big data analytics to validate the Philippines’ occupational gender segregation along with the economic participation and opportunity dimension of the Global Gender Gap Index (GGGI). The result of this textual analysis may be utilized to improve institutional transformation and policy formulation for equalizing economic participation and opportunity for women.

References

[1]        M A R C H 2 0 2 1 Global Gender Gap Report The analysis presented in the Global Gender Gap Report 2021. 2021. [Online]. Available: http://reports.weforum.org/global-

[2]        R. R. Sharma, S. Chawla, C. M. Karam, “Chapter 10: Global Gender Gap Index: World Economic Forum Perspective”, 2021, DOI:88975728.00017.

[3]        T. Mehdi, “Global Gender Gap Index: A Stochastic Dominance Approach,” SSRN Electronic Journal, Sep. 2020, doi: 10.2139/ssrn.3663281.

[4]        R. E. Matland, “Women’s Representation in National Legislatures: Developed and Developing Countries,” Legislative Studies Quarterly, vol. 23, no. 1, p. 109, Feb. 1998, doi: 10.2307/440217.

[5]        C. L. Hoyt, “Women, Men, and Leadership: Exploring the Gender Gap at the Top,” Social and Personality Psychology Compass, vol. 4, no. 7, pp. 484–498, Jul. 2010, doi: 10.1111/j.1751-9004.2010.00274.x.

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: cysy@bicol-u.edu.ph or layertech labs support at learning@layertechlab.com

Students Analyzing Procurement Data: 2019 Datathon for Transparency, Efficiency and Good Governance

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25 students from Bicol University College of Science – Computer Science and IT Department, and students from Southern Luzon Technological College Foundation, Inc., joined the two-day Datathon on September 4-5, 2019 at Bicol University College of Science Laboratory. The event is facilitated by Layertech Labs, with the help of Bicol University CS- CSIT and SLTCFI, supported by Hivos.

In 10 hours, students learned basics of the R Environment, Basic Data Scraping and Data Analytics techniques. The students were made to form teams of 3 or 4, with a procuring entity of their choice. Using R, the students were able to scrape official Philippine procurement data from Philippine Government E-Procurement System (PhilGEPS), clean and standardize the datasets, before visualizing them into graphs.

At the end of theDatathon, the teams presented their findings before a panel of judges from: Department of ICT Luzon Cluster 3, Bicol University CS-CSIT, SLTCFI, and Gayon Bicol Civil Society Organization.

The judges declared the final winner, team “Paste Copy”, for analyzing Department of Education Region 5’s procurement efficiency, focusing on procurement of school supplies in the region’s public schools.

Check out the VIDEO:

Layertech Leads Data Scraping Session using R and R Studio

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Supported by Hivos, Layertech lead a data scraping session using R and R Studio, using official Philippine Procurement Datasets found in Philgeps.gov.ph’s Open Data Portal.

The session attendees were faculty members of Bicol University College of Science IT Department, and faculty and graduating students of Southern Luzon Technological College Foundation, Inc.

While procurement datasets are available in open data formats, the large PhilGEPS datasets still need to be pre-processed, filtered, visualized and analyzed. Only then can researchers, advocates, and concerned citizens draw useful insights to aid them in their advocacy and decision making.

What’s the objective?

Layertech and partners advocate for #DataDrivenGovernance. We aim to encourage researchers to study and innovate on government procurement. For them to do that, they must be equipped with the necessary skills and tools to draw insights from procurement information that is available.

For this first session, the academe was specifically invited because the team also needs to get their insights, comments and suggestions about the training design, in order to improve the next tech training sessions to come.

The team and partners will soon be deploying training sessions for young researchers, students, innovators, and faculty, on various topics such as:

Data Science
Data Analytics
Data Visualization
Python Programming
Machine Learning
Cybersecurity
Data Privacy

What are the results?

For the first training session with R, the participants were able to publish a total of 13 datasets (downloadable HERE, in our Open Data Portal) under various categories such as Health, Local Government, and Education.

The participants also actively presented their outputs and how these cleaned datasets can help increase transparency and efficiency in public procurement in the Philippines.

Want to know more about HOW to filter Philgeps datasets? Here’s a quick, general guide HERE.

Keep on visiting our “References” section for more procurement and data scraping, visualization, and analytics guides!

First Stakeholder Meeting – Open Contracting Data Standards Stakeholder Meeting 2018

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Held at The Oriental Hotel on May 22, 2018, Layertech Software Labs and Hivos conducted the first stakeholder meeting to officially kickstart the Open Contracting and OCDex project in Legazpi city, Albay.

The objective of the meeting is to present the Open Contracting project objectives, proposed activities, and solicit stakeholder feedback and support in order to understand the current issues and difficulties they encounter in public procurement.

Furthermore, in order to create a user-friendly, functional, and relevant procurement portal, stakeholders need to be a constant part of the development process, making them co-creators of the OCDex portal.

Meeting attendees include civil society organizations, local businessmen, members of the academe, and representatives of the Local Government Unit (LGU) of Legazpi.

OCDex team presenting OCDS and potential benefits to stakeholders

The meeting aims to ensure that the OCDex portal, its features, and contents will benefit target stakeholders and assist them in their future procurement planning and decision making activities.