Notes on Open Data and Malaysian Data Efforts

robot presenting electricity bolt

Think about the wildest, most out there, statistic you can think of.

How many bright yellow coats are sold every year? Which place in the world issues the most number of parking tickets? How many plants and trees were cut in your neighborhood this year? What is the color most people associate with aliens?

Well, the government might not know all of these, but it does have a lot of data. When data is available to everyone, free to use, open for republishing for research purposes, it is known as open data (AKA open content, open education, open educational resources, open government, open knowledge, open access, open science, etc)

Serendipity works in mysterious ways. Here I was, in the summer of 2019, outlining my articles on Data Visualization and GIS in Digital Humanities. Right around the same time, there I was, in Google Malaysia Head Office, attending a Malaysia Open Data User Group event. Hack/Hackers is a Media Technology group made up of Data Journalists. People from various (private and government) slices of life were at the event to work out the specifics of government data usage.

MAMPU (Malaysian Administrative Modernisation and Management Planning Unit) was born of a need to modernize the government services. In an effort to become a data-driven government so to speak. Governments are traditionally cautious of releasing data. Figuring out data is a detective murder mystery in action. Also, interestingly enough, MAMPU is women-led! In the Google Malaysia quaint cafe co-working space, we sat watching these presentations.


  • Quality of data published
  • Data Granularity
  • Update the datasets
  • Bring about awareness that exists
  • Help developers in apps and software creation

MAMPU Aspirations

  • Accountability
  • Transparency

After a quick overview of MAMPU and related organizations, we divided into groups according to 8 areas of concern:

  1. National stats/census (including economic data)
  2. Transportation
  3. Healthcare
  4. Education
  5. Crime
  6. Budget/Public contract
  7. Environment/Map/Land Ownership
  8. Others (those who are interested in other aspects of open data like technicalities, policies etc. that are not specific to data cluster)

I jumped from National statistics to Education to Environment / Maps and finally Others to discuss a variety of topics. The event was very well-organized, and well-supplied. Considering how many people were involved, the number of attendees, the arrangements for a structured discussion was wonderfully done. Each group had a long table, whiteboard (we were in a Google office after all), sticky notes, and markers given out to and sped through the evaluations. With a common framework for coming up with questions and answers, each group dove right in.

Questions for the attendees

Surface-level questions

  1. What datasets do you want?
  2. What datasets can you contribute?

In-depth questions

  1. Identify high-impact data – datasets that are most useful to users/can produce the highest impacts (economic or social benefits).
  2. The effectiveness of the existing Open Data platform ( Recommendations to improve the platform as well as the open data ecosystem in general.
  3. How to enable long-term collaboration among MAMPU, data providers and data users?

How to contribute?

  • Identify high impact data
  • Effectiveness of datasets
  • Long term collaboration
  • Blocks as data
  • Non propitiatory
  • Contracts or Tenders
  • Joining different datasets for meaningful information
  • Have real human impact

What can MAMPU work on?

  • Open Data Ecosystem Journey (Portal)
  • Data Champions in government ministries.
  • Citizens can be Data users and providers.
  • Blogs on Digital KL Government.
  • Data was not machine readable. (PDF format)
    • Target: April 2016 (Convert to readable format in csv)
  • Distributed guideline for Data Sharing with 10 Principles
  • 8 Dimensions for Open Data Readiness
  • Clear Legal Policies
  • Graphs can be less wordy.
  • Apps like Moovit require real-time data.
    • Traffic Signals and Weather, along with taking into account Public Holidays data can help adjust traffic light configuration.
  • National and International Hackathon extended to Japan, South Korea, and rest of the APAC (Asia Pacific)
  • Standardized Structured Tagged Datasets
  • Ready-made utility
  • Digitally data-driven
  • Facilitation of Inter-agency sharing of data

TM One (See more in presentations slides)

  • Product Analysis
  • Data Structure Infrastructure
  • “Smart” City

Malaysian Global Information and Creativity Center (MaGIC) (See more in presentations slides)

  • Software for internal government agency
  • Catalyze innovation
  • Focus on education

Use cases

  • Good Services quality
  • Value for Money
  • Level playing field in various areas
  • Areas of focus such as Media, Academia, Journalism, etc.

My own contribution to the event? A plea to make art, historical, and cultural data available on the government portal. I would have loved to use this data in my research and study of Data Analysis and Viz, if only to connect with the place I called home for two years – Kuala Lumpur.

On speaking to dozen or so business people, educationists, law students, techies, data engineers, etc., I actually felt the awe of being a part of such an event. And then I had some excellent lunch, made away with an entire pizza, croissants, cheese blocks, etc and marched off to make jokes about how I searched for me and found myself in Google search engines.

girl in front of Google Malaysia office sign board
Jaj searches for herself.


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.