1.
What is Project MaPPPing
SDP
is constituted of students who have great interest in sustainable development,
and we refer to the SDG goals articulated by the UN as the global standard for
sustainable development. This year, we have specifically focused on goal number
9 and 11 that emphasizes the role of infrastructure in sustainable development [1]. We believe that
sustainable and resilient infrastructure is at the heart of sustainable growth,
so we have launched a project called Project MaPPPing in December 2019.
There are three phases to Project MaPPPing and
we have been working on one phase at a time. During the winter of 2019-2020,
SDP launched the project with Phase 1, and we have continued on with Phase 2
since the Spring semester of 2020. Both phases have been carried out as a
collaboration with the World Bank Group PPI team. Working as a data reviewer
and analyst supporting the World Bank Group, we have been updating data on PPI
projects in middle- and low-income countries. Also, since the outbreak of
COVID-19, we have been collecting data on infrastructure projects that have
been disrupted by the pandemic.
The cooperation between SDP’s research team and tech team is a distinctive
feature of Project MaPPPing since we aim not just to create a database on PPI
projects, but also to create an AI tool that can automatically assess the
status of PPI deals by looking at news articles.
2. The Role of Research Team
The phase 2 can be separated into two parts:
status tracking of PPI projects and tracking the delayed/canceled deals of PPI
projects due to COVID-19. For better understanding, the role of research team
will be described based on the latter since most of it overlaps between two
parts.
At the initial stage of the project, research
team and tech team gathered around to set the deadline and overall timeline. Given
that the objective was collecting failed PPI deals in developing countries,
each team specified their own schedule based on their work.
The main role of research team changed as the
project proceeded. At the beginning, what we had done was preparing data to
train the AI. With the aim to create AI tool to sort out the delayed/canceled
deals due to COVID 19, we first arranged the keywords for crawling. The next
process was giving weights to them respectively so that we could verify the
necessary keywords. We also provided answer sheet for AI training by searching
and accumulating some amount of urls with articles we are looking for. After
receiving the first version of AI tool, the next work we’ve done was enhancing
capacity. We classified frequently appearing websites but with meaningless
contents to eliminate from the tool and also categorized keywords for minus
weights.
The creation of relatively accurate AI tool,
called as SDP tool, could be the point where the role of research team took a
new turn. Our role was more of a research analyst. After studying the World
Bank PPI Methodology, we reviewed the data in the tool and sorted out useful
PPI deals to send it to the World Bank Group. This process continues until now,
where phase 3 has been started, to keep updating and accumulating data.
3. The Learning Process
The process is not easy and there are
hardships to doing this project. Mainly, we struggle finding relevant data on
open source. This is especially true when we are searching for the current
status of specific projects in specific countries. For example, we would search
for the current status of a 400 MW LNG power plant in Thaketa, Myanmar, typing
in keywords like the project name and the type of PPI in the search engines.
Often, we come across search results that are irrelevant or there is just no
data on that specific project. Sometimes, even if we did find articles with
relevant information, we would not be able to fully access the site without
subscribing and or paying.
Through this process we are continuously
trained to be a good researcher. In order to find relevant information, we try
out different combinations of keywords that gets us to the best possible search
results. For example, we would type in the place name (city) with the
infrastructure type (hydropower plant) instead of just putting in the project
name. Also, we have found that typing in keywords in that country’s language
rather than in English often gets us to more relevant information. In that
case, we would utilize Google Translate to read articles written in different
languages and try to get information on the project status.
What maximizes our learning process is the
exchange of thoughts within the research team. During regular sessions, we
share our experiences and insights that we obtained from researching. If
someone found an effective combination of keywords, they would share it with
the rest of the team. If someone had trouble researching specific projects,
other teammates would suggest different ways of doing the research. If someone
was unsure whether a project should be classified as operating or delayed,
other teammates would look into the article together to determine its status.
Likewise, the research team relies on each other and collaborates to solve
problems and build skills.
In addition, while doing research for Project
MaPPPing, we naturally become informed about recent developments in the field.
This helps us improve our understanding of the general trend of infrastructure
development in the developing countries along with specific details on certain
projects. For example, as we are researching infrastructure projects that have
been disrupted by COVID-19, we are aware of the various reasons ranging from
the lack of workers and or supplies to the decrease in demand for electricity
that deter the development of certain projects in certain regions. Having a
broad knowledge on recent developments is important and helpful for us to grasp
the dynamics of sustainable growth in real life.
4. Project MaPPPing Phase 3
Project MaPPPing, which started in the end of 2019,
has entered its final phase on September, 2020 along with the recruitment of the 6th
members of SDP. With more people engaging in the project, the contents have been
enriched and the process is speeding up to show its final work at the end of
2020.
The phase 3 has the title of “Visualization of
the DB” and the visualization will take the form of failure map. It shows
delayed or canceled hard infrastructure PPP (public private partnership) deals on
the map so that various stakeholders can self-access to intuitive information on
PPP infrastructure. PPP is considered as the most effective method of implementing
and the key of sustainable development of infrastructure. Countries suffering from
financial shortage, mostly developing countries, can partner up with corporates
to distribute the financial burden of building power plants, dams, or roads
essential for country development. Also, as the government can easily regulate
PPP based infrastructures, those facilities can reinforce public purposes
rather than solely pursing financial benefit. Through the steady and long
process of phase 2, SDP’s own database on infrastructure has been enriched, prepared
to be illustrated on the map. Among these data, the map utilizes PPP infrastructure
deals worldwide, both developed and developing countries and further explains the
specific reasons of failure. It provides filter service which the users can use
and draw their own insights.
SDP believes the visualization of failure map
to be a meaningful attempt, since, at the macro level, it is necessary work to
contribute to sustainable development. As mentioned above, sustainable
development builds on the presence and resilience of infrastructure. By
arranging the causes of failure, the future stakeholders can harness the data
and suggest their own solutions to prevent themselves from following the same
failure path. The accumulated data will eventually give deeper understandings
and lessons to infrastructure sector which will be the key to its resilience
and improvement. SDP is delightful to mark the major milestone in this process and
will continue to strive to seek the ultimate means for sustainable
development.
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