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    Behind IDETECT Challenge: Detecting incidents of displacement through machine learning and natural language processing Posted By Taija Sironen at 05/31/2017 11:03 PM BST

    The head of IDMC Data & Analysis department, Justin Ginnetti, shares his initial reflections and takeaways on the IDETECT challenge which ended in April. IDETECT enabled IDMC to leverage the efforts of brilliant, talented data scientists from around the world. Also, it called attention to the issue of internal displacement and introduced our work to a community that we had not previously engaged with.

    Girls attend class in a classroom at a school in Khost Province, Pakistan.

    Photo: Andrew Quilty / Oculi for Norwegian Refugee Council

    One afternoon in November 2016, Leonardo Milano and I sat down to map out a plan to develop a semi-automated tool to detect incidents of internal displacement through the analysis of “Big Data” researched online. The tool would sift through databases like GDELT, which contain most of the news published around the world in nearly every language, and find and extract information and data on internal displacement – in near real time. We left the meeting with a solid plan outlining a process to develop a viable working tool ready for implementation by late 2018 or early 2019. 

    Despite this, we didn’t go home satisfied that night. There were a couple of reasons for this. First, we both knew how important it is to IDMC to be able to identify new incidents of displacement: if we don’t know when internal displacement started, we cannot indicate its duration; if we cannot accurately measure new displacement flows it is that much more difficult to develop quantitative empirical evidence about the factors that drive new displacement. In short, IDMC estimates of the number of new displacements are often overshadowed by our global IDP headcount, and this is wrong.

    The availability of quantitative empirical evidence on incidents of new, repeated and secondary displacement is critical for those working on disaster risk reduction, climate change adaptation and development, because it explains what factors need to be addressed – by whom and when – in order to reduce the risk of future displacement. This evidence is also important for humanitarian actors because it can help with disaster preparedness (e.g. knowing how many people have just become displaced or who are likely to continue across borders) and response (e.g. building resilience to future shocks).

    However, our plan was going to take too long to implement: evidence about the drivers of new, secondary and repeated displacement is needed now, and its absence is felt across many global and regional policy fora. Addressing the risk of new displacement caused by climate change is part of the Paris Agreement on climate change; it is also needed to determine the factors that explain when and why some IDPs are forced to flee onward across international borders, and in order to begin to understand how many people are in situations of long-term, protracted displacement.

     A new way of working

    The second reason we went home dissatisfied that night was because we considered our plan to be a bit old fashioned, considering that we were trying to apply a new technology to internal displacement. The following morning, I suggested to Leonardo that for this project we try a new way of working rather than implement the plan with IDMC staff, consultants and interns. The idea was to crowdsource not just the solution but the way to develop it. By lunchtime, Leonardo had discovered the UN’s Unite Ideas platform for crowdsourcing data analysis and visualisation tools. Ten minutes later, I’d written to Unite Ideas, and by the time we went home we’d already received a positive response and an invitation to a conference call.

    Unite Ideas represents the UN at its best. It’s a vehicle for enlisting talented individuals to develop innovative solutions that help solve global problems. The genius of this platform derives from its ability to harness talent and cutting edge techniques and to organise them around a specific and clearly articulated ‘challenge’. Unite Ideas is a newly conceived UN for the 21st century: agile, democratic − a way to merge top-down and bottom-up approaches at lightning speed.

    Proof: within a week, Unite Ideas had green-lighted the idea for our #IDETECT challenge to detect, tag and cluster reports of incidents of displacement and to extract critical information from the source documents, such as the number of people displaced and their location. By the end of January, we’d launched the challenge. I write this in May, having begun to review the first batch of submissions received.

    Initial reflections and takeaways

    Not only have we progressed much faster than originally planned in the development of a tool to detect new displacement, but by working in this manner we have also benefitted in several other ways.

    First, we’ve met and engaged with more than 100 talented data scientists, many of whom had not worked on the issue of internal displacement before. Some weren’t aware of this issue, while others were but didn’t know how or with whom to engage. One team competing in the challenge, Data for Democracy, even organised well-publicised hackathons to help build the code for their solution. The discussions we’ve had and the people we’ve met since November are just the start of what we hope will become several lasting partnerships and collaborations with these new colleagues.

    Second, partnering with Unite Ideas meant crowdsourcing both the solution and the way to develop it. Although we had our own ideas about how to produce the tool, it was up to the Unite Ideas participants to come up with their solution. Thus, instead of having a single possible solution developed one way, we’d receive several working submissions, each potentially unique. Working in this manner meant trusting the crowdsourcing approach, relinquishing a degree of control, and coming out of our comfort zone. In our case, that small leap of faith has been rewarded.  

    The #IDETECT challenge with Unite Ideas has been a big learning experience, both for IDMC and others involved. This learning has taken many forms, but one of the most important lessons is that while IDMC remains part of a large humanitarian NGO – the Norwegian Refugee Council – it can also operate like a small start-up in Kampala, Jakarta, Bangalore, Silicon Valley or elsewhere. 

    What’s next?

    At this point, we would like to sincerely thank everyone who has submitted an entry or contributed to one by working as part of a larger team. In June, IDMC and the rest of the judging panel will select and announce the winner of the challenge. We’ll post a follow-up blog by the challenge winner in which they describe their tool and how IDMC will be able to use it. We’re also planning to organise an event where the winning entry will be presented and demonstrated.

    As excited as we are to have come this far this fast, we’re not done yet. So stay tuned. 

    This blog was originally posted on the IDMC's Blog

    Visualizing a solution for the UNGAviz challenge by Abdulqadir Rashik Posted By Taija Sironen at 06/01/2017 10:49 AM BST

    The United Nations and its member organizations produce a large amount of data on a regular basis.

    While this may be challenging for diplomats and UN employees to sift through, it provides data researchers with a vast number of easily available data sets for analysis.

    The United Nations Office of Information and Communications Technology periodically launches challenges as part of its Unite Ideas initiative to crowdsource solutions from data researchers and the general public. My solution - “Global Policy”, was awarded the first prize for one such recent challenge named UNGAViz.

    The UN General Assembly has passed thousands of resolutions on a range of different issues.

    While most resolutions are passed unanimously without a vote, several others require a vote to be cast by the member states before being adopted. The UNGAViz challenge involved analysing and visualising the several different resolutions passed by the general assembly, in a manner which would simplify analysis of this huge data set by ordinary citizens as well as diplomats.


    In any data analysis solution, the main challenge is to structure the data so that it is effective in informing users in making appropriate choices.

    Too much complexity in terms of choices offered to the user, or in representation of data, is more likely to confuse the user than to help. On the other hand, simplifying the interface too much could mean that important information never reaches the user.

    The challenge requirements made it clear that the solution should be useful to diplomats as well as the general public. This pretty much includes everybody.

    With such a wide spectrum of potential users, balancing simplicity with presentation of detailed information becomes even more important.

    The interface needed to be simple enough to be used by people who weren’t particularly acquainted with the terminology and procedural details familiar to UN personnel.

    At the same time, it would need to retain enough analysis and details so as to be useful to diplomats in their decision making process and to provide researchers a deep understanding of their chosen topic.


    The solution starts off by asking the user for one single input - The topic that they would like to research.
    This serves two important purposes.

    Firstly, it ensures that the user is not burdened with too much complexity in terms of configurable values and selection of settings which would only serve to turn away casual users who wish to gain a broad overview of discussions by the UN General Assembly.

    And secondly, it sets the focus of subsequent information presented by making it clear that all further interactions with the tool are centered around the topic entered by the user.

    The tool provides a standard experience to all users, ranging from a casual user wishing to research “Weapons in Space” to diplomats making important policy decisions.

    At each stage of analysis, more details are progressively provided to users to enable in-depth research.

    After accepting the topic the analysis focuses on three distinct but interrelated viewpoints.

    1. Broad Overview

    The visualization begins with a broad overview of the resolutions found

    The aim is to provide a casual user with insight into the following key data points:

      1. Interest in the topic over time and a listing of the resolutions passed - These are useful indicators of the importance that the topic has been given at the UN, and the time periods when the topic was most in discussion.
      2. Voting patterns for voted resolutions - so as to differentiate the more contentious resolutions from the widely supported ones.

    2. Country Analysis

    Country specific analysis helps diplomats analyze the behavior of any country and identifies other countries with similar or opposed voting patterns. Users can select any country including former states that no longer exist, and analyze their behavior in greater detail.

    Every resolution in the list is overlayed to visually show the vote cast by the selected country for that resolution. Analysis of the past voting record of a country can be a useful indicator of its stance towards future resolutions.

    More importantly, the votes cast by the country are analyzed against those cast by every other country to get a list of supporting and opposed countries.

    This should help diplomats quickly identify the groups of countries sharing a similar stance on any given topic.

    3. Individual Resolution Analysis

    Lastly, the resolution specific view allows the user to select any individual resolution for more detailed analysis

    Detailed information regarding voting patterns is displayed visually on a map as well as in tabulated form.

    A link to the full resolution text is also provided so that the user can get individual details which were not available in the visualization itself.


    Design is one of the most crucial aspects towards making any visualization successful in effectively representing its underlying information.

    Instead of using numbers and text to show each piece of information, the solution uses a more visual form to represent parts of the data during analysis.

    Among other visual indicators, resolutions are overlayed with colored blocks to show voting counts and a map shows voting patterns as well country locations.

    While visual appeal is one factor of a successful design, another equally important factor is the ease by which a user can access relevant information.

    To allow users to easily access any particular aspect of analysis, the solution attempts to ensure that in most cases, switching the focus of analysis is only a single click away. So the user can quickly switch from the broad overview, to analysing a particular country, to analysis of a particular resolution and back, with a minimal number of clicks.

    Final thoughts

    Challenges such as this provide a unique opportunity to improve one’s own abilities while at the same time producing something which could have a positive impact. I hope that the solution proves useful to the general public as well as diplomats to extract meaningful information from the vast amount of data present in the resolutions and their voting patterns.

    You can view the solution at

    If you have any thoughts on how the solution could have been made better, or would generally like to discuss something, feel free to contact me at

    Welcome to the new Unite Ideas platform Posted By Taija Sironen at 06/21/2017 11:03 PM BST

    Unite Ideas team is excited to announce a new and improved platform that will harness the sum total of good programming knowledge globally to create something more relevant than any individual could do working alone.  Unite ideas is a platform for collaboration between the United Nations, academia, civil society, and partner organizations. It is a place to exchange ideas, learn from one another, and help others by taking on data science challenges and with our new platform we will be able to collaborate better than ever.  The new Unite Ideas platform allows us to not only collaborate on solutions, but also allows commenting and voting on winning solutions.  The solutions to these challenges contribute to better understanding of more than 60 years of political and socio-economic history of the world in meaningful ways.

    The United Nations produces a vast amount of information, covering a wide range of subjects in at least 6 official languages, and formats e.g. documents, datasets, and multimedia. Increasingly, this information is being made available to the public as “open data”.  Not only will the new platform use UN data, but partners we collaborate with on challenges will be using their data sets and making them available for the crowdsource community.  Unite Ideas is an avenue for the public to discover these datasets so they can be used and explored to support international peace and security, sustainable development, human rights, international law, and humanitarian aid.

    At Unite Ideas we have already completed 8 successful challenges which can be viewed on the ‘Past Challenges’ page where you can also access open source code of the solutions to these previously completed challenges. As we disseminate data science, visualization and larger crowdsourcing technology worldwide, we cultivate the depth of expertise in this field to find creative solutions to global challenges. This expertise can be re-used by governments and civil society to tackle similar problems in their respective countries.

    Join us to collaborate for the global good!


    Unite Ideas team

    United Nations Office of Information and Communications Technology