Factly Data Devthon

  • About the event
  • Outcomes
  • Media Coverage
  • Participating Organisations
  • Opportunities and Challenges

Introduction to the Event

The Prototyping Stage of the Public Data Devthon was conducted at T-Hub on the 7th and 8th of May. The event was supported by the Government of Telangana and T-Hub. Rakesh Kumar Dubbudu, founder of FACTLY and Co-convenor of NCPRI was the curator for this edition of Devthon. The focus for this event was exploring the possibilities of Public Data.

Many of the participants were attending the Devthon for the first time. After a long wait, the event was finally about to start. By 10 AM, the hall was full of participants eager to learn and explore the possibilities of Open Public Data. At 10 AM, Rakesh started by welcoming everyone present to the Public Data Devthon. He continued to explain about the scope of Open Data in India. Harish Krishnan, founder of Devthon took a few minutes to explain about the goals of Devthon and how this event came to be. This event was conducted jointly by FACTLY/Devthon with support from Manoj and Uday from FACTLY and Abraham from Devthon. Then came the time to discuss about the datasets that were going to be used. Rakesh helped the audience understand the five datasets that were being used:

GHMC data: Based on grievance data from GHMC for the last one year (Apr 2015 to March 2016), can we find out the most common grievances, officials who are loaded with work, areas from where maximum grievances are coming from etc.

Village Dashboard based on Maa Bhoomi Portal: Based on the Village level Pahani on the Maa Bhoomi portal, can we build a dashboard for micro level planning at a village level on land holding size, type of land. water sources etc

NITI Aayog district data: Based on district data from NITI Aayog, can we build a dash board for comparing districts on various parameters and find sister districts?

MNREGA Data: Based on the MNREGA works done in a district since the inception of the scheme, can we find outliers in terms of wage/material expenditure, works done etc?

PDS data: Based on closing balance reports and key register reports of FPS, can we throw light on the FPS that may be diverting food grain meant for the poor.

Brainstorming & Team Formation

At 11 AM, all the participants were given the choice to join any of the 5 groups which were using the 5 different datasets. There was a round of introductions where each one of the team members shared their name, experience and skill sets. After that it was jumping into the datasets that were on offer. The basic ideas that each one of them had in mind were discussed.

But the interesting part was the unique perspectives each team member had to offer. There were programmers, UX designers, database developers, journalists, activists and data enthusiasts that had come together to create a diverse team. A participant Sanjay Y shared, “ I was able to meet people from divergent backgrounds and exchange ideas.”

After 2 hours of brainstorming of different ideas that could be pursued, all teams took a break where the discussions continued over lunch. When they came back at 2 PM, the prototyping started in some teams while others were still finalizing their ideas. In each team, one or two team members focused on cleaning the data and ensuring that they were uniform in structure. Rakesh and Srinivas moved from one team to the other and checked the progress while offering their feedback.

The Prototyping Stage

After two hours of sketching and tinkering, the teams reached their first checkpoint. They had to share the developments that had happened and could ask for feedback from other teams. The experts at the venue chipped in with inputs to help the teams get better clarity of their goals. The representatives from each team stepped forward to explain the prototypes that they were building. There was excitement in the room as the participants listened to what the other teams were up to and looked at ideas that they could incorporate into their own prototypes.

As the checkpoint ended, the team members huddled together to discuss what changes they wanted to make to their prototype. Also, the responsibilities were divided equally among the team members. Each one started working on the part they were assigned and constantly consulted their team members for feedback. Two hours flew by and everyone was happy with the work that they were able to do in a single day.

Day 1 ended with the teams being more than half way in completing their prototypes. A participant Vishal Pallerla said, “This is a good initiation by Devthon team to let the government know the outstanding possibilities that we have with the existing data to make decisions that can help government reduce the wastage of resources.”

Day 2 started at 10 AM with teams working on their presentations that they would be using to explain their prototypes. The work on the prototypes was also going in full swing. There was a checkpoint# 2 at 1 PM where the teams again shared their progress and took a final round of feedback. After lunch, the teams spent a good two hours in refining their work and getting it ready for presentation.

Presentation Practice

At 3 PM, all the teams were ready for the presentation practice. They came forward to explain the goals that they were trying to achieve with their respective prototypes and the users it will benefit. They also elaborated on the need for this product and the impact it will be having. The experts at the venue suggested some changes and corrections that were carefully noted by the team members. They just had 2 hours to make the final changes before they were ready for the final presentation before the IT Secretary, Governement of Telangana, Mr. Jayesh Ranjan.

At 5 PM, the stage was set for the outcomes of the event to presented. The chief guest, Mr. Jayesh Ranjan reached the venue. A short video was played to showcase the problem statements that were being tackled at this event.

Village Dashboard with data on Maa Bhoomi Portal

 

The first team to present was the team that were using the data from the Village Pahani records. They created a dashboard that could show, compare and calculate the data from the Village Pahani records. It could calculate the average land holding per person in a village, highest/lowest land holdings, type of land, water resource and barren/cultivable land in a village. This dashboard could be used by the common man and also an official like the district collector to measure the rural development metrics and find insights.

 

 

 

GHMC Grievance Dataset Analysis

 

The team worked to visualize the complaints that the GHMC has received in the last year. It could show which were the areas that registered the most number of complaints and also the types of works that were requested the most number of times.

They were also able to build a demo for an App that would be able to visualize the status of complaints in a particular region. This would be a handy tool for all decision makers who were part of the GHMC. They could easily monitor if the efforts they were putting in were showing positive results and make changes accordingly.

 

 

 

PDS Dataset Analysis

 

The main problem that the team focused on was the identification of leakages in the Public Distribution System. For achieving this goal, they created visualizations that showed the deviations in the behaviour of ration shop owners who showed huge variations of leftover food grains in the shop across months. By using this visualization, the supply variations across shops can easily be spotted. Also, the correlation between Supply and Number of Ration Food Cards can be seen. This can be used by officials to find fraudulent practices and investigate these shops wherever required.

 

District Dashboard using NITI Aayog Data

This team presented their visualization that they had created to analyze District Level Quality of Life Data. They created visualizations to compare districts on key sectors of development like health, education, water and electricity. Combining this information, they wished to rank different districts on the quality of life. These visualizations could be useful to NGOs, activists, district and state administration to find the deficiencies in key development areas and work towards filling the necessary gaps.

 

 

 

MNREGA Dataset Analysis

Team NREGA had two prototypes to showcase. The first one was a decision tree that would be used to understand if all the criteria were being met and thereby understanding whether the final goals of the NREGA scheme were being achieved. So all the data would be checked using the 4 rules that were part of the decision tree and easily be able to analyze if the scheme was being effective or not.

 

Also the team created a visualization to show the comparison between wages and materials. With the help of the visualization, they were able to clearly show the number of villages that showed a deviation from the average. They were able to find more than 300 villages that had spent more on the materials than the wages, thereby defeating the whole purpose of the scheme. These visualizations could be used to analyze the way villages were using their NREGA funds and easily spot the places where they were being misused.

 

Factly

Factly strives to cultivate civic participation and engaging citizens in accessing, understanding and using high value government records at the centre, state and local body levels.

 

 

Overview

Open data is contributing significantly to promote transparency in governance. It is also supposed to make public more aware of what the government is doing. This awareness, will in turn empower people to advocate/suggest/highlight ways to improve governance. Unfortunately, Government/Public data is complicated and very difficult to understand for most people. It is both difficult to access and difficult to make sense of. Factly is an initiative to make public data more meaningful to the common man.

Public data is also used to a large extent by journalists, NGOs, activists, designers, researchers and those within the government to promote transparency and accountability. It also enables improving policies and spins off new projects in governance, industries and organizations.
We wish to bring together public data experts, data enthusiasts, developers, researchers, engineers, designers and startups in a journey to discover challenges and opportunities in public and government data

Areas of Focus

Data Analysis
Data Visualization
Interaction Design
Mass Communication

Opportunities and Challenges

  • Analyzing the GHMC budget data to look at cost of different works for the city.
  • co-relate MMTS + TSRTC timetables to plan multi-modal timetables for city trips
  • Look at parking violations in the city to identify most offence spots and suggest parking spots for GHMC to reduce violations
  • Predict Water levels in reservoirs of Hyderabad based on rainfall predictions.
  • Build a map based tool to geotag buildings with the necessary building occupancy certificates, sewage connection certificate, electricity meter number and all associated data to look for fraud/violations.
  • Identify number of illegal buildings in the city using LANDSAT satellite imagery or number of buildings from openstreetmap co-relating with property tax data.
  • Look into outliers in water bills data to identify fraud by tampering with water meters.
  • Identify performance of govt schools in comparison to private schools in Hyderabad using schoolreports.in data
  • Look into anomalies of garbage collection using GPS data from garbage trucks.
  • Analyze crime patterns in the city and classify neighbourhoods based on the patterns.
  • Rank wards in the city based on access to public amenities like parks, bus routes, police stations, fire stations, roads, population, schools

Please find our other opportunities here