Cuebiq's Data for Good initiative is being continued with support from the Spectus.ai data cleanroom and their Social Impact professionals. Their commitment to positive social impact through the ethical and responsible use of location-based data makes further insights possible. We invite you to visit https://spectus.ai/social-impact/ for more on contributions to academia and research partners.

Providing social value through location data has been paramount to Cuebiq since day one. Through our Data for Good program, we provide access to anonymous, privacy-preserving location data for academic research and humanitarian initiatives related to human mobility. 

Keep reading for a look back at our Data for Good efforts from last year, what we’re currently working on, and what’s to come in our quest to provide social value through data.

Data for Good Initiatives of 2020 

Looking back, 2020 was a big year for Cuebiq’s Data for Good program — below are three of the major projects we focused on last year:

1. Partnership With Oxford University

Since the beginning of the pandemic, researchers at Oxford University have been using Cuebiq data — in combination with other data sources, such as the UK’s National Health Service data — in order to measure the effects of lockdowns and other COVID-19 restrictions on mobility. In addition to these metrics, the COVID-19 Impact Monitor also measures visitation to various points of interest, such as retail locations, grocery stores, and public-health facilities. Given the UK's multiple lockdowns over the past year, mobility data has proven to be a helpful proxy for understanding the effectiveness of such measures in restricting mobility and COVID-19 transmission.

2. Collaboration With the CDC

In the early days of COVID-19, Cuebiq began working with the CDC's Geospatial Research, Analysis & Services Program (GRASP) to provide real-time insights into mobility in the US. By using Cuebiq's aggregated and privacy-preserving Mobility Insights, the CDC is able to better understand trends in overall mobility, such as median distance traveled, sheltering in place, contact rates, and origin-destination travel, all at the county level. 

3. Hurricane Laura Evacuation Insights

Since 2017, Cuebiq has provided academic researchers with access to its mobility-data insights in order to measure evacuation patterns during natural disasters, such as hurricanes and wildfires. By generating more user-friendly data sets through our Mobility Insights dashboards, we have been able to develop easy-to-read dashboards that provide insight into metrics including evacuation rates, evacuee destination by county, and trends based on income. Our first dashboard provides insights on evacuation patterns during Hurricane Laura, which hit the Louisiana and Texas coast in late August 2020.

Joining the Trinity Challenge

More recently, Cuebiq has made strides in our Data for Good efforts by joining the Trinity Challenge.

The Trinity Challenge is a coalition of partners promoting the use of data and analytics to identify, generate, and reward insights that contribute to the goal of a world better prepared for health emergencies. Cuebiq became a member of the Trinity Challenge in January of 2021 and is partnering with other members to work on integrating geospatial data into decision-making during health emergencies.

Through the Trinity Challenge, we are able to learn from the expertise of other members across the realms of public health, big data, academia and more, while also supporting other members with access to our own COVID-19 Mobility Insights.

How Cuebiq Workbench Fuels Data for Good

Looking ahead, Cuebiq’s Data for Good efforts are set to make a major impact in 2021 and beyond, thanks in part to the launch of our new platform as a service, Cuebiq Workbench.

As Cuebiq continues to be a pioneer in privacy within the location-data space, it is critical to ensure that privacy-preservation techniques also preserve the utility of Cuebiq's data to solve some of the world's biggest challenges, such COVID-19 response, social equity, and the growing threat of natural disasters. With Workbench, Cuebiq is offering our Data-for-Good partners a responsible data-sharing platform that allows users to query our full data stack, while obtaining only highly aggregated and privacy-preserving outputs. This, in addition to our pre-built data sets and processing tools, all wrapped in a governance layer, empowers researchers and public-sector entities to benefit from big data while minimizing resource requirements and privacy risks. 

Check out our Data for Good page to learn more about the program.

The post Cuebiq’s Data for Good Program: Where We’ve Been and Where We’re Going appeared first on Cuebiq.

How has the lockdown in Italy due to COVID-19 been affecting the mobility of citizens? This is a challenging question to answer, but location data can provide some insight.

Cuebiq has partnered with ISI Foundation to assess the efficacy of the intense travel and mobility restrictions put in place in Italy to curb the spread of the novel coronavirus. This analysis focuses specifically on how mobility and contact patterns changed in Italy following lockdown, looking at anonymized and aggregated location data.

Led by ISI Foundation researcher Michele Tizzoni, with aggregated data coming from Cuebiq’s Data for Good Program, this preliminary research shows in near-real time the effects of public health policies in Italy in the first three weeks of intervention (February 18 — March 10). It does that by measuring changes in the traffic fluxes between provinces, in the average distance traveled by users, and in the spatial overlaps of groups of users in public places.

Using Location Data to Power Mobility Analysis

Employing de-identified, large-scale and aggregated data from Cuebiq, this analysis assesses the impact of mobility restrictions and social distancing in Italy. Through its Data for Good program, Cuebiq provides access to aggregated mobility data for academic research and humanitarian initiatives. This first-party data is collected from anonymized users who have opted in to provide access to their location data anonymously, through a GDPR-compliant framework.

To learn more about the data collection and sample for this analysis, be sure to check out the full research. 

View Research

Key Takeaways on Mobility in Italy

So, how has mobility in Italy changed due to increased regulations? The key results of this project can be summarized as follows:

• The initial mobility restrictions targeted at Lombardy, Veneto, and Emilia-Romagna have led to a reduction ranging between 10% and 30% of the traffic between Italian provinces during weeks 1 and 2.
• Following the national lockdown on March 9, the mobility fluxes between provinces have decreased by 50% or more, everywhere in the country.
• Following the national lockdown, the number of users who did not leave their home province after March 9 has increased by an average of 50% at the national level and more than 100% in the provinces of Lodi, Piacenza, Fermo, and Vercelli, with respect to the pre-outbreak period.
• The characteristic distance traveled by users considerably reduced over the 3 weeks of restrictions. Indeed, the average radius of gyration of the users distributed all over Italy and present during all the weeks of the study has declined by 49% over the 3 weeks of outbreak going from 13 km to about 7 km on average.
• The restrictions in mobility, closure of public spaces, and the enhancement of smart/remote working led to an average reduction of potential encounters of 8% during week 2 and almost 19% during week 3.

These results can be helpful to modelers and policymakers worldwide, especially now that travel and social restrictions are becoming more and more common on a global level. For more detail, be sure to check out the complete report, which is updated daily as new data becomes available.

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Cuebiq's Data for Good initiative is being continued with support from the Spectus.ai data cleanroom and their Social Impact professionals. Their commitment to positive social impact through the ethical and responsible use of location-based data makes further insights possible. We invite you to visit https://spectus.ai/social-impact/ for more on contributions to academia and research partners.

We had the pleasure of sitting down with Brennan Lake, Cuebiq’s Senior Director of Research Partnerships and Data, to ask him a few questions about Cuebiq’s Data for Good program. Read on to learn about some exciting new Data for Good initiatives he’s working on, as well as how he interfaces with Cuebiq’s Data Science and Engineering teams to effect positive social change.

Can you tell us about your background and how you came to work at Cuebiq?

My background has traditionally been in international relations and international development. I also worked abroad in tech — I went to Argentina and co-founded an e-commerce software-as-a-service startup, which introduced me to the world of tech and SaaS platforms. After that, I moved back to Boston to run an international development NGO, as social-impact oriented work has always been a passion of mine. I worked there and grew that NGO for five years, and then started looking for a new challenge to give me the opportunity to merge my backgrounds at the intersection of tech and social impact work. 

In my work at the NGO, we were constantly being told to be more data-driven; but in developing countries, a lot of data collection consists of paper-based surveys in communities that are hard to reach. So, I  was really interested in the power of big data and location data to answer sociological questions in these areas at a greater scale. I was also really drawn to the fact that at such an early stage of the company, Cuebiq was already thinking about giving back and creating social value from its data assets.

What is Cuebiq’s Data for Good initiative and how does it work?

Data for Good is our program through which we seek to improve lives through the novel use of location data. We do that in order to provide benefits to the millions of anonymous users who are sharing their location data with us every day. Specifically, we pursue and achieve that mission by supporting academic research and humanitarian initiatives related to mobility. We work with academia and researchers — for example, we’ve done work with MIT Media Lab looking at the impact of economic segregation on the development of urban neighborhoods. We also work with University of Washington and other universities to understand evacuation patterns before, during, and after natural disasters.

Together, we develop research projects where we think our data can make an impact. We seek out projects where the results are actually going to create positive social impact and inform policy. 

What is a Data for Good initiative you’ve worked on that’s been particularly rewarding?

We’ve done a lot of work in disaster response in the past. Through working with academia, we’ve used our data to map evacuation patterns and forecast behaviors for future natural disasters. But now we’re starting to build our capabilities in house to process information on evacuations closer to real time, so that we can provide emergency managers and first responders with insights to help them gain mission-critical awareness on the ground. We’re really excited to be building this out with our Data Science and Engineering teams.

Can you tell us about Cuebiq’s partnership with Politecnico di Milano?

Our relationship with Politecnico di Milano developed organically, since a lot of our data scientists and management team came from Politecnico. As a result of this, researchers at the university were able to see what their alumni were graduating to go off and build using Cuebiq data, and recognized the potential value for different research around the world.

In one such project, Cuebiq is collaborating with Politecnico di Milano to assess “transport poverty” in Maputo, using high-precision location data, with the goal of creating more accessible and inclusive transportation systems in Mozambique. This collaboration is part of the Safari Njema project, funded by the Polisocial Award 2018 by Politecnico di Milano.

How do you interface with Data Science and Engineering to make Data for Good a reality? 

Data for Good would not be possible without our amazing Data Science and Engineering teams. Specifically, we see in them a really strong ethical imperative and enthusiasm for participating in Data for Good projects, whether it be creating new data sets for specific use cases like mapping evacuations, or figuring out how we can better deliver data for population-sparse areas of the world. These teams are always really proactive about problem-solving, to make sure our partners have the data they need to do research that will deliver a high impact downstream.

Our Data Science and Engineering teams are also developing cutting-edge techniques related to differential privacy in order to better prevent misuse while preserving the data's utility for aggregate analyses of human mobility.

What has been the most challenging part of building out Cuebiq’s Data for Good program?

We’re a fast-growing startup, so making sure we have the human resources to work on Data for Good initiatives could potentially be a problem. However, we’ve been lucky to have a very dedicated team supporting Data for Good, not only in Data Science and Engineering, but across the board, from the executive team throughout the entire organization. This will only improve as we expand our technical human resources — we’re always looking for new Data Science and Engineering talent who are interested in contributing to these initiatives.

What do you see as the future of Cuebiq’s Data for Good program? How do you anticipate it will grow or change?

I would say I think that Data for Good is most successful when we’re bringing diverse groups of stakeholders to the table, not only on the researcher or Data Science side, but also on the practitioner side. That’s why we’re excited to be working with partners like the World Bank and UNICEF — it takes the work we’ve been doing on the research side and puts it into practice, to help inform policy-making. At the end of the day, the data is most powerful when it’s put in the hands of people on the front lines of these issues.

Interested in working at Cuebiq? If so, be sure to check out our careers page for new job openings.

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