Unfolded offers open source geospatial libraries and a flexible suite of advanced tooling — including its signature product, Unfolded Studio, a self-serve platform that allows you to transform geospatial data into insightful maps within minutes. Its expert team of co-founders has architected many of the leading open-source innovations in the world of geolocation, including Kepler.gl, deck.gl, and H3. Recently, Unfolded.ai was acquired by Foursquare, a location technology company.
In an interview with Geospatial World, Sina Kashuk, Co-founder and CEO of Unfolded.ai, shares the emerging trends in geospatial analytics and expresses his expectations from the company’s acquisition with Foursquare. He says, “Bringing together Unfolded’s powerful geospatial technology and Foursquare’s comprehensive location data is a perfect mix for success.”
How is Foursquare’s acquisition of Unfolded benefit for you and your customers?
In partnering with Foursquare, we can fuel our technology with some of the most comprehensive location and global Point of Interest (POI) data available in the world. Having access to this immense trove of location data will allow us to elevate the capabilities of the Unfolded platform and develop entirely new features and tools for our customers, which in turn will help enhance their workflows. Our customers will also easily access Foursquare’s data directly from our platform, improving their analytics capabilities and adding more insights for their businesses.
Also Read: How geospatial intelligence powers Big Data analysis
Which sectors do you currently cater to, and which new areas are you eyeing now that Unfolded is acquired by Foursquare?
Unfolded’s founders all stem from Uber and thus have vast insight into the mobility sector — so this has been one of our core targets. In addition to continuing this focus, we now have our sights on Foursquare’s key customer segments, including retail, QSR, and real estate. But, with our combined technology and data and the growing use of POI and visit patterns across numerous industries, the possibilities are endless.
How is Unfolded different from other geospatial analytics platforms?
Hexagonal grid system at our core:
Our platform has been developed from the ground up for seamless geospatial unification — across the full spectrum of tabular datasets (such as point geometries, polygon geometries, and implicit boundaries) as well as raster-based data sources. Our core mechanism for unification builds on the capabilities of the H3 hexagonal grid system. Since Unfolded’s inception, we have been working on unifying data dynamically in one’s browser whenever dataset sizes are small enough or in the cloud when required. This will allow users to open geospatial datasets easily and effortlessly join them to start looking for patterns, correlations, and insights without worrying about where data is from or how it is formatted.
Temporal analysis:
Also unique to the Unfolded platform is its strong support of temporal analysis. With Unfolded, users can process, visualize and analyze datasets and describe changes over time. Traditional GIS tools were designed for large, predominantly static datasets. For decades, such tools served GIS departments well. But today, the large geospatial datasets that are being analyzed by data science departments often have time components and data representing movement.
For such datasets, being able to quickly visualize and analyze this time dimension is critical to making the right insights. Analyzing and visualizing factors like speed and congestion require tools that can handle the time dimension and display and animate datasets — even those that are the huge ones. Unfolded Studio has the capability to do just this — process and animate time related data on a large scale.
Also Read: Why is Python a perfect choice for Big Data?
Can you share with us a few emerging trends in geospatial analytics?
People are using or looking at temporal components and how things are changing over time in a specific location. Behaviors and movement patterns are changing faster, so there is a constant need to make better decisions in a quicker time frame. The demand to do so faster and faster is growing as well. Thus real-time access to this type of data is necessary. Analyzing these changes over shorter periods quickly is key to gaining quick insights and more informed decision-making.
Accessibility to satellite imagery dataset — It’s much easier to access massive satellite imagery data today than ten years ago. Therefore, it’s become more democratized — and is not only used across government and scientific communities but various businesses too. With this, there are now numerous data marketplaces; however, people are looking for more curated data rather than raw data, especially when it comes to geospatial. You’ll see more and more curators on the scene to try and serve this need.
How can businesses best manage Big Data in addressing the privacy and security of customer information?
Geospatial data has become central to more than just the scientific community and governments. More and more businesses are recognizing the importance and great potential that analytics of such data possesses. But there has been resistance to fully embrace geodata sharing because of concerns about data confidentiality and how to protect individuals against unlawful and unauthorized use of their data.
While some of these concerns can be addressed by taking cautionary guidance such as encrypting sensitive files, managing data acquisition, and access, and securely disposing of data, geospatial data allows for other ways to get valuable insights from data without invading an individual’s privacy.
For example, there are many methods for encrypting and creating geospatial data.
Unfolded’s H3 technology not only allows for aggregation but lets you move an individual’s location to a grid center, taking away the exact location and using proximity instead. It also uses the hierarchical nature of H3 to increase the proximity for locations, and data can be analyzed with a lower spatial resolution to allow for anonymization. This is especially important for areas with lower population density where it is easier to identify specific individuals. In essence, this technology removes the possibility of identifying individuals.
With this, businesses can better understand patterns of movements and activities without compromising individuals’ privacy. With the ability to share data confidentiality, people will become more comfortable providing their information, knowing it is truly confidential. Businesses can gather more information for improved analysis and better address their customer needs, which is a win for the customer.
The Geospatial Data Act of 2018, which established new layers of data privacy oversight for most other federal agencies, is just a start. As the geospatial industry continues to grow quickly, we’ll likely see more and more valuable laws being enacted around geo data sharing and confidentiality, which will be crucial to ensuring businesses adhere to privacy guidelines and protect consumers.
Also Read: Liberalization of geospatial data — the expected impact of new policy guidelines
Things to consider when managing data confidentiality:
- To whom data can be disclosed
- Whether laws, regulations, or contracts require data to remain confidential
- Whether data may only be used or released under certain conditions
- Weather data is sensitive by nature and would have a negative impact if disclosed
- Whether data would be valuable to those who aren’t permitted to have it (e.g., hackers)
What are your views on Geospatial 2.0, and how will it impact the economy and society in the coming years?
Verticalization is key. There are vast amounts of telemetry data coming from IOT’s/cell phones and satellite imagery from Showbox satellites capturing images of Earth multiple times a day. There are also many platforms developed to supply and analyze all this data; however, the challenge is that many have not proven helpful to businesses because they are often too generalized and cannot quickly generate actionable insight for any specific industry. Geospatial 2.0 is going to be more about verticalized solutions tailored to specific industries.
