How do crowdsourcing, the Internet of Things and Big Data converge on geospatial technology?

by Matt Ball on October 7, 2011

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While this column title may sound a bit like buzzword bingo, perhaps only missing ‘in the cloud’ to declare a winner, all of these technology trends are linked strongly to the power of geospatial technology to synthesize, visualize and analyze global change. We live in a time of great technological, political, and social disruption, amid expanding environmental extremes. The power of geospatial technology to integrate these various pressures, and sort out priorities, is of the utmost importance.

Each of these technological movements has sprung up independently, but they are all interrelated with the enabler of ubiquitous worldwide information exchange. The sil0- and discipline-breaking power of the Internet has only just begun to be felt, and these trends of people as sensors, things monitored and controlled remotely, and a wealth of data to be mined for greater insight, are all offshoot benefits of the power of greater connectivity.

Crowd Advantage

More and more people are choosing their mobile device as their first choice for online activity, with these handheld tools becoming an indispensable guide. Increasing access to the sensors on these devices for location and readings on surroundings has made these tools a primary input for data collection activities. With these factors in mind, a growing number of initiatives are harnessing mobile users to combine their actions and insights to inform fact-finding objectives.

In the geospatial realm, the OpenStreetMap spatial data building effort uses a community of contributors in a crowdsourcing project that spans the globe, urging contributors to take charge of their neighborhood map and to continuously add data as their surroundings change. This community questions the viability of for-profit spatial data efforts given the huge cost of updates and the never-ending need. With low-overhead and an engaged community, the free and open spatial data model is proving effective in terms of data quality and coverage.

The tools of crowdsourced geospatial data gathering have proven to be very powerful for disaster response as in the action after the Haiti earthquakes, and for the aggregation of on-the-ground conditions, such as the Arab Spring uprisings. Here, location was a key aggregation point for input from the crowd, and map creation by the crowd accurately depicted dynamic situations.

Things Alive

The idea that all objects in our daily lives will be uniquely identified and connected to the network in order to be inventoried by computers and controlled remotely, is coming together. Central to the concept is the ability to discern the identity, status and location of these things. With these details known and accounted for, things can become active participants in our lives and business processes, and can even act autonomously on our behalf. Woven into the Internet of Things is the concept of the sensor web, where sensors on objects and active in our environments take stock of their surroundings and communicate conditions.

The complexity of such an interactive and interconnected system will require means to organize and simplify interactions. One of the easiest approaches to this simplification revolves around the geographic location, size and dimension of things. Location in time and space will be an increasingly important factor for tracking and controlling the interactions, particularly when things begin acting autonomously. There is significant work being done in the geospatial standards space to factor in the issues of control and interoperability of things in geographic space.

Insight Without Accumulation

Both crowdsourcing and the Internet of Things will generate large volumes of data, leading to the third emerging trend of Big Data. The challenges of big data is that with larger datasets it become more difficult to catalog, store, search, share and analyze all of the information that we are collecting. With the world’s data more than doubling every two years, the issues aren’t trivial, but fortunately our computing capacity has been keeping up, and approaches to log and simplify all the data inputs are being worked out, with cloud computing providing much-needed capacity.

While there are challenges, the benefits of having more available and openly accessible data has phenomenal implications for how we understand and interact with our world. The amount of accessible information provides the means for new insights based on patterns and through sharing across disciplines. For the scientific community, this access can free scientists up for immediate explorations of hypotheses rather than long processes of data collection and management, effectively bypassing the need for any data collection.

Geospatial technology has been at the forefront of Big Data from the start, due to large volumes of remote sensing and vector data that need to be stored and managed. In fact, when Microsoft Research set out to demonstrate database scalability way back in 1997, they used aerial imagery as their demonstration project, standing up the TerraServer that is still active today. With the problems of compiling and visualizing global data, there is much that the world can benefit from the industry that serves up the world.

These three trends are gathering a lot of interest, and driving a lot of research and innovation. Because geospatial technology is at the nexus of these trends, we can expect that technology companies and practitioners will benefit from the interest. There has always been a need to better predict the future in order to make more informed decisions, and with these combined tools we’re reaching whole new levels of insight.

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