Guest Column: Extracting Value From Mapping Data
Mapping is impacting our lives in lots of different ways. In transport, Google Maps has expanded to use data to let users know whether parking will be easy or limited at their destination. Meanwhile, ride scheduling service Uber recently announced it has started to collect mapping data for drivers on Australia’s Gold Coast streets in order to inform them of traffic patterns and precise pick-up/drop-off locations.
We also see mapping data being used in disaster zones. The U.K. charity MapAction, for instance, used geographic information systems (GIS) to ensure relief workers could be deployed to the right areas quickly following an earthquake in Ecuador in 2016.
Thanks to the rise in mapping activity, there is huge growth in demand for advanced analytics tools, including big data. This presents both opportunities and challenges for the geospatial industry. While the market for accurate mapping data solutions is increasing, the technology required to process these ever-growing data sets is getting more complex. The fact that most data includes or refers to “location” means that any underlying geospatial data must be accurate and up to date. This also means that there is almost certainly value in all records held within enterprise organizations.
Extracting value from this data is opening up the market to those that are willing to invest time and resources into processing and managing it effectively. By following these six core principles, geospatial organizations can maximize the value of their mapping data.
Stage One: Data Creation
First, organizations must extract the location element of the data from their records through processes such as automated feature or character recognition. This can be found in two different types of sources: first, physical assets such as buildings, land or infrastructure, which are typically captured from imagery via 2D or 3D scans; secondly, non-spatial information such as finance, customer or logistical records, which are coded against existing geospatial data sets. To ensure records are as up to date as possible, geospatial providers are constantly expanding their databases. For example, Amsterdam-based mapmaker, TomTom recently announced it had extended its relationship with U.K. mapping company Mappy to increase access to its traffic data from 10 countries to the whole of Europe.
Stage Two: Spreadsheet Refresh
Inaccurate or outdated spatial data could impact the information’s potential value. For example, it would be incredibly difficult to sell data to an automotive company that was looking to integrate sat-nav systems into its vehicles that didn’t include recent updates to the road network or new area speed restrictions. While constantly refreshing data can be costly and time-consuming, it can be achieved by implementing a programmed update cycle. The best data refresh programs are those that include elements of automated change detection and management.
Stage Three: Data Management
Managing data requires much more work than simply keeping it up to date. It’s also about being able to store it effectively and securely. Therefore, an organization must consider whether its data is better suited to a hosted or on-premise storage environment. On top of this, they may also need to integrate their data sets with other applications or migrate them onto new systems, which could require a change in format.
Stage Four: Data Analysis
This stage only works when the information is interrogated to derive value from it. By doing this, geospatial organizations may be able to find new value in data that was previously ignored or overlooked, and they should also be open to manipulating it beyond their traditional instincts. Bank of America, for example, is analyzing its mapping data to save money using location as a basis to make informed decisions on where investment should be prioritized.
Stage Five: Extracting Value
The realization of value will come from having a successful delivery strategy that defines how the organization intends to distribute, publish and share their data. They must be mindful of their intended audience and ensure that the data is delivered in a way that can be used and understood by every stakeholder. To cater to all audiences and their preferences, for instance, Ordnance Survey launched an online mapping system in which a digital map is provided alongside a paper download.
Organizations should also consider compliance to industry or legislative standards such as the Open Geospatial Consortium that looks to “geo-enable” the Web, wireless and location-based services, and mainstream IT or the European INSPIRE Directive, which aims to create a European Union spatial data infrastructure.
Stage Six: Close Collaboration
Finally, organizations should be open to working with third parties who can provide consultation on how to maximize the value of their data. The partner should act as a natural extension of the organization’s own team to ensure consistency and a seamless working relationship.
At a time when mapping data is being used in many different facets of life, both from a business and consumer perspective, there is a huge opportunity for geospatial providers. By following these six guiding principles, organizations will be able to get more out of their mapping data and continually provide their customers with accurate and up-to-date services.