|Title||Impacts and implications of Big Data for geomatics: backgrounder|
|Author||GeoConnections; Hickling Arthurs Low Corporation|
|Source||Canadian Geospatial Data Infrastructure, Information Product 44e, 2016, 36 pages, https://doi.org/10.4095/297538 (Open Access)|
|Publisher||Natural Resources Canada|
|Related||This publication is a translation of GéoConnexions; Hickling
Arthurs Low Corporation; (2016). Document d'information sur l'incidence et les répercussions des mégadonnées sur la géomatique, Canadian Geospatial Data Infrastructure, Information Product no. 44f|
|Subjects||geophysics; remote sensing; information geology; computer mapping; mapping techniques; data collections; geographic information system|
|Program||GeoConnections Secretariat, GeoConnections Secretariat|
|Released||2016 03 01|
This backgrounder was written to further examine the characteristics of Big Data and the impact it has with the geomatics sector. The first chapter of the report discusses key
concepts of Big Data in detail including its origins, definition, actors and usages. The second chapter of the report addresses the geospatial side of Big Data, starting with the contribution of geomatics to Big Data and vice-versa. The last chapter
concludes with key elements to remember, followed by the appendices and references.
Big data has been an emerging trend in geomatics in recent years with datasets continuing to get larger and more complex resulting in new challenges for
organizations managing and analyzing data. Geospatial information technologies will now play a central role into how successful and useful Big Data can become in the geomatics sector. The emergence of Big Data brings a need for embedding powerful
analytics into organizations that will create additional value from the location base information collected.
Geomatics contributes to the success of Big Data in three main ways: by enriching data visualization, integrating unlinked big data and
more powerful analytics. Many large companies such as Facebook, Amazon and Walmart are already currently using Big Data analytics to link user locations with activities, track inventory and other valuable location based information. Big Data also
benefits from geospatial solutions in various ways from technologies such as digital maps produced from satellite imagery, aerial photographs and GPS-based field measurements.
Big Data (along with Business Intelligence (BI)) concepts are also
impacting the geomatics community in two main ways, as a facilitator, and as a source of innovation. New innovations include new geospatial-specific solutions, new bodies of knowledge, new scientific communities, new specialized conferences, and new
working groups in standardization bodies (e.g., OGC). Big Data is enabling communities to perform new tasks such as combining analytics capabilities with the transactional approach of Geographical Information Systems (GIS) to provide new insights in
spatially-referenced business data. Big data facilitates the geomatics industry with access to powerful, scalable storage and processing services hosted at remote locations, which further simplifies existing work being done.
The rapid growth of
Big Data brings many challenges as well for the geomatics sector. The five main challenges that are currently in need of solutions and strategies include: location privacy, embracing the new paradigm in geomatics, geomatics skills, spatial
interoperability, and geospatial data processing technology. Big Data has also created new opportunities for geomatics communities as experts in geomatics know how powerful geospatial data is with regards to integration, analytics and visualization.
Big Data has already changed the way location based data can be managed and explored and with new possibilities arising information technologies must be implemented to effectively process and analyze the data.
|Summary||(Plain Language Summary, not published)|
This document is intended to inform CGDI stakeholders about 'Big Data' in terms of technologies, usages, challenges, and opportunities, and more
specifically how geospatial data and Big Data are connected. It was written to further examine the characteristics of Big Data and the impact it has with the geomatics sector. It introduces the Big Data concept, including its origins, definition,
actors and usages. It then introduces the relationship of Big Data and geomatics, which includes a discussion of the role of geospatial data in the Big Data ecosystem. In addition, risks in terms of legal or policy related concerns, such as privacy,
opportunities and the value proposition of the geospatial component 'Big Data' are addressed. It concludes with key elements to remember, followed by the appendices and references.