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The "Social Network" of Machines

Ron Lake on December 6, 2012 - in Column

The past decade has clearly been the era of social networks, with revolutionary impact on nearly everything, from social behaviour to mapping and response to emergency events. Associated with the rise of Facebook, Twitter and the other dominant social network sites, we have seen an increased emphasis on “unstructured” data such as imagery, videos and schema-less data stores. This was possible because the intent of these sites and their infrastructure is the direct interaction between humans. Free form tagging, and folksonomies became caché terms of the time.

While I do not envision any decline in the importance of social networks, I think we are at the start of a new kind of network, and that is the “social” network of machines, with a new (or old, depending on your point of view) set of terms, and priorities.

Machine to Machine

Just as the social media sites built on the Internet of people and the web, so too will the social network of machines, build on the Industrial Internet and the Internet of Things. Just as the social networks built new infrastructure on the Internet, and the Web, so too will the social network of machines build new infrastructure on the Internet of Things. What will this look like?

In the social network of persons, machines mediate interactions between people, displaying their images, their histories and interests. Machines carry the messages from one person to another.

In the social network of machines, machines will again mediate the interactions between machines, providing services for machine discovery, data translation, and data transformation. Machines will again carry the messages from one machine to another, but in such a form that machines can readily process, display and interact with the message content. One can anticipate real “social networks” of machines in the sense that some machines will be able to “talk” to each other, while others will not, in much the same way that I can readily chat to people in English, but am quite unable to do the same in Chinese.

Machines will be able to discover one another to communicate. This is not to say that we are constructing the infrastructure of cyborgs or that we are talking about artificial understanding. We are just moving to an era where machine communication becomes easier to accomplish and plays an increasingly significant role in the management of our impact on one another and the world around us.

Drivers and Changes

What will drive this era of the social network of machines? What technology changes are required to make it possible?

The most obvious driver will be the increasing ubiquity of sensors. Sensors to measure our energy consumption, and our carbon emissions. Sensors in our homes and offices, measuring the energy consumed by individual appliances, or the cubicles in which we work. Sensors to measure the quality of the air in the baby’s room, in our office and in the street. Sensors to measure the flow of people, traffic, water and sewage. Sensors to measure the health of our aging parents and ourselves.

Deployment of these sensors will greatly increase the volume of data to be processed. More importantly, inter-machine communication will be necessary to benefit from the investment in the measurement technology. Only through machine processing of this data and interconnections between machines, can we relate traffic flows to carbon emission and to local air quality. While it seems illogical, it is very likely that things will occur in this very bottom up manner – sensing before understanding – sensing before action and control. This has been the way of the world.

To make the social network of machines possible, we need to give increased weight to machine readable data. This means that we strive to encode more of the meaning of the data in the data stream itself; what we use to be call “self-describing” data. This means an increased importance for structured data, meaning data that has an associated information model (e.g. a schema) that can be sent with the data directly or by reference. It also means an increased importance with registration of data sources as well as more formal means for automated discovery than are possible in the world of the Internet of persons. It will also mean increased importance in those information standards that support extensible, machine readable data streams. Content is indeed king, and ever more so in the coming age of social networks of machines.

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About Ron Lake

Ron Lake, chairman and CEO of Galdos Systems Inc., is a founding member of the Open Geospatial Consortium, and author of “Geography Markup Language – Foundation of the GeoWeb”. He has been recognized for his work in creating GML and promoting its standardization on a global level. Mr. Lake plays a significant role in shaping the international conversation regarding the global integration of data and systems dealing with the physical world. He is an internationally recognized speaker in the field of Geographic Information Systems and geospatial interoperability, and he writes and speaks regularly on the topic of advanced spatial information systems.

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