Smart cities and Tech Evolution - XXXX - Soft IoT

The Trentino Region has set up an Open Living Data framework, making its data accessible to third parties to develop services. Furthermore, the data support infrastructure can be used to host third parties data to provide regulated access to them. Credit: Province of Trento

Data can become self standing entities. Each encapsulated entity contains an agent, a set of rules steering the processing of the agent, a set of properties associated to the data, a definition of the context and a track of variations over time. The entity discloses its value(s) upon request and based on the associated rules and can generate alerts when values change.

The Region of Trentino set up an open data framework, http://dati.trentino.it , comprising over 5,100 data sets (as of September 2016. These data sets are available to third parties to develop applications and offer services.

The data are made accessible through a set of API (Application Programming Interfaces) that regulate the access to the Data Platform. The Platform is fed by several public and private data sources.  Through API third parties access clusters of data in a way that ensures privacy, anonimity and ownership protection. At the same time the procedures associated to the provisioning of data on the platform ensure data accoutability and trust.

Data released through the API are tagged, so that their usage can be monitored (this does not applies to all data but to a subset that is deemed relevant from an economic point of view).

The Trentino Region has started to open up its data since 2014 and has worked to make its over 120 data bases accessible as a single cluster of data. This makes data correlation possible. Part of these data sets are static (like geographic information) or semi static (like the catastral records), others are dynamic like power use, transportation data, telecommunication traffic indicators.

 

New projects are required to open up their data and this is increasing the data set made available to third parties. Additionally, whereas old data sets have required different degrees of harmonisation, the new data set are required to comply with the Trentino Open Data framework.

A crucial aspect, to ensure accessibility and at the same time protect privacy and ownership, is to maintain the control of the data. The data has to be seen as an entity, rather than a value. 
 It is an entity that has some properties and an associated set of rules that govern its access and its use. Part of it can be the requirement that any usage has to be monitorable. 

 

In other terms it becomes an encapsulated entity, like a software applications, that provides services and that by itself generates the control structure desired.

As part of the services provided a data entity can generate alerts, as an example when its (set of) value changes. You can easily see this as a virtual sensor. The crucial point is that we no longer have a supervisory function that monitors the data value (set) and generates an alert, rather it the alert generation is a property of the data (set). It is actually part of the rules. These rules are pre-defined as part of the data (set) characteristics but a service provided by the data can also include the possibility of creating/expanding the set of rules for a specific “customer”. This expansion is made possibile through specific APIs.

A data entity can become quite sophisticated and can have rules that determine its interaction with the environment (both in terms of responses to queries activated via APIs as well as alert generation). One interesting property for a data entity is its understanding of the context, that is having its rules taking into account both its data set as well as other data entities connected to it.

Hence a change in a connected data entity, made visible through the generation of an alert, can influence the responses to a query. It is possible to create structures of data entities, hierarchies, that can result in very sophisticated data spaces.

 

This is similar to having clusters of IoT, sensors, reporting to a controller that in turns generates an aggregated data reflecting the “status” of the IoT supervised. It is also not that much different from what is going on in our body, where our senses are conditioned by local situation and are influencing one another.

Our senses are also conditioned by what happened before. They con become “insensitive” or their sensitivity can be hightened. In a way they keep track of the history and to a certain extent they “learn”.

This can also happen to a data entity. Depeding on the way its value set changes over time (and the relations with other data entities) it can change its reactions to queries.

 

Data entities are becoming more and more complex and their value set cannot be disjointed from the interactions taking place. It is becoming a sophisticated IoT, actually it can become more sophisticated than the average IoT.  This is what I call a Soft IoT.

Author - Roberto Saracco

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