How Semantic Technologies Can Help Smart Cities Succeed

With the UN predicting that more than 70 percent of the world’s population will live in urban areas by 2050, the development of sustainable smart cities is a rising need. Cities are now capable of collecting and analyzing enormous amounts of data to automate processes, improve service quality, and to make better decisions. This opens up several possibilities and at the same time challenges. How to transform this data into action?

In this blog post, we will introduce you to the importance of digital infrastructure to public administrations at all levels. You will gain the semantic technologies’ perspective to solve current and upcoming challenges for data management. Two use cases from Australian public organizations will inspire you to think of semantics and artificial intelligence as a suitable solution to succeed as Smart City.

Register for the upcoming webinar on the 19th of June at 3 PM Central European Time and learn from the experts.

Digital Infrastructure as a Commodity

When discussing digitization, people commonly think about sensors, broadband networks, and data centers as being the infrastructure. Access to technology is a key parameter for the dynamic and municipality’s sustainable development. However, IT hardware makes only half of the plot of the story.

A community’s competence of providing access to comprehensive information repositories as a commodity is increasingly enabling enhancing societal living conditions. Data are driving lifestyle, business and administration, so information access is crucial for enterprises, small businesses, citizens, and the municipalities themselves.

To achieve this, context and sense-making of data have to be added to digital infrastructure. Reflecting this to traditional patterns, digital roads need junctions, road signs, and semaphores to function, just like their physical counterparts.

The existing use of social networks and the increasing use of intelligent agents will as well raise the question of how to co-exist in a hybrid world. Human-machine interfaces have to be developed that fulfill security, productivity, but also transparency, privacy and sociability needs of society.

The Semantic Web Approach to Deliver Actionable Knowledge

There are several challenges smart cities face, but from a data perspective, the main is how to break up data silos and how to connect data sources spread across agencies, departments, and third-party providers to create actionable knowledge.

Semantic web technologies solve these two challenges with a standards-based approach that has been widely implemented throughout the World Wide Web and in several enterprise use cases.

A semantic layer on top of your content provides endless possibilities to develop smart city applications within a robust information architecture. Integration harmonizes data and metadata as a Knowledge Graph, which makes content from disparate systems easily accessible. This facilitates nouvelle approaches to quality assurance and trust of information.

A semantic information architecture provides along quality, also context and meaning to your data based on controlled vocabularies. In fact, the context extracted from your content and the meaning obtained from words is what makes semantic applications smart and actionable.

Within this framework, it is reasonable to assume that in a smart city, most city functions could benefit from data that gives them the potential to be more efficient, responsive, and effective.

How to Connect People and Data using Semantics and Artificial Intelligence (AI)

The abundance of digital information together with today’s algorithms and powerful computers took AI to the next level. Artificial Intelligence can reveal new insights from your data, something that was not possible before.

Every AI strategy relies on data quality to provide accurate outputs. Semantic technologies support any AI initiative with a robust information architecture that increases data quality along the entire data lifecycle.

This synergetic relation is what we call Semantic AI. A semantic knowledge graph is used at the heart of a semantic enhanced AI architecture, which provides means for a more automated data quality management.

Semantic AI is the perfect companion when smart cities want to connect people and data. We will demonstrate this with one application scenario and two related use cases.

Smart governance for Smart Cities

Government information is subject to digitization thanks to the internet, the development of digital technology and modern lifestyle that demands more public services available online. Digital Government Data is driving economic growth, competitiveness, innovation, job creation and societal progress in general.

According to SmartCity.Press, e-governance and the involvement of the public in the decision-making process is the most important aspect of smart governance. The European Smart City Model rank and benchmark European medium-sized cities under these three aspects to define how well they do in smart governance:

  • Political awareness
  • Public and social services
  • Efficient and transparent administration

So far we know that making digital data useable for public and social services in an efficient and transparent manner improves city’s smart governance. But how to promote the re-use of digital public data to strengthen democracy and public welfare?

We will demonstrate how semantic technologies in general and, Semantic AI in particular, helped two Australian public organizations to provide better services based on their digital assets.

ANDS – Australian National Data Service

The research sector in Australia has over one hundred research organizations, government agencies, and cultural institutions. To success in the discovery, linking, understanding, and reuse of their research data, ANDS agreed on controlled vocabularies reflected in a semantic knowledge graph. Australian research organizations have now free access to the vocabularies, can create an own machine-readable vocabulary and reuse them inside their community. At the same time, ANDS created a web portal to find data for research that is publicly accessible online.

Healthdirect Australia

Healthdirect is a free service supported by the government of Australia. It provides free health advice based on content from over 140 specialized information providers. Built upon a publicly available thesaurus, they enhanced their semantic knowledge graph by extracting entities from all available content repositories. The final result is a web portal for end-users. Now citizens of a vast territory like Australia don’t need to drive far to get medical services. With the smart symptom checker, most often search queries receive a professional and trustworthy answer.

Conclusions

Only when we follow the approach of integration and the use of a semantic layer to glue together all the different types and models – thereby linking heterogeneous information and data from several sources to solve the data variety problem – are we able to develop interoperable and sustainable information models.

The presented initiatives and applications are based on a mature and forward-looking approach, based on open standards. Grown up to productivity stage, these examples still only give us a small glimpse o what will be possible in the future.

Such model can not only be used inside one city or municipality – but it should also be used to interlink and exchange data and information between cities as well as between provinces, regions, countries and societal digitalization transformation.