The KM4City project released another addition to its ecosystem called SNAP4City. SNAP4City, which stands for “scalable Smart aNalytic APplication builder for sentient Cities and IOT,” is built on top of KM4City and provides a flexible method and solution to quickly create a large range of smart city applications. It exploits heterogeneous data and enables services for stakeholders by IoT/IoE (Internet of Everything), data analytics, and big data technologies.

The KM4City Ecosystem is a complete, open-source, modern data solution for smart cities. The ecosystem is implemented using data from 33 cities and regions across Europe and supports many smart city dashboards and applications. This includes mobile applications accessible to both the public agencies and the general public.

The Open Connectivity Foundation is working to secure interoperability for consumers, businesses, and industries by delivering a standard communications platform; a bridging specification; an open source implementation; and a certification program allowing IoT devices to communicate regardless of form factor, operating system, service provider, transport technology, or ecosystem.

ATIS/US Ignite, through their Smart City Data Exchange Initiative, have brought together smart cities' leaders and industry experts to tackle data sharing issues and work on a common framework for “the secure and interoperable exchange of data beyond city operational boundaries.” Their Smart Cities Data Sharing Framework

The Global City Teams Challenge from the National Institute of Standards and Technology (NIST) developed The Municipal IoT Blueprint.

Smart City PDX, the smart city project for Portland, OR, is partnering with the community to make Portland a place where data and technology are used to improve people’s lives, particularly in underserved communities.

Columbus, Ohio, the winner of the USDOT Smart City Challenge, was designated as America's Smart City. The Smart Columbus project funded the development of a range of smart city projects – from self-driving shuttles to prenatal trip assistance to a multimodal trip planning application – that demonstrate the value of data in a smart city environment.

There are a multitude of freight databases, both public and private, that do not conform to any uniform standard or ontology. This makes the creation of one single authoritative ontology challenging, as the individual data sources do not and will not share a common vocabulary.

The SHRP2 program sponsored a number of studies relating to Freight Demand Modeling and Local Freight Data Improvement. The program included an analysis of the current state of practice for f

This project developed guidance for local agencies, MPOs, and state DOTs to utilize the rapidly emerging data being collected and processed by the private sector in urban and metropolitan areas. The study defined and described new data sources; examined approaches, methods, and analytical techniques that enable agencies to better carry out their planning, programming, and operations responsibilities.