Smartphones have become the main information hub for billions of people around the world, and the market of mobile information services has grown in parallel with thousands of apps that provide great value to individual users, businesses, and institutions. Most mobile applications create or consume data stored in standalone databases, without addressing the potential of interlinking with data from other applications or organizations. The Web community has advocated the use of Linked Data technologies to enable greater data interoperability, with the promise of bringing mobile business closer to its consumers and delivering more relevant content and personalized and customized services than ever before. However, while Linked Data has achieved widespread success as a data publishing mechanism, its use in mobile apps remains purely occasional. Reaching out to end-users with intuitive, attractive, and usable applications based on Linked Data seems critical to finally deliver the promises of the Semantic Web, paving the way to a new generation of ubiquitous applications able to consume structured data from the web (e.g., via the Linked Open Data cloud) and combine that information with contextual information coming from device sensors.

This Special Issue calls for original, high-quality research papers on mobile applications powered by Linked Data. Contributions may address the whole spectrum of related questions, from the design and interaction paradigms of mobile Linked Data apps to the development aids offered to software engineers for embedding semantic technologies easily in their apps and onwards to case studies and market readiness analyses. High-quality critical reviews of the field are also welcomed, discussing the strengths, weaknesses, and promises of Linked Data in relation to new modes of deep learning, big data analytics, and cognitive computing.

Potential topics include but are not limited to the following:

* UI design issues and interaction paradigms for mobile Linked Data
* Tools to facilitate development of mobile Linked Data applications
* Artificial intelligence for mobile Linked Data: context awareness, content adaptation, personalization and recommendation
* Design and experience case studies: information search, entertainment, tourism, education, healthcare, emergency situations, and so forth
* Linked Data for mobile crowdsourcing and crowd computing
* Business models for mobile Linked Data
* Linked Data and/versus machine learning and cognitive computing in mobile information services