Advances in online technology and news systems, such as automated reasoning across digital resources and connectivity to cloud servers for storage and software, have changed digital journalism production and publishing methods. Integrated media systems used by editors are also conduits to search systems and social media, but the lure of big data and rise in fake news have fragmented some layers of journalism, alongside investments in analytics and a shift in the loci for verification. Data has generated new roles to exploit data insights and machine learning methods, but access to big data and data lakes is so significant it has spawned newsworthy partnerships between media moguls and social media entrepreneurs. However, digital journalism does not even have its own semantic systems that could protect the values of journalism, but relies on the affordances of other systems. Amidst indexing and classification systems for well-defined vocabulary and concepts in news, data leaks and metadata present challenges for journalism. By contrast data visualisations and real-time field reporting with short-form mobile media and civilian drones set new standards during the European asylum seeker crisis. Aerial filming with drones also adds to the ontological base of journalism. An ontology for journalism and intersecting ontologies can inform the design of new semantic learning systems. The Semantic CAT Method, which draws on participatory design and game design, also assists the conceptual design of synthetic players with emotion attributes, towards a meta-model for learning. The design of context-aware sensor systems to protect journalists in conflict zones is also discussed.