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The widely increasing availability and improving resolution of LiDAR data are revolutionising landscape archaeology, allowing the identification of previously unknown archaeological features and thus aiding research as well as heritage protection strategies. This can be achieved even on a countrywide scale by using effective automation techniques. Our work aims at developing an approach to automatically detect hillfort sites cross-regionally, using Britain to train a neural network tool and Italy and Germany to test its transferability to different regions and landscapes. Hillforts are amongst the most evident and iconic archaeological sites in Europe. Usually associated with the Iron Age, they can date from the Neolithic to early Medieval times. The Atlas of Hillforts (Lock and Ralston 2017) provides a comprehensive and up-to-date record of these sites, over 4000 in total, and an invaluable database for further research (e.g., Maddison 2022). The large number of hillforts known in Britain constitutes the best training dataset available to date for developing effective automation for recognising hillforts in remotely sensed data. The variety of landscapes present in Italy and Germany, on the other hand, makes these areas an optimal case study for testing the transferability of this type of automation in different regions.

Virtual reality (VR) systems utilize more and more input and output media in order to make virtual environments more realistic. Furthermore, VR developers nowadays concentrate on rich interaction and behavior. This causes the need for a new type of VR development system architecture. In this paper such a new architecture is proposed and discussed. Its key features include support for new input and output media, device independence, and rapid behavioral prototyping. The Lightning VR system is introduced as a prototype for the presented architecture. It has already shown its usefulness in several industrial applications as design reviews, marketing events, assembly planing, etc.

Virtual reality (VR) systems utilize more and more output media in order to make virtual environments more realistic. Furthermore, VR developers nowadays concentrate on rich interaction and animation. This causes the need for a new VR development system architecture. Such a new architecture is proposed and discussed. Its key features include support for new output media, device independence, and rapid behavioral prototyping. The Lightning VR system is introduced as a prototype for the presented architecture. It has already shown its usefulness in several industrial applications.

Programming-by-demonstration systems often have problems with control structure inference and user-intended generalization. We propose a new solution for these weaknesses based on the concepts of the programming language AWK and present a prototype system for text processing. It utilizes 'vertical demonstration', extensive visual feedback and program visualization via spreadsheets to achieve improved usability and expressive power.

High interactivity in real-time environments requires new system design concepts for virtual reality environments. We will define our understanding of a modern system and describe the prototypical system Lightning, which addresses some of these new features.

Programming by demonstration (PBD) promises to enable non-programmers to do more with their computers. However, PBD systems today are either limited to very narrow application domains, or are not reliable enough concerning the correctness of generated programs. We examine the reasons for this gap between generality and reliability and present a proposal for bridging it, thus leading to a design methodology for general-purpose PBD systems. This is achieved by supporting the visual scanning abilities of humans by a diligently designed user interface, immediate feedback, and ‘trial & error demonstration’. Furthermore, we discuss experiences with a prototype system named Visual AWK implementing the new concept. It enables end-users to create rather complex text-processing programs in a structure editor and thus automates repetitive tasks as they encounter them in their work.