Specialized systems aiming at o ering hypertext functionality in users' computing have been discussed since the early days of hypertext. However, with the claim to also support other structure domains than node-link structures, hypertext systems had to overcome some challenges. Researchers came up with component-based approaches and low level structure services. Due to the raising omnipresence of the Web, research on traditional hypertext systems has been fading out over the past decade. is paper focuses again on hypertext infrastructures and goes beyond ongoing Web discussions. Based on lessons learned from well thought through previous work, we present a novel design for multi-structure supporting, general purpose hypertext systems that can be used in a series of application domains. e system provides intelligence analysis which is needed for sophisticated user support. We argue that this lets us use the hypertext system also as a visual analytics tool. Furthermore, for demonstration purposes we describe the use of the system in combination with a Web-based so ware engineering platform, which is part of the ongoing project ODIN. CCS CONCEPTS •Human-centered computing →Hypertext / hypermedia; •So ware and its engineering →So ware infrastructure;

The idea to associate information with so-called links was developed by hypertext pioneers in the 1960s. In the 1990s the Dexter Hypertext Reference Model was developed with the goal to provide a general model for node-link hypertext systems. In the 1990s and 2000s there were important steps made for hypertext infrastructures, which led to component-based open hypermedia systems (CB-OHS).In this paper we provide a detailed description of node-link structures. We argue that Dexter does not match the need of CB-OHS, as it supports a mix of multiple structure domains. Based on the implementation of link support in our system Mother we demonstrate how Dexter needs to be tailored accordingly. We further describe Mother's ability of node-link structures to interoperate with other available structure services and vice versa.

Software applications become more and more dominant in our daily life and work. However, it is very difficult to provide sophisticated tools for all arising use cases. End-User Development (EUD) is a term that describes the development of applications by end users rather than professional developers. This enables them creating highly specialized solutions. End users are laypersons when it comes to building software, therefore they need appropriate tools for managing the whole development process. This includes designing, implementing and deploying applications. While there are already various tools available, we focus on a recommendation feature for graphical EUD tools, utilizing their spatial hypertext capabilities. In this paper we provide an overview of some common issues such tools are often struggling with. We explain how visually analyzing the workspace, parsing an implicit spatial hypertext and eventually presenting recommendations may tackle them. We further describe the project HEIMDALL in detail, especially the way of generating recommendations for software modules with the aim to raise users' awareness. Furthermore, we discuss the use of such a system that reaches a similar understanding of relationships between software modules as users have. Finally, we point to open issues that still need to be addressed to improve results and their presentation. CCS CONCEPTS • Human-centered computing → Hypertext / hypermedia; Graphical user interfaces; • Software and its engineering → Software creation and management;

The task of organizing and retrieving knowledge is often elaborative and involves different types of media including digital or analog. In this paper we describe a system that is based on related research in the fields of spatial hypertext, information retrieval, and visualization. It utilizes a 2D space on which users can add, remove, or manipulate information entities (so-called user nodes) visually. A spatial parser recognizes the evolving structure and queries a knowledge base for helpful other information entities (so-called suggestions nodes).Similar to user nodes, those suggestions are presented as visual objects in the space. We propose a physics model to simulate their behavior. Their characteristics encode the relevance of suggestions to user nodes and to each other. This enables human recipients to interpret the given visual clues and, thus, identify information of interest. The way users organize nodes spatially influences the parsed spatial structures, i.e., the placement of suggestion nodes. This allows the creation of complex queries without any prior knowledge, yet the users do not have to be aware of that, because they can express their thoughts implicitly by manipulating their nodes.We discuss the strengths of a physics based simulation to encode context visually and point to open issues and potential solutions. On the basis of an implemented demonstrator we show the benefits compared to similar and related applications in the field of information visualization, especially when it comes to tasks where a high portion of creativity is involved and the information space is not well known.

Historically, there has been a tendency to consider hypertext as a type of system, perhaps characterised by provision of links or other structure to users. In this article, we consider hypertext as a method of inquiry, a way of viewing arbitrary systems. In this view, what are traditionally called "navigational hypertext systems" might be considered as information retrieval systems. This opens the hypertext field to various other types of systems that traditionally would not be considered as part of the field. The change of view enables a deeper fusion of human and machine. In particular, today's AI-based, intelligent systems open the demand of synthesising automation (on the machine's side) and augmentation (on the user's side). This article is not about researching AI systems; it is about extending the view of hypertext systems to synthesise augmentation and automation. We specifically apply this view to intelligent systems, asking the question about how hypertext can act as a common medium between human and machine, particularly for knowledge intensive tasks. We propose spatial hypertext as a medium that enables users to create cognitive maps. Along these lines, we provide examples from multiple projects and examine how these applications can be productive.