Drag it together with Groupie: making RDF data authoring easy and fun for anyone

One of the foremost challenges towards realizing a “Read-write Web of Data” [3] is making it possible for everyday computer users to easily find, manipulate, create, and publish data back to the Web so that it can be made available for others to use. However, many aspects of Linked Data make authoring and manipulation difficult for “normal” (ie non-coder) end-users. First, data can be high-dimensional, having arbitrary many properties per “instance”, and interlinked to arbitrary many other instances in a many different ways. Second, collections of Linked Data tend to be vastly more heterogeneous than in typical structured databases, where instances are kept in uniform collections (e.g., database tables). Third, while highly flexible, the problem of having all structures reduced as a graph is verbosity: even simple structures can appear complex. Finally, many of the concepts involved in linked data authoring - for example, terms used to define ontologies are highly abstract and foreign to regular citizen-users.To counter this complexity we have devised a drag-and-drop direct manipulation interface that makes authoring Linked Data easy, fun, and accessible to a wide audience. Groupie allows users to author data simply by dragging blobs representing entities into other entities to compose relationships, establishing one relational link at a time. Since the underlying representation is RDF, Groupie facilitates the inclusion of references to entities and properties defined elsewhere on the Web through integration with popular Linked Data indexing services. Finally, to make it easy for new users to build upon others’ work, Groupie provides a communal space where all data sets created by users can be shared, cloned and modified, allowing individual users to help each other model complex domains thereby leveraging collective intelligence

Creating information delivery specifications using linked data

The use of Building Information Management (BIM) has become mainstream in many countries. Exchanging data in open standards like the Industry Foundation Classes (IFC) is seen as the only workable solution for collaboration. To define information needs for collaboration, many organizations are now documenting what kind of data they need for their purposes. Currently practitioners define their requirements often a) in a format that cannot be read by a computer; b) by creating their own definitions that are not shared. This paper proposes a bottom up solution for the definition of new building concepts a property. The authors have created a prototype implementation and will elaborate on the capturing of information specifications in the future

Editing OWL through generated CNL

Abstract. Traditionally, Controlled Natural Languages (CNLs) are de-signed either to avoid ambiguity for human readers, or to facilitate auto-matic semantic analysis, so that texts can be transcoded to a knowledge representation language. CNLs of the second kind have recently been adapted to the requirements of knowledge formation in OWL for the Semantic Web. We suggest in this paper a variant approach based on automatic generation of texts in CNL (as opposed to automatic analy-sis), and argue that this provides the best of both worlds, allowing us to pursue human readability in addition to a precise mapping from texts to a formal language.

Collaborative Authoring of Adaptive Educational Hypermedia by Enriching a Semantic Wiki’s Output

This research is concerned with harnessing collaborative approaches for the authoring of Adaptive Educational Hypermedia (AEH) systems. It involves the enhancement of Semantic Wikis with pedagogy aware features to this end. There are many challenges in understanding how communities of interest can efficiently collaborate for learning content authoring, in introducing pedagogy to the developed knowledge models and in specifying user models for efficient delivery of AEH systems. The contribution of this work will be the development of a model of collaborative authoring which includes domain specification, content elicitation, and definition of pedagogic approach. The proposed model will be implemented in a prototype AEH authoring system that will be tested and evaluated in a formal education context

A story environment for learning object annotation and collection : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Palmerston North, New Zealand

With the increase in computer power, network bandwidth and availability, e-learning is used more and more widely. In practice e-learning can be applied in a variety of ways, such as providing electronic resources to support teaching and learning, developing computer based tutoring programs or building computer supported collaborative learning environments. Nowadays e-learning becomes significantly important because it can improve the quality of learning through using interactive computers, online communications and information systems in ways that other teaching methods cannot achieve. The important advantage of e-learning is that it offers learners a large amount of sharable and reusable learning resources. The current approaches such as Internet search and learning object repository does not effectively help users to search for appropriate learning objects. The original story concept introduces a new semantic layer between collections of learning objects and learning material. The basic idea of the story concept is to add an interpretative, semantically rich layer, informally called 'Story' between learning objects and learning material that links learning objects according to specific themes and subjects (Heinrich & Andres, 2003a). One motivation behind this approach is to put a more focused, semantic layer on top of untargeted metadata that are commonly used to describe a single learning object. Speaking from an e-learning context the stories build on learning objects and become information resources for learning material. The overall aim of this project was to design and build a story environment to realize the above story concept. The development of the story environment includes story metadata, story environment components, the story browsing and authoring processes, and tools involved in story browsing and authoring. The story concept suggests different types of metadata should be used in a story. This project developed those different metadata specifications to support story environment. Two prototypes of tools have been designed and implemented in this project to allow users to evaluate the story concept and story environment. The story browser helps story readers to read the story narrative and look at a story from different perspectives. The story authoring tool is used by the story authors to author a story. The future work of this project has been identified in the area of adding features of current tools, user testing and further implementation of the story environment