Supporting Distributed Coalition Planning with Semantic Wiki Technology

Contemporary and near-future military coalition environments present a number of challenges for military planning. Not only must military planners create plans against a backdrop of strict time constraints and uncertain information, they must also coordinate their planning efforts with other planning staff (often from different organizational, linguistic and cultural communities). This paper examines the potential for semantic wikis to support collaborative planning activities in the face of these challenges. Whilst we do not claim that semantic wikis could support all aspects of the collaborative planning process, we do suggest that semantic wikis can provide a highly configurable online editing environment which is likely to be of value in at least some coalition planning contexts. The strengths of semantic wikis include their support for distributed editing, their support for flexible forms of information presentation, and the opportunities they provide for new forms of inter-agent coordination. Their weaknesses include the absence of supportive plan editing interfaces and the limited support for the representation of highly expressive planning models. In the current paper, we discuss this profile of strengths and weaknesses, and we also discuss how a specific semantic wiki system, namely Semantic MediaWiki, could be used to support some aspects of collaborative planning

How Controlled English can Improve Semantic Wikis

The motivation of semantic wikis is to make acquisition, maintenance, and mining of formal knowledge simpler, faster, and more flexible. However, most existing semantic wikis have a very technical interface and are restricted to a relatively low level of expressivity. In this paper, we explain how AceWiki uses controlled English - concretely Attempto Controlled English (ACE) - to provide a natural and intuitive interface while supporting a high degree of expressivity. We introduce recent improvements of the AceWiki system and user studies that indicate that AceWiki is usable and useful

AceWiki: A Natural and Expressive Semantic Wiki

We present AceWiki, a prototype of a new kind of semantic wiki using the controlled natural language Attempto Controlled English (ACE) for representing its content. ACE is a subset of English with a restricted grammar and a formal semantics. The use of ACE has two important advantages over existing semantic wikis. First, we can improve the usability and achieve a shallow learning curve. Second, ACE is more expressive than the formal languages of existing semantic wikis. Our evaluation shows that people who are not familiar with the formal foundations of the Semantic Web are able to deal with AceWiki after a very short learning phase and without the help of an expert.Comment: To be published as: Proceedings of Semantic Web User Interaction at CHI 2008: Exploring HCI Challenges, CEUR Workshop Proceeding

Combining Semantic Wikis and Controlled Natural Language

We demonstrate AceWiki that is a semantic wiki using the controlled natural language Attempto Controlled English (ACE). The goal is to enable easy creation and modification of ontologies through the web. Texts in ACE can automatically be translated into first-order logic and other languages, for example OWL. Previous evaluation showed that ordinary people are able to use AceWiki without being instructed

ODEWiki: A Semantic Wiki That Interoperates with the ODESeW Semantic Portal

We present ODEWiki, a technology for the development of Semantic Wikis, which has a combined set of added-value features over other existing semantic wikis in the state of the art. Namely, ODEWiki interoperates with an existing semantic portal technology (ODESeW), it manages inconsistencies raised because of the distributed nature of knowledge base development and maintenance, it uses RDFa for the annotation of the resulting wiki pages, it follows a WYSIWYG approach, and it allows decoupling wiki pages and ontology instances, that is, a wiki page may contain one or several ontology instances. Although some of these features appear in some of the state-of-the-art semantic wikis, but they are not combined together in a single solution

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

AceWiki: Collaborative Ontology Management in Controlled Natural Language

AceWiki is a prototype that shows how a semantic wiki using controlled natural language - Attempto Controlled English (ACE) in our case - can make ontology management easy for everybody. Sentences in ACE can automatically be translated into first-order logic, OWL, or SWRL. AceWiki integrates the OWL reasoner Pellet and ensures that the ontology is always consistent. Previous results have shown that people with no background in logic are able to add formal knowledge to AceWiki without being instructed or trained in advance

Combining knowledge discovery, ontologies, annotations, and semantic wikis

Semantic Wikis provide an original and operational infrastructure for efficiently com- bining semantic technologies and collaborative design activities. This text presents: a running example and its context (organization of the collections in a museum); concepts of wikis as a tool to allow computer supported cooperative work (cscw); concepts of se- mantic technologies and knowledge representation; concepts and examples of semantic wikis; anatomy of a semantic wiki (reasoning tools, storage, querying); and research directions.Laboratorio de Investigación y Formación en Informática Avanzad

Reason Maintenance - State of the Art

This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques

Constructive Reasoning for Semantic Wikis

One of the main design goals of social software, such as wikis, is to support and facilitate interaction and collaboration. This dissertation explores challenges that arise from extending social software with advanced facilities such as reasoning and semantic annotations and presents tools in form of a conceptual model, structured tags, a rule language, and a set of novel forward chaining and reason maintenance methods for processing such rules that help to overcome the challenges. Wikis and semantic wikis were usually developed in an ad-hoc manner, without much thought about the underlying concepts. A conceptual model suitable for a semantic wiki that takes advanced features such as annotations and reasoning into account is proposed. Moreover, so called structured tags are proposed as a semi-formal knowledge representation step between informal and formal annotations. The focus of rule languages for the Semantic Web has been predominantly on expert users and on the interplay of rule languages and ontologies. KWRL, the KiWi Rule Language, is proposed as a rule language for a semantic wiki that is easily understandable for users as it is aware of the conceptual model of a wiki and as it is inconsistency-tolerant, and that can be efficiently evaluated as it builds upon Datalog concepts. The requirement for fast response times of interactive software translates in our work to bottom-up evaluation (materialization) of rules (views) ahead of time – that is when rules or data change, not when they are queried. Materialized views have to be updated when data or rules change. While incremental view maintenance was intensively studied in the past and literature on the subject is abundant, the existing methods have surprisingly many disadvantages – they do not provide all information desirable for explanation of derived information, they require evaluation of possibly substantially larger Datalog programs with negation, they recompute the whole extension of a predicate even if only a small part of it is affected by a change, they require adaptation for handling general rule changes. A particular contribution of this dissertation consists in a set of forward chaining and reason maintenance methods with a simple declarative description that are efficient and derive and maintain information necessary for reason maintenance and explanation. The reasoning methods and most of the reason maintenance methods are described in terms of a set of extended immediate consequence operators the properties of which are proven in the classical logical programming framework. In contrast to existing methods, the reason maintenance methods in this dissertation work by evaluating the original Datalog program – they do not introduce negation if it is not present in the input program – and only the affected part of a predicate’s extension is recomputed. Moreover, our methods directly handle changes in both data and rules; a rule change does not need to be handled as a special case. A framework of support graphs, a data structure inspired by justification graphs of classical reason maintenance, is proposed. Support graphs enable a unified description and a formal comparison of the various reasoning and reason maintenance methods and define a notion of a derivation such that the number of derivations of an atom is always finite even in the recursive Datalog case. A practical approach to implementing reasoning, reason maintenance, and explanation in the KiWi semantic platform is also investigated. It is shown how an implementation may benefit from using a graph database instead of or along with a relational database