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The confluence of computers, communications, and databases is quickly creating a distributed database where many applications require real-time access to both temporally accurate and multimedia data. This is particularly true in military and intelligence applications, but these required features are needed in many commercial applications as well. We are developing a distributed database, called BeeHive, which could offer features along different types of requirements: real-time, fault-tolerance, security, and quality-of service for audio and video. Support of these features and potential trade-offs between them could provide a significant improvement in performance and functionality over current distributed database and object management systems. In this paper, we present a high level design for BeeHive architecture and sketch the design of the BeeHive Object Model (BOM) which extends object-oriented data models by incorporating time and other features into objects, resulting in a highly reflective architecture.

On January 07, 2009, OASIS announced the submission of a draft charter for a new OASIS Technical Committee to define an integrated collaboration object model supporting a complete range of enterprise collaboration activities. The proposed data model is based upon the Oracle Beehive Object Model (BOM), to be contributed by Oracle to the ICOM TC. The new standard model, interface, and protocol would support contextual collaboration within business processes for an integrated collaboration environment which includes communication artifacts (e.g., email, instant message, telephony, RSS), teamwork artifacts (such as project and meeting workspaces, discussion forums, real-time conferences, presence, activities, subscriptions, wikis, and blogs), content artifacts (e.g., text and multi-media contents, contextual connections, taxonomies, folksonomies, tags, recommendations, social bookmarking, saved searches), and coordination artifacts (such as address books, calendars, tasks) etc.

The Object-Oriented Hypermedia Design Method (OOHDM) (and its successor, the Semantic Hypermedia Design Method, SHDM) allow the concise specification and implementation of hypermedia (web) applications. This is achieved based on various models describing information (conceptual), navigation and interface aspects of these applications, and the mapping of these models into running applications, in various environements.

But invariably, simple models and a lot of data trump more elaborate models based on less data."

See also: http://lists.w3.org/Archives/Public/semantic-web/2008Apr/0005.html NaturalOWL is an open-source natural language generation engine written in Java. It produces descriptions of individuals (e.g., items for sale, museum exhibits) and classes (e.g., types of exhibits) in English and Greek from OWL DL ontologies. The ontologies must have been annotated in RDF with linguistic and user modeling resources. We demonstrate a plug-in for Protege that can be used to produce these resources and to generate texts by invoking NaturalOWL. We also demonstrate how NaturalOWL can be used by robotic avatars in Second Life to describe the exhibits of virtual museums. NaturalOWL demonstrates the benefits of Natural Language Generation (NLG) on the Semantic Web. Organizations that need to publish information about objects, such as exhibits or products, can publish OWL ontologies instead of texts. NLG engines, embedded in browsers or Web servers, can then render the ontologies in multiple natural languages, whereas computer programs may access the ontologies directly.

The project KiWi is concerned with knowledge management in Semantic Wikis and funded by the European Commission under the Project Number 211932 in the EU Seventh Framework Programme (FP7). KiWi's objective is to investigate how knowledge management in highly dynamic environments can be supported using Semantic Wiki technologies, and how Semantic Wikis can be improved to satisfy the requirements of knowledge management. For this purpose, KiWi will * implement an advanced knowledge management system based on the Semantic Wiki IkeWiki and extend it by improved, rule-based reasoning support, information extraction, personalisation, and advanced visualisations and editors * verify the system on two use cases in the areas of project knowledge management and software knowledge management, with flexible workflow models and specific support for the respective application areas.

Faviki is a social bookmarking tool which allows you to tag webpages you want to remember with Wikipedia terms. This means that everybody uses the same names for tags from the world's largest collection of knowledge. Thanks to DBpedia, which extracts structured information from Wikipedia and represents it in a flexible data model, these tags are reference to objects which are categorized automatically, keeping your and your friend's bookmarks and interests well organized.

SMORE is a tool that allows users to markup their documents in RDF using web ontologies in association with user-specific terms and elements. The aim of this software is as follows: To provide the user with a flexible environment in which he can create his web page without too many hindrances involving markup To allow the user to markup his document with minimal knowledge of RDF terms and syntax. However, the user should be able to semantically classify his data set for annotation i.e. breakup sentences into the basic subject-predicate-object model To provide a reference to existing ontologies on the Internet in order to use more precise references in his own web page/text. The user can also create his own ontology from scratch and borrow terms from existing ontologies To ensure accurate and complete RDF markup with scope to make modifications easily

Rapid advances in information technologies continue to drive a flood of data and analysis techniques in ecological and environmental sciences. Using these resources more effectively and taking advantage of associated cross-disciplinary research opportunities poses a major challenge to both scientists and information technologists. These challenges are now being addressed in projects that apply knowledge representation and Semantic Web technologies to problems in discovering and integrating ecological data and data analysis techniques. In this paper, we present an overview of the major ontological components of our project, SEEK ("Science Environment for Ecological Knowledge"). We describe the concepts and models that are represented in each, and present a discussion of potential applications of these ontologies on the Semantic Web

Individual-intelligence research, from a neurological perspective, describes the cortex as a medium for performing conceptual abstraction and specification. This idea has been used to explain how motor-cortex regions responsible for different behavioral modalities such as writing and speaking can express the same general concept represented in the cortex. For example, the concept of a dog, abstractly represented in the higher-layers of the cortex, can either be written or spoken about depending on the context. Abstract models in the higher-layers propagate activation patterns down the cortical hierarchy to the desired region of the motor-cortex for worldly implementation. In this paper, the individual-intelligence framework is expanded to incorporate collective-intelligence within a hyper-cortical construct. This hyper-cortex is a multi-layered network used to represent abstract collective concepts. This collective-intelligence framework plays an important role in understanding how collective-intelligence systems can be engineered to handle collective problem-solving. To conclude the paper, five common problems in the scientific community are solved using an artificial hyper-cortex generated from digital-library metadata.