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OntoWebber is a Web site management system, which facilitates the creation, generation and maintenance of Web sites. Using OntoWebber, site engineers can build site models for domain-specific Web sites. The site models are based on explicit ontologies including the domain ontology and four distinct site-modeling ontologies. Using a RDF-aware rule engine, rules can be defined to check integrity constraints on the resulting site models, thus enforcing desirable properties of the materialized Web site. Both ontologies and site models are expressed using RDF(S)/XML languages. Rules are defined in the F-logic format. The prototype system provides an Integrated Development Environment (IDE) for site engineers to performed all the above tasks for managing Web sites.

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 Lemur Toolkit is a open-source toolkit designed to facilitate research in language modeling and information retrieval. Lemur supports a wide range of industrial and research language applications such as ad-hoc retrieval, site-search, and text mining. The toolkit supports indexing of large-scale text databases, the construction of simple language models for documents, queries, or subcollections, and the implementation of retrieval systems based on language models as well as a variety of other retrieval models. The system is written in the C and C++ languages, and is designed as a research system to run under Unix operating systems, although it can also run under Windows.

The Lemur Toolkit is a open-source toolkit designed to facilitate research in language modeling and information retrieval. Lemur supports a wide range of industrial and research language applications such as ad-hoc retrieval, site-search, and text mining. The toolkit supports indexing of large-scale text databases, the construction of simple language models for documents, queries, or subcollections, and the implementation of retrieval systems based on language models as well as a variety of other retrieval models. The system is written in the C and C++ languages, and is designed as a research system to run under Unix operating systems, although it can also run under Windows.

In our work the traditional bipartite model of ontologies is extended with the social dimension, leading to a tripartite model of actors, concepts and instances.We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages.

The temptation to interpret model noise as forecast information invades our living rooms every night. TV weather-forecast maps look so realistic it is hard not to over-interpret tiny details - to imagine that the band of rain passing over Oxfordshire at noon next Saturday requires postponing a barbecue. Rain may indeed be likely somewhere in the area sometime on Saturday, but the details we see on TV forecasts are noise from the models. I think we are having exactly the same problem with climate projections.

The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biochemical reaction networks in software. It's applicable to models of metabolism, cell-signaling, and many others. SBML has been evolving since mid-2000 thanks to an international community of software developers and users. This website is the portal for the global SBML development effort; here you can find information about all aspects of SBML.

It seems likely that the university grew out of the apprenticeship model of an expert working closely with an apprentice, assigning them challenging tasks and then providing guidance as needed to carry out those tasks, as well as offering ongoing feedback on their work. This model, or its modern day embodiment of "the expert individual tutor," remains the most effective demonstrated approach to education.

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.

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

Here, we present a computational model that learns structures of many different forms and that discovers which form is best for a given dataset. The model makes probabilistic inferences over a space of graph grammars representing trees, linear orders, multidimensional spaces, rings, dominance hierarchies, cliques, and other forms and successfully discovers the underlying structure of a variety of physical, biological, and social domains. Our approach brings structure learning methods closer to human abilities and may lead to a deeper computational understanding of cognitive development.

Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. Python leverages a vast developer-base external to the Neuroscience community, and promises leaps in simulation complexity and maintainability to any neural simulator which adopts it. As more and more simulators support Python, model development times can be drastically reduced by promoting code sharing and reuse across simulator communities. As a result, modellers can devote their software development time to innovating new simulation tools such as network topology databases, stimulus programming, analysis and visualisation tools, and simulation accounting, to name a few.

Special Section on Creating Bayesian Belief Network Models in Ecology

What Are "Bayesian Belief Network Models?" Bruce G. Marcot 24 April 2005 In short, a Bayesian belief network (BBN) is simply a way of showing how things interact and cause specific outcomes.

A new Species-Environment Relations (SER) modeling approach depicts key ecological functions (KEFs) and key environmental correlates (KECs) of terrestrial plant and animal species, as part of a regional assessment of the Interior Columbia Basin Ecosystem Management Project. Assessing KEFs of species is one facet of understanding management effects and ecological integrity of ecosystems. A relational database was developed that ties species' KEFs with their key habitats, KECs, and distribution maps. In this way, potential management activities can be evaluated for how they influence: habitats and environmental correlates; associated plant, invertebrate, and vertebrate species; the array of ecological functions associated with those species; geographic functional ecology; and potential effects on ecosystem productivity, diversity, and sustainability.

We propose a biologically and physically plausible model for ants and pheromones, and show this model to be sufficiently powerful to simulate the computation of arbitrary logic circuits. We thus establish that coherent deterministic and centralized computation can emerge from the collective behavior of simple distributed markovian processes as those followed by ants.

Primarily, we want to create a new tool that uses the unique features of virtual environments to facilitate education, collaboration, and understanding. The output of many supercomputing applications - from astronomical simulations to medical models - is complex and often highly visual. Creating a persistent, standardized environment where these models can reside will make it easier to share and explore these data sets with other researchers. Also, for educators, ScienceSim will provide an interactive 3-D environment that can be used to explain complex concepts such as gravity [see video below] in a highly intuitive manner.

Primarily, we want to create a new tool that uses the unique features of virtual environments to facilitate education, collaboration, and understanding. The output of many supercomputing applications - from astronomical simulations to medical models - is complex and often highly visual. Creating a persistent, standardized environment where these models can reside will make it easier to share and explore these data sets with other researchers. Also, for educators, ScienceSim will provide an interactive 3-D environment that can be used to explain complex concepts such as gravity in a highly intuitive manner.

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.

In my previous article, I introduced the Map/Reduce model as a powerful model for parallelism. However, although Map/Reduce is simple, powerful, and provides a good opportunity to parallelize algorithm, it is based on a rigid procedural structure that requires injection of custom user code and therefore it is not easy to understand the big picture from a high level. You need to drill into the implementation code of the map and reduce functions in order to figure out what is going on.