AceWiki is a semantic wiki that is powerful and at the same time easy to use. Making use of the controlled natural language ACE, the formal statements of the wiki are shown in a way that looks like natural English. In order to help the users to write correct ACE sentences, AceWiki provides a predictive authoring tool.

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Appropedia is the site for collaborative solutions in sustainability, poverty reduction and international development. Appropedia helps us sustain our world.

MOAT (Meaning Of A Tag) provides a Semantic Web framework to publish semantically-annotated content from free-tagging. While tags are widely used in Web 2.0 services, their lack of machine-understandable meaning can be a problem for information retrieval, especially when people use tags that can have different meanings depending on the context. MOAT aims to solve this by providing a way for users to define meaning(s) of their tag(s) using URIs of Semantic Web resources (such as URIs from dbpedia, geonames … or any knowledge base), and then annotate content with those URIs rather than free-text tags, leveraging content into Semantic Web, by linking data together. Moreover, tag meanings can be shared between people, providing an architecture of participation to define and exchange potential meanings of tags within a community of users. To achieve this goal, MOAT relies on an architecture that can be deployed for any organisation or community and that involves a lightweight ontology, a MOAT server, and some third-party clients .

In this article, we will explore the Map/Reduce approach to turn a sequential algorithm into parallel

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.

Semantic technologies are playing an an increasingly important role in capturing and modeling biological knowledge. Semantic systems biology can complement the bottom-up approach with data-driven generation of hypotheses. Therefore, Semantic Systems Biology (SSB) is a systems biology approach that uses semantic description of knowledge about biological systems to facilitate integrated data analysis.

Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

More than 40 years ago the fragmentation of scientific knowledge was a problem actively discussed but without much visible progress toward a solution; perhaps people then had the consummate wisdom to know that no problem is so big that you can't run away from it.

ARROWSMITH is interactive software that extends the power of a MEDLINE search. It operates on the output of a conventional search in a way that helps the user see new relationships and form and assess novel scientific hypotheses. It is based on the premise that information developed in one area of research can be of value in another without anyone being aware of the fact.

The Bio2RDF project is a tool to convert bioinformatics data and knowledge bases to RDF format. It is a kind of generalized rdfizer for bioinformatics applications, and it is a place for the semantic web life science community to develop and grow.

Semantic web atlas of postgenomic knowledge about human and mouse

This is a sub-project of the BioMoby project. It aims to develop tools in Java in order: * to access BioMoby registries, allowing all features provided by such registries, including but not limited to registering and deregistering of the BioMoby services and their parts, discovering them, and understanding their data in various formats (such as RDF), * to create Java implementations of BioMoby services, especially to help service providers with creating BioMoby data containers (input and output data) without exposing providers to the complexity of the XML required and produced by BioMoby services, and finally

The MOBY system for interoperability between biological data hosts and analytical services The MOBY-S system defines an ontology-based messaging standard through which a client will be able to automatically discover and interact with task-appropriate biological data and analytical service providers, without requiring manual manipulation of data formats as data flows from one provider to the next.

The goal of WikiScience is to create a global community of researchers on wiki communities, with a special focus on Wikipedia and Wikimedia Foundation projects.

Theory Garden™ Seed™ is the brainchild of Professor Richard J. Boland, Jr. and Dr. Tanvir Y. Goraya. It grows from research funded from by the National Science Foundation Program on Coordination Theory and Collaborative Technology. That award was supplemented by a grant from Digital Equipment Corporation and resulted in the development of a software tool named Spider. Publications describing the Spider project are listed below.

Rotman Magazine is published for alumni and friends of the Rotman School of Management three times per year.

We enable people to know who knows. We take a people-centric view on information and provide links to people that are knowledgable about your question at hand. Thereby we help organizations to better leverage the knowledge of their members and work more efficiently.

The mistake is that semantic search engines present us with Google-like search box and allow us to enter free form queries. So we type the things that we are used to asking - primitive queries. It never occurs to us to type in What actor starred in both Pulp Fiction and Saturday Night Fever? or What two US Senators received donations from a foreign entity? We type simple questions, but this is not where the power of semantic search lies. Lets look at the spectrum of semantic technologies from Google, to SearchMonkey, to Powerset, and Freebase to understand what is going on.