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Kuling.net is a Topic Maps-driven web site where editorially assured cultural historic content meets Web 2.0. In line with the philosophy of collaborative web communities, anyone can contribute at their own level and with their own perspective on content. Kuling.net is developed with pedagogical intent...explanation found at http://www.topicmaps.com/tmc/speaker.jsp?conf=TM2008&id=Tommy_Nordeng

Upper Mapping and Binding Exchange Layer A lightweight, subject concept reference structure for the Web

Graphical ontology editor, plugin for protege

This post would make good fodder for issue mapping

Good potential for an issue mapping exercise

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

The Historical Event Markup and Linking project provides a means of coordinating and navigating disparate historical materials on the internet. It includes 1. an XML schema for historical events which describes the events' participants, dates, location and keywords; the schema associates these with source materials in print or on the web. 2. XSLT stylesheets that combine conforming documents and generate lists, maps and graphical timelines out of them. Heml integrates these resources using the Cocoon2 web publishing engine.

How to Make a Complete Map of Every Thought You Think

Carneades is an argument mapping application, with a graphical user interface, and a software library for building applications supporting various argumentation tasks.

delving into the deep structure of problems by using an issue based mapping method

Narrative techniques both provide a complementary form of what we will call pre-hypothesis research, but further that the use of narrative research techniques produces, through a single intervention, quantitative conclusions supported by narrative context, fragmented knowledge databases, and a mechanism for measuring impact and more complex issues such as mapping ideation cultures.

Snowden again... Looks like a fairly interesting book is on its way, as well...?

Andreas Hotho's talk more specifically addressed the search for methods to identify tags which describe the same concept (or a more specific / a more general concept respectively) within a folksonomy. He suggested two approaches: 1. Applying measures directly to folksonomy statistics, allowing to describe tags as a vector; e.g. co-occurrence frequency and FolkRank could serve as a similarity measure (with these two having a tendency towards high-frequency tags) or a cosine method (which is more likely to produce "siblings") 2. Looking up tags in an external thesaurus/vocabulary (for instance achieving semantic grounding by mapping a tag and its most similar tags with Wordnet Synsets)

By integrating heterogeneous original data with uniform RDF format, creating additional ontology mappings between GO terms, and introducing a set of reasoning rulebases, we proposed a RDF model GORouter.

Using segments of rich media makes it possible to aggregate context and meaning on these chunks by using a number of different mechanisms. Starting with a granular node -- be it a sound bite, visual clip or written fact -- it is possible to aggregate contextual metadata through a series of steps that emergently progress from: * Starting with thousands of defined Audio Sound Bites & visual clips * Rating sound bites and clustering them with folksonomy tags * Sequencing audio sound bites within playlists * Collaboratively building larger sequences with nested playlists * Independently controlling the video & audio tracks with 2-dimensional nested playlists * Evaluating Multiple Storylines and Hypotheses with a 2-dimensional playlist matrix * Visualizing complex networks by mapping out feedback loop relationships between nodes

Unstructured Information Management applications are software systems that analyze large volumes of unstructured information in order to discover knowledge that is relevant to an end user. UIMA is a framework and SDK for developing such applications. An example UIM application might ingest plain text and identify entities, such as persons, places, organizations; or relations, such as works-for or located-at. UIMA enables such an application to be decomposed into components, for example "language identification" -> "language specific segmentation" -> "sentence boundary detection" -> "entity detection (person/place names etc.)". Each component must implement interfaces defined by the framework and must provide self-describing metadata via XML descriptor files. The framework manages these components and the data flow between them. Components are written in Java or C++; the data that flows between components is designed for efficient mapping between these languages. UIMA additionally provides capabilities to wrap components as network services, and can scale to very large volumes by replicating processing pipelines over a cluster of networked nodes.

Upper Mapping and Binding Exchange Layer A lightweight, subject concept reference structure for the Web

OntoWiki facilitates the visual presentation of a knowledge base as an information map, with different views on instance data. It enables intuitive authoring of semantic content, with an inline editing mode for editing RDF content, similar to WYSIWIG for text documents.

Dubai Knowledge Village (DKV), launched in 2003, places the Middle East on the map as a destination for learning excellence. Its 1 KM long picturesque campus provides a ready environment for a variety of knowledge-based entities including training centres and learning support entities.

CollabRx applies collaborative science to slash the time, cost and risk of therapy development. CollabRx builds and operates Virtual Biotechs for foundations and patients who urgently seek cures for their diseases. Working with these foundations and research institutions, CollabRx * builds teams of top researchers * facilitates planning of a strategic road map * brings best practices to therapy development * manages the execution of the plan The CollabRx research platform connects researchers to one another and to a network of scientific services, providing unprecedented opportunities for knowledge sharing and economies of scale.

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.