COSMO is the proposed Common Semantic Model, viewed as consisting of a lattice of ontologies which will serve as a set of basic logically-specified concepts (classes, relations, functions, instances) with which the meanings of all terms and concepts in domain ontologies can be specified. The most important function of the COSMO is to serve as a Foundation Ontology that has a sufficient inverntory of fundamental concept representations so that it can support utilities to translate assertions of fundamentally different ontologies into the terminology and format of each other. The use of a common set of defining concepts will permit accurate interoperability of knowledge-based systems using the logical relations of their ontologies as the basis for reasoning in the system. The COSMO can also be used as the starting ontology for creation of more specialized domain ontologies.
WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at http://www.wikiprofessional.org
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.
Picturing to Learn (PtL) is founded on the following core premises:
one From a student's perspective:
undergraduate students can clarify their own understanding of scientific concepts
and processes by creating drawings that explain these concepts to non-experts.
two From a teacher's perspective:
drawings can be useful as:
* assessment tools, allowing instructors to identify students' scientific
understanding and pinpoint their misconceptions
* educational tools, to help inform instructors' lecture preparation
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)
Sensemaking involves turning circumstances into a situation that is comprehended explicitly in words and that serves as a springboard into action. In this paper we take the position that the concept of sensemaking fills important gaps in organizational theory. The seemingly transient nature of sensemaking belies its central role in the determination of human behavior, whether people are acting in formal organizations or elsewhere. Sensemaking is central because it is the primary site where meanings materialize that inform and constrain identity and action. The purpose of this paper is to take stock of the concept of sensemaking. We do so by pinpointing central features of sensemaking, some of which have been explicated but neglected, some of which have been assumed but not made explicit, some of which have changed in significance over time, and some of which have been missing all along or have gone awry. We sense joint enthusiasm to restate sensemaking in ways that make it more future oriented, more action oriented, more macro, more closely tied to organizing, meshed more boldly with identity, more visible, more behaviorally defined, less sedentary and backward looking, more infused with emotion and with issues of sensegiving and persuasion. These key enhancements provide a foundation upon which to build future studies that can strengthen the sensemaking perspective.
In ECOSPACE, the Semantically Interlinked Online Community (SIOC) is used to facilitate CWE interoperability [1, 2]. SIOC provides an ontology for representing rich data from the Social Web in RDF. The SIOC ontology was recently published as a W3C Member Submission, which was submitted by 16 organisations [3].
The SIOC Core ontology defines the main concepts and properties required to describe information from online communities on the Semantic Web. The main terms in the SIOC Core ontology are shown in Figure 1. The basic concepts in SIOC have been chosen to be as generic as possible, thereby enabling many different kinds of user-generated content to be described. Once proprietary CWE data is annotated with the SIOC ontology, it becomes interpretable by other CWEs. Based on this, a CWE Interoperability Architecture has been designed.
Semantic Cloud is the API that powers semantic search engine SenseBot and contextual linking tool for bloggers LinkSensor. The API supports SOAP and REST protocols (HTTP GET).
The idea is to empower semantic startups or any ventures that are looking to utilize an affordable high-quality semantic solution to build their applications.
Semantic API features include:
* extraction of semantic concepts from a page or document;
* creating a "semantic cloud" of concepts describing a group of documents;
* generating a multi-document summary of a set of pages;
* generating an essay on a topic based on a set of documents.
Multiple parameters allow the client to control the type and format of results.
Belvedere 4.1 is designed to help support problem-based collaborative learning scenarios with concept and evidence moodels, and provides multiple representational views (tables and graphs) on those models.
Belvedere was originally intended to help secondary school students learn critical inquiry skills that they can apply in everyday life as well as in science, but can be adopted to other applications as well.
The Biomedical Grid Terminology (BiomedGT) is an open, collaboratively developed terminology for translational research. BiomedGT builds on the strengths of the NCI Thesaurus, including concept orientation, description logic, and public accessibility. While the current terminology has been seeded with NCI Thesaurus content, it is being restructured to facilitate open content development. The goal is to evolve BiomedGT into a set of federated sub-terminologies, with content maintained by experts in the relevant research communities.
A Semantic Map is kind of like a dictionary, in that it's a representation of Cognition's ability to define things. Cognition claims that its Semantic Map has over 10 million semantic connections; over 4 million semantic contexts (word meanings that create contexts for specific meanings of other related words); over 536,000 word senses (word and phrase meanings); 75,000 concept classes (or synonym classes of word meanings); 7,500 nodes in the technology's ontology or classification scheme; and 506,000 word stems (roots of words) for the English language.
In the process of knowledge discovery, workers examine available information in order to make sense of it. By sensemaking, we mean interacting with and operating on the information with a variety of information processing mechanisms [3,18]. Previously, we introduced a concept that uses the spreadsheet metaphor with cells containing visualizations of complex data. In this paper, we extend and apply a cognitive model called "visual sensemaking " to the Visualization Spreadsheet. We use the task of making sense of a large Web site as a concrete example through out the paper for demonstration. Using a variety of visualization techniques, such as the Disk Tree and Cone Tree, we show that the interactions of the Visualization Spreadsheet help users draw conclusions from the overall relationships of the entire information set.
Using the 1994, South Canyon fire in Colorado as a case study, this article suggests Taylor's (1993) concept of worldview functions as an important "frame" for organizational sensemaking (Weick, 1995a). Taylor argues that organizations use either an "activity" or "particle" orientation. An activity view focuses attention on organizational units while a particle view sees the organization from the point of view of the product or customer. Results from this study indicate that an organization's worldview functions as an overarching metaphor that influences sensemaking and decision-making processes, and that the worldview perspective in retrospective accounts may differ from that of the participants themselves.
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
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.
This project will
1. Provide useful findings about
* why and how people use electronic information
* how system design features affect how well systems meet the needs of users
* how system design features affect the actual use of systems.
2. Apply diverse user-research interpretations to the inquiry, in order to
* focus on both commonalities and diversities in findings and interpretations
* develop boundary-bridging concepts that enable more effective application and collaboration in both system design and user research.
How storytelling communicates complex ideas
In this group of pages, some of the underlying mechanisms of storytelling and its relationships to knowledge and knowledge management are revealed:
Narrative vs abstract thinking : Jerome Bruner
Communications as media : the conventional view of Roman Jakobsen
Communications the interactive view : Walter Ong
Communications as social flow : David Bohm
Stories and archetypes : Carl Jung
Engineering vs ecological viewpoints : John Seely Brown
Storytelling and the literature of persuasion : Homo vendens
Storytelling and genuine persuasion :
Storytelling and seduction : Jean Baudrillard
Storytelling and openness : de Bono
Why isn't storytelling taken seriously? Who's to blame?
Why does science despise storytelling?
Storytelling and zen: Eastern concepts of knowledge
Storytelling and post-modernism: Jean-François Lyotard
Open, distributed, social.
* About The DiSo Project
* Blog
* Links
* Chat
About The DiSo Project
Silo free living.
Social networks are becoming more open, more interconnected, and more distributed. Many of us in the web creation world are embracing and promoting web standards - both client-side and server-side. Microformats, standard apis, and open-source software are key building blocks of these technologies. This model can be described as having three sides/legs/arms/spokes - pick your connection: Information, Identity, and Interaction.
DiSo (dee * zoh) is an umbrella project for a group of open source implementations of these distributed social networking concepts. or as Chris puts it: "to build a social network with its skin inside out".
The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data. With linked data, when you have some of it, you can find other, related, data.
Like the web of hypertext, the web of data is constructed with documents on the web. However, unlike the web of hypertext, where links are relationships anchors in hypertext documents written in HTML, for data they links between arbitrary things described by RDF,. The URIs identify any kind of object or concept. But for HTML or RDF, the same expectations apply to make the web grow:
1.
Use URIs as names for things
2.
Use HTTP URIs so that people can look up those names.
3.
When someone looks up a URI, provide useful information.
4.
Include links to other URIs. so that they can discover more things.
Group items tagged 
