Group items tagged

Making sense of the world is a ubiquitous activity, taking place around the margins of what we know. At work, your boss says, "Can you give a presentation next week on how wireless will affect our business?" Or perhaps, you join a new committee, and wonder "Who are these people? Who is in charge? What is our mission? What are we really going to do?" Maybe you move to a new neighborhood, and you try to make sense of the streets, schools, parks, shopping, and neighbors. Or you say to yourself, "I really need to get an updated cellphone-what has been happening with the current set of features, costs, plans and new gadgets?" Sensemaking can be a core professional task in itself, as for researchers, designers, or intelligence analysts. It arises when we change our place in the world or when the world changes around us. It arises when new problems, opportunities, or tasks present themselves, or when old ones resurface. It involves finding the important structure in a seemingly unstructured situation. It is an activity with cognitive and social dimensions, and has informational, communicational, and computational aspects.

VIVACE stands for Vortex Induced Vibrations for Aquatic Clean Energy. It doesn't depend on waves, tides, turbines or dams. It's a unique hydrokinetic energy system that relies on "vortex induced vibrations." Vortex induced vibrations are undulations that a rounded or cylinder-shaped object makes in a flow of fluid, which can be air or water. The presence of the object puts kinks in the current's speed as it skims by. This causes eddies, or vortices, to form in a pattern on opposite sides of the object. The vortices push and pull the object up and down or left and right, perpendicular to the current.

A system and method for organizing knowledge in such a way that humans can find knowledge, learn from it, and add to it as needed is disclosed. The exemplary system has four components: a knowledge base, a learning model and an associated tutor, a set of user tools, and a backend system. The invention also preferably comprises a set of application programming interfaces (APIs) that allow these components to work together, so that other people can create their own versions of each of the components. In the knowledge web a community of people with knowledge to share put knowledge in the database using the user tools. The knowledge may be in the form of documents or other media, or it may be a descriptor of a book or other physical source. Each piece of knowledge is associated with various types of meta-knowledge about what the knowledge is for, what form it is in, and so on. The information in the knowledge base can be created specifically for the knowledge base, but it can also consist of information converted from other sources, such as scientific documents, books, journals, Web pages, film, video, audio files, and course notes. The initial content of the knowledge web comprises existing curriculum materials, books and journals, and those explanatory pages that are already on the World Wide Web. These existing materials already contain most of the information, examples, problems, illustrations, even lesson plans, that the knowledge web needs. The knowledge base thus represents the core content (online documents or references to online or offline documents); the meta-knowledge that was created at the time of entry; and a number of user annotations and document metadata that accumulate over time about the usefulness of the knowledge, additional user opinions, certifications of its veracity and usefulness, commentary, and connections between various units of knowledge.

In particular, I am thinking about intentional communities -- communities in which people live geographically near one another, and participate in community together, by choice. They may live together or not, dine together or not, work together or not, worship together or not -- but at least they need to live within some limit of proximity to one another and participate in community together. These are the minimum requirements. But is there a model that works? Or is it time to design a new model that fits the time and place in which we live better?

This talk is an essay on design. In the 16th century, Michel de Montaigne invented a new genre of writing he called an essai, which in modern French translates to attempt. Since then, the best essays have been explorations by an author of a topic or question, perhaps or probably without a definitive conclusion. Certainly in a good essay there can be no theme or conclusion stated at the outset, repeated several times, and supported throughout, because a true essay takes the reader on the journey of discovery that the author has or is experiencing. This essay-on design-is based on my reflections on work I've done over the past 3 years. Some of that work has been on looking at what constitutes an "ultra large scale software system" and some on researching how to keep a software system operating in the face of internal and external errors and unexpected conditions.

What is the OpenKnowledge project? In a nutshell, OpenKnowledge is a system which allows peers on an arbitrarily large peer-to-peer network to interact productively with one another without any global agreements or pre-run-time knowledge of who to interact with or how interactions will proceed. Any kind of service (e.g., a WSDL service) can become a peer or else we provide facilities for users to easily create their own peer, by sharing existing code or writing their own.

Open Archives Initiative Object Reuse and Exchange (OAI-ORE) defines standards for the description and exchange of aggregations of Web resources. This document provides an introduction and lists the specifications and user guide documents that make up the OAI-ORE standards.

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.

Action research is a reflective process of progressive problem solving led by individuals working with others in teams or as part of a "community of practice" to improve the way they address issues and solve problems. Action research can also be undertaken by larger organizations or institutions, assisted or guided by professional researchers, with the aim of improving their strategies, practices, and knowledge of the environments within which they practice.

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.

In the following, we document the following types of information for behaviors (e.g., group goal setting), phenomena (e.g., team performance), or concepts (e.g., process gain), pathologies (e.g., social loafing), biases (e.g., loss aversion). For each, we list one or more of the following, depending on the richness of available research, listing both theories and empirical evidence where available: * Typology (what is it?) * Origins, mechanisms, mediators (how does it work?) * Issues, pathologies, biases (what are the problems with its workings?) * Determinants, moderators (what affects it, directly or indirectly?)

# The primary intention of creating aTags is not the categorization of the document, but the representation of the key facts inside the document. Key facts in the biomedical domain might be, for example, "Protein A interacts with protein B" or "Overexpression of protein A in tissue B is the cause of disease C". # An aTag is comprised of a set of associated entities. The size of the set is arbitrary, but will typically lie between 2 and 5 entities. For example, the fact "Protein A binds to protein B" can be represented with an aTag comprising of the three entities "Protein A", "Molecular interaction" and "Protein B". Similarly, the fact "Overexpression of protein A in tissue B is the cause of disease C" can be represented with an aTag comprising of the four entities "Overexpression", "Protein A", "Tissue B" and "Disease C". # Each document or database entry can be described with an arbitrary number of such aTags. Each aTag can be associated with the relevant portions of text or data in a fine granularity. # The entities in an aTag are not simple strings, but resources that are part of ontologies and RDF/OWL-enabled databases. For example, "Protein A" and "Protein B" are resources that are defined in the UniProt database, whereas "Molecular Interaction" is a class in the branch of biological processes of the Gene Ontology. They are identified with their URIs.

TagCrowd is a web application for visualizing word frequencies in any user-supplied text by creating what is popularly known as a tag cloud or text cloud. TagCrowd is taking tag clouds far beyond their original function: * as topic summaries for speeches and written works * as blog tool or website analysis for search engine optimization (SEO) * for visual analysis of survey data * as brand clouds that let companies see how they are perceived by the world * for data mining a text corpus * for helping writers and students reflect on their work * as name tags for conferences, cocktail parties or wherever new collaborations start * as resumes in a single glance * as visual poetry

Annotea Ubimarks is part of Annotea social bookmarks and topics work in Mozilla. It lets any user familiar with the common bookmark user interface metaphora to create metadata for Semantic Web while the complexities of the Semantic Web are hidden from the users. It also offers users better means to share and combine bookmark data and bookmark categories, or topics from several locations or with other metadata. Topics in Annotea can be very simple tags or they can form hierarchies.

The problem with social networking services is that you do not control a social network, which can behave in highly unpredictible ways according to the theory of complex systems, especially if the strategic intent of its originator is not clear. For me, no human society, whether in the real world or in the virtual world, can survive without some form of visible leadership, i.e. someone who symbolizes what the brand stands for. I don't know about Facebook, and I honestly do not understand where it is going. But for Wikipedia, there is a big risk remaining faceless. In France, Wikipedia is said to be in the hands of the far left of the political spectrum, and manipulating content accordingly. It might be true or not, but if nobody stands up against this accusation, it might prevail in the end. Perception is reality.

tagCare lets you to maintain all your tags jointly in one place, which is especially useful if you normally use several of these different platforms. Many users apply a variety of different tags within different platforms - and finally get lost among them. For example, it is hard to keep track of consistent spelling variants (e.g. not using "science_fiction" in one case and "scienceFiction" in the other) or of preferred terms (e.g. not using "bike" in one case and "bicycle" in the other). Some documents may be tagged with the general term "dog", others more specifically with "greyhound" or "border_collie". tagCare will help you to apply some structure to your tagging vocabulary so that you will more easily navigate through vocabulary choices and use tags more consistently. In tagCare, a user can assemble all tags which he has used within different systems and may then create his own vocabulary hierarchy, synonym collections and cross-references to related terms to establish some lightweight form of controlled vocabulary. This process is also called "tag gardening". Edited and structured tags will then be used to browse document collections in other platforms and to directly tag documents out of tagCare. tagCare is still under development, a first demo version will be available soon and more features will then be added step by step. tagCare will first support Flickr, Bibsonomy and del.icio.us.

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)

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.

To begin using SemantiFind, you must go to www.google.com - the service won't work from iGoogle or your Google search box in your browser. After you enter your search term in the box as usual, you then are prompted to indicate the precise meaning of your term before starting your query. This is done through the use of a drop-down box where specific terms and their definitions display. For example, if you were searching for "Georgia," you would be presented with the option to select either the U.S. state or the former soviet republic.

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.