Group items tagged

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.

KHarvester (Informal Knowledge Harvester) is a SOA layer which collects RDF data from web pages. It provides REST based Web Services for managing data available on Social Semantic Information Sources (SSIS): semantic blogs, semantic wikis, and JeromeDL (the Social Semantic Digital Library). These Web Services allow saving harvested data in the informal knowledge repository, and providing them in a form of informal Learning Objects (LOs) that are described accroding to LOM (Learning Object Metadata) standard. Also, IKHarvester is an extension to Didaskon system. Didaskon (διδάσκω - gr. teach) delivers a framework for composing an on-demand curriculum from existing Learning Objects provided by e-Learning services (formal learning). Moreover, the system derives from SSIS which provide informal knowledge. Then, the selection and work-flow scheduling of Learning Objects is based on the semantically annotated specification of the user's current skills/knowledge (pre-conditions), anticipated resulting skills/knowledge (goal) and technical details of the clients platform.

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.

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.

The Distributed Annotation System (DAS) defines a communication protocol used to exchange biological annotations. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities.

"The debate within the Web community over the optimal means by which to organize information often pits formalized classications against distributed collaborative tagging systems. A number of questions remain unanswered, however, regarding the nature of collaborative tagging systems including whether coherent categorization schemes can emerge from unsupervised tagging by users. This paper uses data from the social bookmarking site del.icio.us to examine the dynamics of collaborative tagging systems. In particular, we examine whether the distribution of the frequency of use of tags for “popular” sites with a long history (many tags and many users) can be described by a power law distribution, often characteristic of what are considered complex systems. We produce a generative model of collaborative tagging in order to understand the basic dynamics behind tagging, including how a power law distribution of tags could arise. We empirically examine the tagging history of sites in order to determine how this distribution arises over time and to determine the patterns prior to a stable distribution. Lastly, by focusing on the high-frequency tags of a site where the distribution of tags is a stabilized power law, we show how tag co-occurrence networks for a sample domain of tags can be used to analyze the meaning of particular tags given their relationship to other tags."

The paper shows that the tags users choose are not chaotic, but rather quickly converge to a common descriptive set of tags that is almost unchanging over time. Perhaps once the tags have stabilized, coherent URI-based identification schemes could emerge?

Nice paper, thanks. Categories / tags / subjects / topics / issues ... that's what I'm working with right now. p.s. sure would be nice if the email notification included the source URL. I'm far more likely to download the PDF when I see something like www2007.org/paper635.pdf

DynaQ stands for 'Dynamic Queries for document based, personal information spaces'. The goal of the project is to conceptualise and to develop a prototypical inquiry system to explore the personal information space, that supports the user with the help of the searching paradigm orienteering. The document-based, personal information space of the user constitutes by all documents on his computer. Included are documents of several file formats (e.g. *.pdf), but also the users emails. Also included are all available meta informations and existing semantic informations according to the documents. Users that are not aware of the scientific context of the project can just think of DynaQ as an desktop search engine.

The relationship among data, information and knowledge is often depicted as a pyramid. With data at the base, it's converted to information and information converted to knowledge. This metaphor of a pyramid or ladder to explain these concepts is unhelpful because you start to believe one is better than the other and there is a tendency to extrapolate to the next level believing that knowledge is simply extrapolated to form wisdom-I have even heard people talk about wisdom management. My two days at the meaning making symposium has helped me see this relationship differently, that is, viewing data, information and knowledge as a system.

a particular methodology of Brenda Dervin

Sense-Making is an approach to thinking about and implementing communication research and practice and the design of communication-based systems and activities. It consists of a set of philosophical assumptions, substantive propositions, methodological framings, and methods. It has been applied in myriad settings (e.g., libraries, information systems, media systems, web sites, public information campaigns, classrooms, counseling services, and so on), at myriad levels (e.g., intrapersonal, interpersonal, small group, organizational, mass, national, global), and within myriad perspectives (e.g., constructivist, critical, cultural, feminist, postmodern, communitarian). The approach has been developed by Brenda Dervin and is being expanded, transformed, and enriched daily by the efforts of some 100-plus persons worldwide (academics and practitioners, teachers and students). This web site is designed to provide access to these efforts and links to those who are involved. On this site, Sense-Making (capitalized) refers to the methodology; sense-making (not capitalized) refers to the phenomena of making and unmaking of sense.

NKOS is devoted to the discussion of the functional and data model for enabling knowledge organization systems (KOS), such as classification systems, thesauri, gazetteers, and ontologies, as networked interactive information services to support the description and retrieval of diverse information resources through the Internet.

Sensemaking systems don't only help people find stuff faster. That's just the information retrieval part. The bigger story is about augmenting and amplifying our abilities to make sense. Sensemaking adds things like skimming, power reading, organizing, spotting patterns, tracing social networks, taking notes, summarizing, drilling for details, and flagging biases. Reading an article is different from reading a book, and that's different from reading from a collection or stream. Radically new forms of human-information interaction are being enabled by these new technologies. Sensemaking systems not only have front ends (visualization), but also back ends (content analytics and reasoning).

Welcome to ITIS, the Integrated Taxonomic Information System! Here you will find authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world

In this paper an application of methodologies to automatically acquire semantic word classes and to use them in text information retrieval systems is described.

The project KiWi is concerned with knowledge management in Semantic Wikis and funded by the European Commission under the Project Number 211932 in the EU Seventh Framework Programme (FP7). KiWi's objective is to investigate how knowledge management in highly dynamic environments can be supported using Semantic Wiki technologies, and how Semantic Wikis can be improved to satisfy the requirements of knowledge management. For this purpose, KiWi will * implement an advanced knowledge management system based on the Semantic Wiki IkeWiki and extend it by improved, rule-based reasoning support, information extraction, personalisation, and advanced visualisations and editors * verify the system on two use cases in the areas of project knowledge management and software knowledge management, with flexible workflow models and specific support for the respective application areas.

17 November 2008 - The international open standards consortium, OASIS, has formed a new group to standardize a Web services interface specification that will enable greater interoperability of Enterprise Content Management (ECM) systems. The new OASIS Content Management Interoperability Services (CMIS) Technical Committee will advance an open standard that uses Web services and Web 2.0 interfaces to enable information to be shared across Internet protocols in vendor-neutral formats, among document systems, publishers and repositories, within and between companies.

Matching and relating identities is of the utmost importance for Las Vegas casinos. The author describes a specific matching technique known as identity resolution. This approach provides superior results over traditional identity matching systems.

High flair, non academic case for semantic reconciliation and indexing. No tech detail, but clear and useful principles.

This text sets out a series of approaches to the analysis and synthesis of the World Wide Web, and other web-like information structures. A comprehensive set of research questions is outlined, together with a sub-disciplinary breakdown, emphasising the multi-faceted nature of the Web, and the multi-disciplinary nature of its study and development. These questions and approaches together set out an agenda for Web Science, the science of decentralised information systems. Web Science is required both as a way to understand the Web, and as a way to focus its development on key communicational and representational requirements. The text surveys central engineering issues, such as the development of the Semantic Web, Web services and P2P. Analytic approaches to discover the Web's topology, or its graph-like structures, are examined. Finally, the Web as a technology is essentially socially embedded; therefore various issues and requirements for Web use and governance are also reviewed.

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.

CENDI's vision is to provide its member federal STI agencies a cooperative enterprise where capabilities are shared and challenges are faced together so that the sum of accomplishments is greater than each individual agency can achieve on its own. CENDI's mission is to help improve the productivity of federal science- and technology-based programs through effective scientific, technical, and related information-support systems. In fulfilling its mission, CENDI agencies play an important role in addressing science- and technology-based national priorities and strengthening U.S. competitiveness. CENDI is an interagency working group of senior scientific and technical information (STI) managers from 13 U.S. federal agencies