How to organize your EndNote library By Sarah Tanksalvala EndNote includes a number of functions to help organize your sources and find exactly what you want when you want it. Properly organizing a large number of sources can save you hours of work and frustration. Here are five ways to organize your EndNote libraries, along with tips to use them more efficiently: 1) Smart Groups: Smart groups let you automatically sort your sources by select criteria. Expert tip: When auto-importing files, use smart groups to sort your sources before you ever read them. 2) Group Sets: Whether you’ve manually created your groups or created a smart group, you can combine groups either by creating a new group from smaller ones, or by creating a group set. Expert tip: Create very specific groups and then combine them under broader group sets so you can target precise references when you’re looking for something, or general groups for browsing. 4) Tagging and comments: Add comments and tags to any source and then use those for searches later.
Knowledge representation and reasoning Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) devoted to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets. Overview[edit] Knowledge-representation is the field of artificial intelligence that focuses on designing computer representations that capture information about the world that can be used to solve complex problems. This hypothesis was not always taken as a given by researchers. History[edit] Characteristics[edit]
What Is Programme Management? Traditional Project Management approaches tend to look at a project as a discrete entity having its own set of resources (the budget and project team) and producing its own set of deliverables that deliver benefit to the organisation. In a complex organisation such as a college or university rarely is any project completely self-contained. Even a relatively simple IT application is likely to require interfaces to other systems and most of our activities impact on a diverse range of stakeholder groups. Large organisations such as ours also tend to have hundreds of individual projects running at the same time and many find themselves at the mercy of inter-departmental competition for resources. This infoKit assumes you are familiar with the terms and concepts in our Project Management infoKit. At its simplest Programme Management can be defined as A group of projects managed together for added benefitTurner (1999) The additional benefits might include: Projects Versus Programmes MSP website
Ripple-down rules Ripple-down rules (RDR) are a way of approaching knowledge acquisition. Knowledge acquisition refers to the transfer of knowledge from human experts to knowledge-based systems. Introductory material[edit] Ripple-down rules are an incremental approach to knowledge acquisition and covers a family of techniques. In the RDR framework, the human expert's knowledge is acquired based on the current context and is added incrementally. Methodology[edit] Ripple-down rules consist of a data structure and knowledge acquisition scenarios. Data structure[edit] There are various structures of ripple-down rules, for example single-classification ripple-down rules (SCRDR), multiple-classification ripple-down rules (MCRDR), nested ripple-down rules (NRDR) and repeat-inference multiple-classification ripple-down rules (RIMCRDR). The data structure is similar to a decision tree. An example of SCRDR tree (defined recursively) is shown below: where Child-1 and Child-2 are also SCRDR trees. Implementations[edit]
Knowledge Management - Systems and Processes, 2 edition - The Largest Open Book Storage on PDFTorrents.eu Technical Details Vote for Torrent Health Trackers Knowledge Management - Systems and Processes, 2 edition Details: Knowledge Management: Systems and Processes, 2 editionEnglish | 2014 | ISBN: 0765639157 | 382 pages | PDF | 3 MB This text serves as a complete introduction to the subject of knowledge management, incorporating technical, and social aspects of knowledge management, as well as practical examples, traditional approaches, and emerging topics.
Knowledge base A knowledge base (KB) is a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in connection with expert systems which were the first knowledge-based systems. The original use of the term knowledge-base was to describe one of the two sub-systems of a knowledge-based system. A knowledge-based system consists of a knowledge-base that represents facts about the world and an inference engine that can reason about those facts and use rules and other forms of logic to deduce new facts or highlight inconsistencies.[1] The term 'knowledge-base' was to distinguish from the more common widely used term database. At the time (the 1970s) virtually all large Management Information Systems stored their data in some type of hierarchical or relational database. Flat data. Early expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data. See also[edit]
Kinship Web of human social relationships In anthropology, kinship is the web of social relationships that form an important part of the lives of all humans in all societies, although its exact meanings even within this discipline are often debated. Anthropologist Robin Fox says that the study of kinship is the study of what humans do with these basic facts of life – mating, gestation, parenthood, socialization, siblingship etc. Broadly, kinship patterns may be considered to include people related by both descent – i.e. social relations during development – and by marriage. Kinship can also refer to a principle by which individuals or groups of individuals are organized into social groups, roles, categories and genealogy by means of kinship terminologies. In biology, "kinship" typically refers to the degree of genetic relatedness or the coefficient of relationship between individual members of a species (e.g. as in kin selection theory). Basic concepts[edit] Family types[edit] Terminology[edit]
Quality System - Quality Management Plans A Quality Management Plan documents how an organization will plan, implement, and assess the effectiveness of its quality assurance and quality control operations. Specifically, it describes how an organization structures its quality system, the quality policies and procedures, areas of application, and roles, responsibilities, and authorities. The elements of a quality system are documented in a Quality Management Plan. Both EPA organizations and organizations performing data collection activities funded by EPA are required to document their quality systems. The Quality Management Plan is an organization or program-specific document; it describes the general practices of an organization or program. Project-specific details of individual projects of the organization or program are documented in a Quality Assurance Project Plan (see QA Project Plans). References Training Introduction to Quality Management Plans. Examples and Other On-line Resources
Cynefin framework Decision-making framework The Cynefin framework ( kuh-NEV-in)[1] is a conceptual framework used to aid decision-making.[2] Created in 1999 by Dave Snowden when he worked for IBM Global Services, it has been described as a "sense-making device".[3][4] Cynefin is a Welsh word for 'habitat'.[5] Background[edit] Terminology[edit] The idea of the Cynefin framework is that it offers decision-makers a "sense of place" from which to view their perceptions.[8] Cynefin is a Welsh word meaning 'habitat', 'haunt', 'acquainted', 'familiar'. History[edit] The Cynefin Centre—a network of members and partners from industry, government and academia—began operating independently of IBM in 2004.[18] In 2007 Snowden and Mary E. Domains[edit] Cynefin offers five decision-making contexts or "domains": clear, complicated, complex, chaotic, and a centre of confusion. Clear[edit] The clear domain represents the "known knowns". Complicated[edit] Complex[edit] The complex domain represents the "unknown unknowns".
Knowledge Management Definition Based on the discussion in the previous section, my knowledge management definition is as follows: Knowledge management is the systematic management of an organization's knowledge assets for the purpose of creating value and meeting tactical & strategic requirements; it consists of the initiatives, processes, strategies, and systems that sustain and enhance the storage, assessment, sharing, refinement, and creation of knowledge. Knowledge management (KM) therefore implies a strong tie to organizational goals and strategy, and it involves the management of knowledge that is useful for some purpose and which creates value for the organization. Expanding upon the previous knowledge management definition, KM involves the understanding of: From this knowledge management definition we can see that it depends upon the management of the organization's knowledge creation and conversion mechanisms; organizational memory and retrieval facilities; organizational learning; and organizational culture.
Tutorial 4: Introducing RDFS & OWL Next: Querying Semantic Data Having introduced the advantages of modeling vocabulary and semantics in data models, let's introduce the actual technology used to attribute RDF data models with semantics. RDF data can be encoded with semantic metadata using two syntaxes: RDFS and OWL. After this tutorial, you should be able to: Understand how RDF data models are semantically encoded using RDFS and OWLUnderstand that OWL ontologies are RDF documentsUnderstand OWL classes, subclasses and individualsUnderstand OWL propertiesBuild your own basic ontology, step by stepEstimated time: 5 minutes You should have already understood the following tutorial (and pre-requisites) before you begin: Tutorial 3: Semantic Modeling In the last lesson, we compared some of the more popular traditional forms of modeling data with the semantic model, and then introduced a situation where data sharing was enhanced and made significantly easier by using a semantic web approach. 4.1 A Starting Example 01. 08. 09. 10. 11.
Kynapse Kynapse is the artificial intelligence middleware product, developed by Kynogon, which was bought by Autodesk in 2008 and called Autodesk Kynapse. In 2011, it has been re-engineered and rebranded Autodesk Navigation[3]. Features[edit] Usage[edit] References[edit] External links[edit] Official website