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Source

Politische Meinung. 381(2001) Nr.1, S.65-74 [https%3A%2F%2Fwww.dgfe.de%2Ffileadmin%2FOrdnerRedakteure%2FSektionen%2FSek02_AEW%2FKWF%2FPublikationen_Reihe_1989-2003%2FBand_17%2FBd_17_1994_355-406_A.pdf&usg=AOvVaw2KcbRsHy5UQ9QRIUyuOLNi]

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Abstract

The new term Representation of knowledge, applied to the framework of electronic segments of information, with comprehension of new material support for information, and a review and total conceptualisation of the terminology which is being applied, entails a review of all traditional documentary practices. Therefore, a definition of the concept of Representation of knowledge is indispensable. The term representation has been used in westere cultural and intellectual tradition to refer to the diverse ways that a subject comprehends an object. Representation is a process which requires the structure of natural language and human memory whereby it is interwoven in a subject and in conscience. However, at the present time, the term Representation of knowledge is applied to the processing of electronic information, combined with the aim of emulating the human mind in such a way that one has endeavoured to transfer, with great difficulty, the complex structurality of the conceptual representation of human knowledge to new digital information technologies. Thus, nowadays, representation of knowledge has taken an diverse meanings and it has focussed, for the moment, an certain structures and conceptual hierarchies which carry and transfer information, and has initially been based an the current representation of knowledge using artificial intelligence. The traditional languages of documentation, also referred to as languages of representation, offer a structured representation of conceptual fields, symbols and terms of natural and notational language, and they are the pillars for the necessary correspondence between the object or text and its representation. These correspondences, connections and symbolisations will be established within the electronic framework by means of different models and of the "goal" domain, which will give rise to organisations, structures, maps, networks and levels, as new electronic documents are not compact units but segments of information. Thus, the new representation of knowledge refers to data, images, figures and symbolised, treated, processed and structured ideas which replace or refer to documents within the framework of technical processing and the recuperation of electronic information.

Date

2. 1.2005 18:22:25

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Abstract

This paper suggests a framework and systematic definitions for 6 words commonly used in dthe field of information science: data, information, knowledge, wisdom, inspiration, and intelligence. We intend these definitions to lead to a quantification of information science, a quantification that will enable their measurement, manipulastion, and prediction.

Date

22. 2.2007 18:56:23
22. 2.2007 19:22:13

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Abstract

User problems with large information spaces multiply in complexity when we enter the digital domain. Virtual information environments can offer 3D representations, reconfigurations, and access to large databases that may overwhelm many users' abilities to filter and represent. As a result, user frequently experience disorienting in navigation large digital spaces to locate an duse information. To date, the research response has been predominantly based on the analysis of visual navigational aids that might support users' bottom-up processing of the spatial display. In the present paper, an emerging alternative is considered that places greater emphasis on the top-down application of semantic knowledge by the user gleaned from their experiences within the sociocognitive context of information production and consumption. A distinction between spatial and semantic cues is introduced, and existing empirical data are reviewed that highlight the differential reliance on spatial or semantic information as the domain expertise of the user increases. The conclusion is reached that interfaces for shaping information should be built on an increasing analysis of users' semantic processing

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Abstract

Die moderne Gesellschaft leidet an Reizüberflutung durch Fernsehen, Internet, Zeitschriften aller Art. Jack Meadows, Professor für Bibliotheks- und Informationswissenschaft setzt sich mit Definitionen zu Begriffen wie 'Data', 'Information', 'Communication' oder 'Knowledge' auseinander, die für uns alläglich geworden sind. wie verarbeiten wir den Fluss von wichtigen und unwichtigen Informationen, der täglich auf uns einströmt? Welche 'Daten' sind es für uns Wert, gespeichert zu werden, welche vergessen wir nach kurzer Zeit? Wann wird aus Information Wissen oder gar Weisheit? Das Buch ist eine grundlegende Einführung in das weitläufige Thema Information und Wissensmanagement

Date

15. 6.2002 19:22:01

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Abstract

Survivors of intimate partner violence face more than information gaps; many face powerful barriers in the form of information myths. Triangulating data from in-depth interviews and community bulletin board postings, this study incorporates insights from survivors, police, and shelter staff to begin mapping the information landscape through which survivors move. An unanticipated feature of that landscape is a set of 28 compelling information myths that prevent some survivors from making effective use of the social, legal, economic, and support resources available to them. This analysis of the sources, contexts, and consequences of these information myths is the first step in devising strategies to counter their ill effects.

Date

22. 3.2009 19:16:44

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Abstract

Dem von Uwe Jochum diagnostizierten häufigen Versuch, den modernen mathematisch-nachrichtentechnischen Begriff der Information in die Geschichte zurückzuspiegeln und also alle möglichen Informationsbegriffe als Vorformen und Spielarten desselben auszuweisen, widerstrebt der (sit venia verbo) medienarchäologische Blick, der auf die Diskontinuitäten, die Brüche und Unvereinbarkeiten in der Genealogie des Informationsbegriffs zwischen analogen und digitalen, logischen und mathematischen, philosophischen und nondiskursiven Konzeptionen von Wissen achtet - und vor allem zwischen einer metaphorischen Beschreibung gesellschaftlicher Prozesse und einem medialen Begriff der Übertragung trennt. Eine genaue Lektüre des antiken Wissens-Verständnisses entdeckt in Aristoteles' Schrift Über die Seele tatsächlich den Begriff des "Mediums", des to metaxy als des "Dazwischen". Der ganze Unterschied zwischen aristotelischen und digitalen Medien liegt aber bekanntlich darin, daß im letzteren Zwischenraum tatsächlich etwas geschieht, ein data processing, das nicht länger ausschließlich von der Kognition des Menschen abhängig ist, sondern die Fähigkeit zum feedback besitzt - die begriffliche Alternative zum Wissensbegriff.

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Abstract

Many definitions of information have been suggested throughout the history of information science. In this essay, the objective has been to provide a definition that is usable for the physical, biological and social meanings of the term, covering the various senses important to our field. Information has been defined as the pattern of organization of matter and energy. Information is everywhere except where there is total entropy. Living beings process, organize and ascribe meaning to information. Some pattern of organization that has been given meaning by a living being has been defined as information 2, while the above definition is information 1, when it is desirable to make the distinction. Knowledge has been defined as information given meaning and integrated with other contents of understanding. Meaning itself is rooted ultimately in biological survival. In the human being, extensive processing space in the brain has made possible the generation of extremely rich cultural and interpersonal meaning, which imbues human interactions. (In the short term, not all meaning that humans ascribe to information is the result of evolutionary processes. Our extensive brain processing space also enables us to hold beliefs for the short term that, over the long term, may actually be harmful to survival.) Data 1 has been defined as that portion of the entire information environment (including internal inputs) that is taken in, or processed, by an organism. Data 2 is that information that is selected or generated and used by human beings for research or other social purposes. This definition of information is not reductive--that is, it does not imply that information is all and only the most microscopic physical manifestation of matter and energy. Information principally exists for organisms at many emergent levels. A human being, for example, can see this account as tiny marks on a piece of paper, as letters of the alphabet, as words of the English language, as a sequence of ideas, as a genre of publication, as a philosophical position and so on. Thus, patterns of organization are not all equal in the life experience of animals. Some types of patterns are more important, some less so. Some parts of patterns are repetitive and can be compressed in mental storage. As mental storage space is generally limited and its maintenance costly to an animal, adaptive advantage accrues to the species that develops efficient storage. As a result, many species process elements of their environment in ways efficient and effective for their particular purposes; that is, as patterns of organization that are experienced as emergent wholes. We see a chair as a chair, not only as a pattern of light and dark. We see a string of actions by a salesperson as bait and switch, not just as a sequence of actions. We understand a series of statements as parts of a whole philosophical argument, not just as a series of sentences. The understanding of information embraced here recognizes and builds on the idea that these emergent wholes are efficient for storage and effective for the life purposes of human beings as successful animals (to date) on our planet. Thus, people experience their lives in terms of these emergent objects and relations, for the most part. Likewise, information is stored in retrieval systems in such a way that it can be represented to human beings in their preferred emergent forms, rather than in the pixels or bits in which the information is actually encoded within the information system.

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Abstract

Consider a sentence such as "the current price of tea in China is 35 cents per pound." In a library with millions of books we might find many statements of the above form that we could capture today with relatively simple rules: rather than pursuing every variation of a statement, programs can wait, like predators at a water hole, for their informational prey to reappear in a standard linguistic pattern. We can make inferences from sentences such as "NAME1 born at NAME2 in DATE" that NAME more likely than not represents a person and NAME a place and then convert the statement into a proposition about a person born at a given place and time. The changing price of tea in China, pedestrian birth and death dates, or other basic statements may not be truth and beauty in the Phaedrus, but a digital library that could plot the prices of various commodities in different markets over time, plot the various lifetimes of individuals, or extract and classify many events would be very useful. Services such as the Syllabus Finder1 and H-Bot2 (which Dan Cohen describes elsewhere in this issue of D-Lib) represent examples of information extraction already in use. H-Bot, in particular, builds on our evolving ability to extract information from very large corpora such as the billions of web pages available through the Google API. Aside from identifying higher order statements, however, users also want to search and browse named entities: they want to read about "C. P. E. Bach" rather than his father "Johann Sebastian" or about "Cambridge, Maryland", without hearing about "Cambridge, Massachusetts", Cambridge in the UK or any of the other Cambridges scattered around the world. Named entity identification is a well-established area with an ongoing literature. The Natural Language Processing Research Group at the University of Sheffield has developed its open source Generalized Architecture for Text Engineering (GATE) for years, while IBM's Unstructured Information Analysis and Search (UIMA) is "available as open source software to provide a common foundation for industry and academia." Powerful tools are thus freely available and more demanding users can draw upon published literature to develop their own systems. Major search engines such as Google and Yahoo also integrate increasingly sophisticated tools to categorize and identify places. The software resources are rich and expanding. The reference works on which these systems depend, however, are ill-suited for historical analysis. First, simple gazetteers and similar authority lists quickly grow too big for useful information extraction. They provide us with potential entities against which to match textual references, but existing electronic reference works assume that human readers can use their knowledge of geography and of the immediate context to pick the right Boston from the Bostons in the Getty Thesaurus of Geographic Names (TGN), but, with the crucial exception of geographic location, the TGN records do not provide any machine readable clues: we cannot tell which Bostons are large or small. If we are analyzing a document published in 1818, we cannot filter out those places that did not yet exist or that had different names: "Jefferson Davis" is not the name of a parish in Louisiana (tgn,2000880) or a county in Mississippi (tgn,2001118) until after the Civil War.
Although the Alexandria Digital Library provides far richer data than the TGN (5.9 vs. 1.3 million names), its added size lowers, rather than increases, the accuracy of most geographic name identification systems for historical documents: most of the extra 4.6 million names cover low frequency entities that rarely occur in any particular corpus. The TGN is sufficiently comprehensive to provide quite enough noise: we find place names that are used over and over (there are almost one hundred Washingtons) and semantically ambiguous (e.g., is Washington a person or a place?). Comprehensive knowledge sources emphasize recall but lower precision. We need data with which to determine which "Tribune" or "John Brown" a particular passage denotes. Secondly and paradoxically, our reference works may not be comprehensive enough. Human actors come and go over time. Organizations appear and vanish. Even places can change their names or vanish. The TGN does associate the obsolete name Siam with the nation of Thailand (tgn,1000142) - but also with towns named Siam in Iowa (tgn,2035651), Tennessee (tgn,2101519), and Ohio (tgn,2662003). Prussia appears but as a general region (tgn,7016786), with no indication when or if it was a sovereign nation. And if places do point to the same object over time, that object may have very different significance over time: in the foundational works of Western historiography, Herodotus reminds us that the great cities of the past may be small today, and the small cities of today great tomorrow (Hdt. 1.5), while Thucydides stresses that we cannot estimate the past significance of a place by its appearance today (Thuc. 1.10). In other words, we need to know the population figures for the various Washingtons in 1870 if we are analyzing documents from 1870. The foundations have been laid for reference works that provide machine actionable information about entities at particular times in history. The Alexandria Digital Library Gazetteer Content Standard8 represents a sophisticated framework with which to create such resources: places can be associated with temporal information about their foundation (e.g., Washington, DC, founded on 16 July 1790), changes in names for the same location (e.g., Saint Petersburg to Leningrad and back again), population figures at various times and similar historically contingent data. But if we have the software and the data structures, we do not yet have substantial amounts of historical content such as plentiful digital gazetteers, encyclopedias, lexica, grammars and other reference works to illustrate many periods and, even if we do, those resources may not be in a useful form: raw OCR output of a complex lexicon or gazetteer may have so many errors and have captured so little of the underlying structure that the digital resource is useless as a knowledge base. Put another way, human beings are still much better at reading and interpreting the contents of page images than machines. While people, places, and dates are probably the most important core entities, we will find a growing set of objects that we need to identify and track across collections, and each of these categories of objects will require its own knowledge sources. The following section enumerates and briefly describes some existing categories of documents that we need to mine for knowledge. This brief survey focuses on the format of print sources (e.g., highly structured textual "database" vs. unstructured text) to illustrate some of the challenges involved in converting our published knowledge into semantically annotated, machine actionable form.

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Abstract

Many competing definitions for the terms data, information, metadata, and knowledge can be traced in the library and information science literature. The lack of a clear consensus in the way reference is made to the corresponding fundamental concepts is intensified if one considers additional disciplinary perspectives, e.g. database technology, data mining, etc. In the present paper, we use a common sense approach, to selectively survey the literature, and define these terms in a way that can advance the interdisciplinary development of information systems.

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Abstract

1957 hat Karl Steinbuch mit seinem Mitarbeiter Helmut Gröttrup den Begriff "Informatik" erfunden. Er gebrauchte diesen Begriff nicht zur Bezeichnung eines wissenschaftlichen Fachgebiets, sondern eher für seine Abteilung bei der Firma SEL in Stuttgart. Zu dieser Zeit standen sich in diesem Feld drei Parteien gegenüber: Die Mathematiker, die mit Rechenanlagen elektronisch rechneten, die Elektrotechniker, die Nachrichtenverarbeitung trieben und die Wirtschaftler und Lochkartenleute, die mit mechanisch-elektronischen Geräten zählten, buchten und aufsummierten. Während sich in den USA und England die Mathematiker mit dem Namen für das Gerät "Computer" durchsetzten und die Wissenschaft pragmatisch "Computer Science" genannt wurde, war in Deutschland die Diskussion bis in die 60er Jahre unentschieden: Die Abkürzung EDV hält sich noch immer gegenüber "Rechner" und "Computer"; Steinbuch selbst nannte 1962 sein Taschenbuch nicht "Taschenbuch der Informatik" sondern "Taschenbuch der Nachrichtenverarbeitung". 1955 wurde eine Informatik-Tagung in Darmstadt noch "Elektronische Rechenanlagen und Informationsverarbeitung" genannt. Die Internationale Gesellschaft hieß "International Federation for Information Processing". 1957 aber definierte Steinbuch "Informatik" als "Automatische Informationsverarbeitung" und war auf diese Art den Mathematikern entgegengegangen. Als Firmenbezeichnung schien der Begriff geschützt zu sein. Noch 1967 wurde der Fachbeirat der Bundesregierung "für Datenverarbeitung" genannt. Erst als die Franzosen die Bezeichnung "Informatique" verwendeten, war der Weg frei für die Übernahme. So wurde der Ausschuss des Fachbeirats zur Etablierung des Hochschulstudiums bereits der "Einführung von Informatik-Studiengängen" gewidmet. Man überzeugte den damaligen Forschungsminister Stoltenberg und dieser machte in einer Rede den Begriff "Informatik" publik. Ende der 60er Jahre übernahmen F. L. Bauer und andere den Begriff, nannten 1969 die Berufsgenossenschaft "Gesellschaft für Informatik" und sorgten für die entsprechende Benennung des wissenschaftlichen Fachgebiets. Die strittigen Grundbegriffe dieses Prozesses: Information/Informationen, Nachrichten und Daten scheinen heute nur Nuancen zu trennen. Damals ging es natürlich auch um Politik, um Forschungsrichtungen, um den Geist der Wissenschaft, um die Ausrichtung. Mehr Mathematik, mehr Ingenieurwissenschaft oder mehr Betriebswirtschaft, so könnte man die Grundströmungen vereinfachen. Mit der Ausrichtung der Informatik nicht versöhnte Elektrotechniker nannten sich Informationstechniker, die Datenverarbeiter sammelten sich im Lager der Wirtschaftsinformatiker. Mit den Grundbegriffen der Informatik, Nachricht, Information, Datum, hat es seitdem umfangreiche Auseinandersetzungen gegeben. Lehrbücher mussten geschrieben werden, Lexika und Nachschlagewerke wurden verfasst, Arbeitsgruppen tagten. Die Arbeiten C. Shannons zur Kommunikation, mit denen eine statistische Informationstheorie eingeführt worden war, spielten dabei nur eine geringe Rolle.

Date

5. 4.2013 10:22:48

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Date

17. 7.1996 9:33:22
22. 7.2000 19:05:41

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Abstract

The field of Information Science is constantly changing. Therefore, information scientists are required to regularly review-and if necessary-redefine its fundamental building blocks. This article is one of a group of four articles, which resulted from a Critical Delphi study conducted in 2003-2005. The study, "Knowledge Map of Information Science," was aimed at exploring the foundations of information science. The international panel was composed of 57 leading scholars from 16 countries, who represent (almost) all the major subfields and important aspects of the field. This particular article documents 130 definitions of data, information, and knowledge formulated by 45 scholars, and maps the major conceptual approaches for defining these three key concepts.

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Date

13. 7.2008 19:22:28

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Date

22. 7.2000 19:05:18

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Abstract

Purpose - This philosophical essay aims to explore the concept of information science. Design/methodology/approach - The philosophical argumentation is composed of five phases. It is based on clarifying the meanings of its basic concept "data", "information" and "knowledge". Findings - The study suggests that the name of the field "information science" should be changed to "knowledge science". Originality/value - The paper offers reflections on the explored phenomena of information science.

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Date

22. 7.2000 19:05:31

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Date

22. 6.2000 13:33:40

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Date

17. 7.1996 9:33:22

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Content

Enthält die Beiträge: RAUCH, W.: Neue Informations-Horizonte? VÖLZ, H.: Gedanken zut Verdaulichkeit von Informationen; RATZEK, W.: Suum cuique - Jedem das Seine! Oder: Was wollen wir wissen; VOWE, G.: Das Internet als elektronische Agora? Zum politischen Potential internetbasierter Kommunikation; GRUDOWSKI, S.: Ideen zur Förderung der Fachinformations-Institutionen durch Fachinformationspolitik: Hyperinformationszentren und Informationswissenschaft; ZIMMERMANN, H.H.: Zur Gestaltung eines Internet-Portals als offenes Autor-zentriertes Kommunikationssystem; HENNINGS, R.-D.: Machine Learning, Data Mining and Knowledge Discovery: Von der Generierung zur Entdeckung von Wissen