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Abstract

Aufgrund der so großen Bedeutung von Privatheit im Internet hat acatech, die Deutsche Akademie der Technikwissenschaften, 2011 ein Projekt initiiert, das sich mit dem Privatheitsparadoxon wissenschaftlich auseinandersetzt. In dem Projekt werden Empfehlungen entwickelt, wie sich eine Kultur der Privatheit und des Vertrauens im Internet etablieren lässt, die es ermöglicht, das Paradoxon aufzulösen. Wir verwenden hier den Begriff der Privatheit. Er deutet an, dass hier nicht nur der räumliche Begriff Privatsphäre gemeint ist, sondern auch das im europäischen Kontext wichtige Konzept der informationellen Selbstbestimmung einbezogen ist. Dieser Band legt die Ergebnisse der ersten Projektphase vor: eine Bestandsaufnahme von Privatheit im Internet aus verschiedenen Blickwinkeln. Kapitel 1 stellt die Wünsche und Befürchtungen von Internetnutzern und Gesellschaft im Hinblick auf ihre Privatheit vor. Sie wurden mithilfe sozialwissenschaftlicher Methoden untersucht. Ergänzend dazu untersucht das zweite Kapitel Privatheit im Cyberspace aus ethischer Perspektive. Das dritte Kapitel widmet sich ökonomischen Aspekten: Da viele Onlinedienstleistungen mit Nutzerdaten bezahlt werden, ergibt sich die Frage, was dies sowohl für den Nutzer und Kunden als auch für die Unternehmen bedeutet. Kapitel 4 hat einen technologischen Fokus und analysiert, wie Privatheit von Internettechnologien bedroht wird und welche technischen Möglichkeiten es gibt, um die Privatheit des Nutzers zu schützen. Selbstverständlich ist der Schutz von Privatheit im Internet nicht nur ein technisches Problem. Deshalb untersucht Kapitel 5 Privatheit aus rechtlicher Sicht. Bei der Lektüre der fünf Kapitel wird dem Leser sofort die Komplexität der Frage von Privatheit im Internet (Internet Privacy) bewusst. Daraus folgt die unbedingte Notwendigkeit eines interdisziplinären Ansatzes. In diesem Sinne wird die interdisziplinäre Projektgruppe gemeinsam Optionen und Empfehlungen für einen Umgang mit Privatheit im Internet entwickeln, die eine Kultur der Privatheit und des Vertrauens im Internet fördern. Diese Optionen und Empfehlungen werden 2013 als zweiter Band dieser Studie veröffentlicht.

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Date

23. 1.2022 10:22:18

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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.