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020 _a9783031794414
_9978-3-031-79441-4
024 7 _a10.1007/978-3-031-79441-4
_2doi
050 4 _aQA1-939
072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
072 7 _aPB
_2thema
082 0 4 _a510
_223
100 1 _aSimperl, Elena.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981828
245 1 0 _aIncentive-Centric Semantic Web Application Engineering
_h[electronic resource] /
_cby Elena Simperl, Roberta Cuel, Martin Stein.
250 _a1st ed. 2013.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2013.
300 _aXII, 105 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Data, Semantics, and Knowledge,
_x2691-2031
505 0 _aSemantic Data Management: A Human-driven Process -- Fundamentals of Motivation and Incentives -- Case Study: Motivating Employees to Annotate Content -- Case Study: Building a Community of Practice Around Web Service Management and Annotation -- Case Study: Games with a Purpose for Semantic Content Creation -- Conclusions.
520 _aWhile many Web 2.0-inspired approaches to semantic content authoring do acknowledge motivation and incentives as the main drivers of user involvement, the amount of useful human contributions actually available will always remain a scarce resource. Complementarily, there are aspects of semantic content authoring in which automatic techniques have proven to perform reliably, and the added value of human (and collective) intelligence is often a question of cost and timing. The challenge that this book attempts to tackle is how these two approaches (machine- and human-driven computation) could be combined in order to improve the cost-performance ratio of creating, managing, and meaningfully using semantic content. To do so, we need to first understand how theories and practices from social sciences and economics about user behavior and incentives could be applied to semantic content authoring. We will introduce a methodology to help software designers to embed incentives-minded functionalities into semantic applications, as well as best practices and guidelines. We will present several examples of such applications, addressing tasks such as ontology management, media annotation, and information extraction, which have been built with these considerations in mind. These examples illustrate key design issues of incentivized Semantic Web applications that might have a significant effect on the success and sustainable development of the applications: the suitability of the task and knowledge domain to the intended audience, and the mechanisms set up to ensure high-quality contributions, and extensive user involvement. Table of Contents: Semantic Data Management: A Human-driven Process / Fundamentals of Motivation and Incentives / Case Study: Motivating Employees to Annotate Content / Case Study: Building a Community of Practice Around Web Service Management and Annotation / Case Study: Games with a Purpose for Semantic Content Creation / Conclusions.
650 0 _aMathematics.
_911584
650 0 _aInternet programming.
_935503
650 0 _aApplication software.
_981829
650 0 _aComputer networks .
_931572
650 0 _aOntology.
_95277
650 1 4 _aMathematics.
_911584
650 2 4 _aWeb Development.
_935505
650 2 4 _aComputer and Information Systems Applications.
_981830
650 2 4 _aComputer Communication Networks.
_981831
650 2 4 _aOntology.
_95277
700 1 _aCuel, Roberta.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981832
700 1 _aStein, Martin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981833
710 2 _aSpringerLink (Online service)
_981834
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031794407
776 0 8 _iPrinted edition:
_z9783031794421
830 0 _aSynthesis Lectures on Data, Semantics, and Knowledge,
_x2691-2031
_981835
856 4 0 _uhttps://doi.org/10.1007/978-3-031-79441-4
912 _aZDB-2-SXSC
942 _cEBK
999 _c85257
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