3LConOnt: a three-level ontology for context modelling in context-aware computing
Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposal...
Ausführliche Beschreibung
Autor*in: |
Cabrera, Oscar [verfasserIn] Franch, Xavier [verfasserIn] Marco, Jordi [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2017 |
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Übergeordnetes Werk: |
Enthalten in: Software and systems modeling - Berlin : Springer, 2002, 18(2017), 2 vom: 16. Aug., Seite 1345-1378 |
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Übergeordnetes Werk: |
volume:18 ; year:2017 ; number:2 ; day:16 ; month:08 ; pages:1345-1378 |
Links: |
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DOI / URN: |
10.1007/s10270-017-0611-z |
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Katalog-ID: |
SPR009315667 |
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520 | |a Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. | ||
650 | 4 | |a Context-aware computing |7 (dpeaa)DE-He213 | |
650 | 4 | |a Service-oriented computing |7 (dpeaa)DE-He213 | |
650 | 4 | |a Context life cycle |7 (dpeaa)DE-He213 | |
650 | 4 | |a Context modelling |7 (dpeaa)DE-He213 | |
650 | 4 | |a Context reasoning |7 (dpeaa)DE-He213 | |
650 | 4 | |a Context ontology |7 (dpeaa)DE-He213 | |
700 | 1 | |a Franch, Xavier |e verfasserin |4 aut | |
700 | 1 | |a Marco, Jordi |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Software and systems modeling |d Berlin : Springer, 2002 |g 18(2017), 2 vom: 16. Aug., Seite 1345-1378 |w (DE-627)355691426 |w (DE-600)2090971-8 |x 1619-1374 |7 nnns |
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10.1007/s10270-017-0611-z doi (DE-627)SPR009315667 (SPR)s10270-017-0611-z-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 54.50 bkl Cabrera, Oscar verfasserin aut 3LConOnt: a three-level ontology for context modelling in context-aware computing 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 Franch, Xavier verfasserin aut Marco, Jordi verfasserin aut Enthalten in Software and systems modeling Berlin : Springer, 2002 18(2017), 2 vom: 16. Aug., Seite 1345-1378 (DE-627)355691426 (DE-600)2090971-8 1619-1374 nnns volume:18 year:2017 number:2 day:16 month:08 pages:1345-1378 https://dx.doi.org/10.1007/s10270-017-0611-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.50 ASE AR 18 2017 2 16 08 1345-1378 |
spelling |
10.1007/s10270-017-0611-z doi (DE-627)SPR009315667 (SPR)s10270-017-0611-z-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 54.50 bkl Cabrera, Oscar verfasserin aut 3LConOnt: a three-level ontology for context modelling in context-aware computing 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 Franch, Xavier verfasserin aut Marco, Jordi verfasserin aut Enthalten in Software and systems modeling Berlin : Springer, 2002 18(2017), 2 vom: 16. Aug., Seite 1345-1378 (DE-627)355691426 (DE-600)2090971-8 1619-1374 nnns volume:18 year:2017 number:2 day:16 month:08 pages:1345-1378 https://dx.doi.org/10.1007/s10270-017-0611-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.50 ASE AR 18 2017 2 16 08 1345-1378 |
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10.1007/s10270-017-0611-z doi (DE-627)SPR009315667 (SPR)s10270-017-0611-z-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 54.50 bkl Cabrera, Oscar verfasserin aut 3LConOnt: a three-level ontology for context modelling in context-aware computing 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 Franch, Xavier verfasserin aut Marco, Jordi verfasserin aut Enthalten in Software and systems modeling Berlin : Springer, 2002 18(2017), 2 vom: 16. Aug., Seite 1345-1378 (DE-627)355691426 (DE-600)2090971-8 1619-1374 nnns volume:18 year:2017 number:2 day:16 month:08 pages:1345-1378 https://dx.doi.org/10.1007/s10270-017-0611-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.50 ASE AR 18 2017 2 16 08 1345-1378 |
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10.1007/s10270-017-0611-z doi (DE-627)SPR009315667 (SPR)s10270-017-0611-z-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 54.50 bkl Cabrera, Oscar verfasserin aut 3LConOnt: a three-level ontology for context modelling in context-aware computing 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 Franch, Xavier verfasserin aut Marco, Jordi verfasserin aut Enthalten in Software and systems modeling Berlin : Springer, 2002 18(2017), 2 vom: 16. Aug., Seite 1345-1378 (DE-627)355691426 (DE-600)2090971-8 1619-1374 nnns volume:18 year:2017 number:2 day:16 month:08 pages:1345-1378 https://dx.doi.org/10.1007/s10270-017-0611-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.50 ASE AR 18 2017 2 16 08 1345-1378 |
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10.1007/s10270-017-0611-z doi (DE-627)SPR009315667 (SPR)s10270-017-0611-z-e DE-627 ger DE-627 rakwb eng 004 ASE 004 ASE 54.50 bkl Cabrera, Oscar verfasserin aut 3LConOnt: a three-level ontology for context modelling in context-aware computing 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 Franch, Xavier verfasserin aut Marco, Jordi verfasserin aut Enthalten in Software and systems modeling Berlin : Springer, 2002 18(2017), 2 vom: 16. Aug., Seite 1345-1378 (DE-627)355691426 (DE-600)2090971-8 1619-1374 nnns volume:18 year:2017 number:2 day:16 month:08 pages:1345-1378 https://dx.doi.org/10.1007/s10270-017-0611-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.50 ASE AR 18 2017 2 16 08 1345-1378 |
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Cabrera, Oscar @@aut@@ Franch, Xavier @@aut@@ Marco, Jordi @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR009315667</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110210656.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10270-017-0611-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR009315667</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10270-017-0611-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.50</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cabrera, Oscar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">3LConOnt: a three-level ontology for context modelling in context-aware computing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Context-aware computing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Service-oriented computing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Context life cycle</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Context modelling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Context reasoning</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Context ontology</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Franch, Xavier</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Marco, Jordi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Software and systems modeling</subfield><subfield code="d">Berlin : Springer, 2002</subfield><subfield code="g">18(2017), 2 vom: 16. 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Cabrera, Oscar |
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Cabrera, Oscar ddc 004 bkl 54.50 misc Context-aware computing misc Service-oriented computing misc Context life cycle misc Context modelling misc Context reasoning misc Context ontology 3LConOnt: a three-level ontology for context modelling in context-aware computing |
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004 ASE 54.50 bkl 3LConOnt: a three-level ontology for context modelling in context-aware computing Context-aware computing (dpeaa)DE-He213 Service-oriented computing (dpeaa)DE-He213 Context life cycle (dpeaa)DE-He213 Context modelling (dpeaa)DE-He213 Context reasoning (dpeaa)DE-He213 Context ontology (dpeaa)DE-He213 |
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ddc 004 bkl 54.50 misc Context-aware computing misc Service-oriented computing misc Context life cycle misc Context modelling misc Context reasoning misc Context ontology |
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ddc 004 bkl 54.50 misc Context-aware computing misc Service-oriented computing misc Context life cycle misc Context modelling misc Context reasoning misc Context ontology |
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3lconont: a three-level ontology for context modelling in context-aware computing |
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3LConOnt: a three-level ontology for context modelling in context-aware computing |
abstract |
Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. |
abstractGer |
Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. |
abstract_unstemmed |
Abstract Context-aware computing is the ability of Services and applications to adapt and react to context changes. Context modelling is a core feature of context-aware computing. Although a lot of research has been made in the field of context modelling, most of the context-aware computing proposals prefer to design their own customized context model instead of reusing an existing one. The main reason for this behaviour is that current context models present some problems concerning reusability, extensibility and adaptation. To contribute solving these issues, in this paper we present 3LConOnt, a three-level context ontology that can be easily reused, extended and adapted for specific or generic purposes. The proposed context model consolidates the context knowledge already available from a modular perspective yielding a clear schema of knowledge reutilization. To do so, we gathered context knowledge pieces from different ontologies to be integrated into standardized and well-defined levels of abstraction and modules. The proposal has been validated considering: (1) reusability, extensibility and adaptation by instantiating different smart scenarios; (2) consistency and reasoning by triggering queries to the proposed model based on some competence questions; and (3) reusability in existing ontologies by importing the needed module or level of the model. Additionally, we also illustrate its usability in context-aware Services by modelling a context-aware framework architecture for supporting the whole context life cycle: acquisition, modelling, reasoning and distribution. |
collection_details |
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container_issue |
2 |
title_short |
3LConOnt: a three-level ontology for context modelling in context-aware computing |
url |
https://dx.doi.org/10.1007/s10270-017-0611-z |
remote_bool |
true |
author2 |
Franch, Xavier Marco, Jordi |
author2Str |
Franch, Xavier Marco, Jordi |
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doi_str |
10.1007/s10270-017-0611-z |
up_date |
2024-07-04T01:34:43.718Z |
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|
score |
7.400526 |