A Collaborative Video Annotation System Based on Semantic Web Technologies View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-12

AUTHORS

Marco Grassi, Christian Morbidoni, Michele Nucci

ABSTRACT

In recent years, videos have become more and more a familiar multimedia format for common users. In particular, the advent of Web 2.0 and the spreading of video-sharing services over the Web have led to an explosion of online video content. The capability to provide broader support in accessing and exploring video content, and in general other kind of multimedia formats as images and documents, is becoming more and more important. In this context, the value of semantically structured data and metadata is recognized as a key factor both to improve search efficiency and to guarantee data interoperability. This latter aspect is critical to connect different, heterogeneous content coming from a variety of data sources. On the other hand, the annotation of video resources has been increasingly understood as a medium factor to enable deep analysis of contents and collaborative study of online digital objects. However, as existing annotation tools provide poor support for semantically structured content or in some cases express the semantics in proprietary and non-interoperable formats, such knowledge that users build by carefully annotating contents hardly crosses the boundaries of a single system and often cannot be reused by different communities (e.g., to classify content or to discover new relations among resources). In this paper, a novel Semantic Web-based annotation system is presented that enables user annotations to form semantically structured knowledge at different levels of granularity and complexity. Annotation can be reused by external applications and mixed with Web of Data sources to enable “serendipity,” the reuse of data produced for a specific task (annotation) by different people and in different contexts from the one data originated from. The main ideas behind the approach are to build on ontologies and support linking, at data level, to precise thesauri and vocabularies, as well as to the Linked Open Data cloud. By describing the software model, developed in the context of SemLib EU project, and by providing an implementation of an online video annotation tool, the main aim of this paper is to demonstrate how such technologies can enable a scenario where users annotations are created while browsing the Web, naturally shared among users, stored in machine readable format and then possibly recombined with external data and ontologies to enhance end-user experience. More... »

PAGES

497-514

References to SciGraph publications

  • 2006. M-OntoMat-Annotizer: Image Annotation Linking Ontologies and Multimedia Low-Level Features in KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS
  • 2011. Towards Semantic Multimodal Video Annotation in TOWARD AUTONOMOUS, ADAPTIVE, AND CONTEXT-AWARE MULTIMODAL INTERFACES. THEORETICAL AND PRACTICAL ISSUES
  • 2011-09. Sentic Web: A New Paradigm for Managing Social Media Affective Information in COGNITIVE COMPUTATION
  • 2011. A Survey of Semantic Image and Video Annotation Tools in KNOWLEDGE-DRIVEN MULTIMEDIA INFORMATION EXTRACTION AND ONTOLOGY EVOLUTION
  • 2011. Semantic Web Techniques Application for Video Fragment Annotation and Management in ANALYSIS OF VERBAL AND NONVERBAL COMMUNICATION AND ENACTMENT. THE PROCESSING ISSUES
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12559-012-9172-1

    DOI

    http://dx.doi.org/10.1007/s12559-012-9172-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1051237471


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information Systems", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Marche Polytechnic University", 
              "id": "https://www.grid.ac/institutes/grid.7010.6", 
              "name": [
                "Semedia (Semantic Web and Multimedia), Polytechnic University of Marche, Via Brecce Bianche I, 60131, Ancona, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Grassi", 
            "givenName": "Marco", 
            "id": "sg:person.012254550647.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012254550647.94"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Marche Polytechnic University", 
              "id": "https://www.grid.ac/institutes/grid.7010.6", 
              "name": [
                "Semedia (Semantic Web and Multimedia), Polytechnic University of Marche, Via Brecce Bianche I, 60131, Ancona, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Morbidoni", 
            "givenName": "Christian", 
            "id": "sg:person.016277275261.20", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016277275261.20"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Marche Polytechnic University", 
              "id": "https://www.grid.ac/institutes/grid.7010.6", 
              "name": [
                "Semedia (Semantic Web and Multimedia), Polytechnic University of Marche, Via Brecce Bianche I, 60131, Ancona, Italy"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Nucci", 
            "givenName": "Michele", 
            "id": "sg:person.015207055165.13", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015207055165.13"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.websem.2009.07.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011160236"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12559-011-9101-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012153753", 
              "https://doi.org/10.1007/s12559-011-9101-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1839707.1839757", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012792698"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/371920.372166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018835628"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11893011_80", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023287280", 
              "https://doi.org/10.1007/11893011_80"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11893011_80", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023287280", 
              "https://doi.org/10.1007/11893011_80"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1873951.1874305", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032534743"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-20795-2_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036366018", 
              "https://doi.org/10.1007/978-3-642-20795-2_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-20795-2_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036366018", 
              "https://doi.org/10.1007/978-3-642-20795-2_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-18184-9_25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046660846", 
              "https://doi.org/10.1007/978-3-642-18184-9_25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-18184-9_25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046660846", 
              "https://doi.org/10.1007/978-3-642-18184-9_25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-25775-9_9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049185396", 
              "https://doi.org/10.1007/978-3-642-25775-9_9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tsmcc.2011.2109710", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061798320"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/mmse.2004.58", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094287004"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2012-12", 
        "datePublishedReg": "2012-12-01", 
        "description": "In recent years, videos have become more and more a familiar multimedia format for common users. In particular, the advent of Web 2.0 and the spreading of video-sharing services over the Web have led to an explosion of online video content. The capability to provide broader support in accessing and exploring video content, and in general other kind of multimedia formats as images and documents, is becoming more and more important. In this context, the value of semantically structured data and metadata is recognized as a key factor both to improve search efficiency and to guarantee data interoperability. This latter aspect is critical to connect different, heterogeneous content coming from a variety of data sources. On the other hand, the annotation of video resources has been increasingly understood as a medium factor to enable deep analysis of contents and collaborative study of online digital objects. However, as existing annotation tools provide poor support for semantically structured content or in some cases express the semantics in proprietary and non-interoperable formats, such knowledge that users build by carefully annotating contents hardly crosses the boundaries of a single system and often cannot be reused by different communities (e.g., to classify content or to discover new relations among resources). In this paper, a novel Semantic Web-based annotation system is presented that enables user annotations to form semantically structured knowledge at different levels of granularity and complexity. Annotation can be reused by external applications and mixed with Web of Data sources to enable \u201cserendipity,\u201d the reuse of data produced for a specific task (annotation) by different people and in different contexts from the one data originated from. The main ideas behind the approach are to build on ontologies and support linking, at data level, to precise thesauri and vocabularies, as well as to the Linked Open Data cloud. By describing the software model, developed in the context of SemLib EU project, and by providing an implementation of an online video annotation tool, the main aim of this paper is to demonstrate how such technologies can enable a scenario where users annotations are created while browsing the Web, naturally shared among users, stored in machine readable format and then possibly recombined with external data and ontologies to enhance end-user experience.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s12559-012-9172-1", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.3788078", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1041199", 
            "issn": [
              "1866-9956", 
              "1866-9964"
            ], 
            "name": "Cognitive Computation", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "4", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "4"
          }
        ], 
        "name": "A Collaborative Video Annotation System Based on Semantic Web Technologies", 
        "pagination": "497-514", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "f41303ee27a0402564395915794d99496b1fff211c80a6f81b7d1086461c5ce7"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s12559-012-9172-1"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1051237471"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s12559-012-9172-1", 
          "https://app.dimensions.ai/details/publication/pub.1051237471"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T16:45", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8669_00000524.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs12559-012-9172-1"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12559-012-9172-1'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12559-012-9172-1'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12559-012-9172-1'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12559-012-9172-1'


     

    This table displays all metadata directly associated to this object as RDF triples.

    115 TRIPLES      21 PREDICATES      38 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s12559-012-9172-1 schema:about anzsrc-for:08
    2 anzsrc-for:0806
    3 schema:author N990476d4efe04b31a623a443bf26fda8
    4 schema:citation sg:pub.10.1007/11893011_80
    5 sg:pub.10.1007/978-3-642-18184-9_25
    6 sg:pub.10.1007/978-3-642-20795-2_8
    7 sg:pub.10.1007/978-3-642-25775-9_9
    8 sg:pub.10.1007/s12559-011-9101-8
    9 https://doi.org/10.1016/j.websem.2009.07.002
    10 https://doi.org/10.1109/mmse.2004.58
    11 https://doi.org/10.1109/tsmcc.2011.2109710
    12 https://doi.org/10.1145/1839707.1839757
    13 https://doi.org/10.1145/1873951.1874305
    14 https://doi.org/10.1145/371920.372166
    15 schema:datePublished 2012-12
    16 schema:datePublishedReg 2012-12-01
    17 schema:description In recent years, videos have become more and more a familiar multimedia format for common users. In particular, the advent of Web 2.0 and the spreading of video-sharing services over the Web have led to an explosion of online video content. The capability to provide broader support in accessing and exploring video content, and in general other kind of multimedia formats as images and documents, is becoming more and more important. In this context, the value of semantically structured data and metadata is recognized as a key factor both to improve search efficiency and to guarantee data interoperability. This latter aspect is critical to connect different, heterogeneous content coming from a variety of data sources. On the other hand, the annotation of video resources has been increasingly understood as a medium factor to enable deep analysis of contents and collaborative study of online digital objects. However, as existing annotation tools provide poor support for semantically structured content or in some cases express the semantics in proprietary and non-interoperable formats, such knowledge that users build by carefully annotating contents hardly crosses the boundaries of a single system and often cannot be reused by different communities (e.g., to classify content or to discover new relations among resources). In this paper, a novel Semantic Web-based annotation system is presented that enables user annotations to form semantically structured knowledge at different levels of granularity and complexity. Annotation can be reused by external applications and mixed with Web of Data sources to enable “serendipity,” the reuse of data produced for a specific task (annotation) by different people and in different contexts from the one data originated from. The main ideas behind the approach are to build on ontologies and support linking, at data level, to precise thesauri and vocabularies, as well as to the Linked Open Data cloud. By describing the software model, developed in the context of SemLib EU project, and by providing an implementation of an online video annotation tool, the main aim of this paper is to demonstrate how such technologies can enable a scenario where users annotations are created while browsing the Web, naturally shared among users, stored in machine readable format and then possibly recombined with external data and ontologies to enhance end-user experience.
    18 schema:genre research_article
    19 schema:inLanguage en
    20 schema:isAccessibleForFree false
    21 schema:isPartOf N608171f34b2e4309b2ffd92a1c8d371a
    22 Nd74c69e0d2d445e28ceebb9d7eede57d
    23 sg:journal.1041199
    24 schema:name A Collaborative Video Annotation System Based on Semantic Web Technologies
    25 schema:pagination 497-514
    26 schema:productId N227cc3765ca44dd2b135078e3dca31ed
    27 N3181c699a83f4b1da989c7bdd3cfbb79
    28 Ne02ca6f2924b4cf78664754c6ee638c4
    29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051237471
    30 https://doi.org/10.1007/s12559-012-9172-1
    31 schema:sdDatePublished 2019-04-10T16:45
    32 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    33 schema:sdPublisher N8c38e19b1f5e4aea8090f68e03d8cad0
    34 schema:url http://link.springer.com/10.1007%2Fs12559-012-9172-1
    35 sgo:license sg:explorer/license/
    36 sgo:sdDataset articles
    37 rdf:type schema:ScholarlyArticle
    38 N227cc3765ca44dd2b135078e3dca31ed schema:name doi
    39 schema:value 10.1007/s12559-012-9172-1
    40 rdf:type schema:PropertyValue
    41 N3181c699a83f4b1da989c7bdd3cfbb79 schema:name readcube_id
    42 schema:value f41303ee27a0402564395915794d99496b1fff211c80a6f81b7d1086461c5ce7
    43 rdf:type schema:PropertyValue
    44 N608171f34b2e4309b2ffd92a1c8d371a schema:issueNumber 4
    45 rdf:type schema:PublicationIssue
    46 N8c38e19b1f5e4aea8090f68e03d8cad0 schema:name Springer Nature - SN SciGraph project
    47 rdf:type schema:Organization
    48 N8cccdd52c0f84a41998d398784245926 rdf:first sg:person.016277275261.20
    49 rdf:rest Nb4d490fb2ea34682b4ad2bf5c22d2355
    50 N990476d4efe04b31a623a443bf26fda8 rdf:first sg:person.012254550647.94
    51 rdf:rest N8cccdd52c0f84a41998d398784245926
    52 Nb4d490fb2ea34682b4ad2bf5c22d2355 rdf:first sg:person.015207055165.13
    53 rdf:rest rdf:nil
    54 Nd74c69e0d2d445e28ceebb9d7eede57d schema:volumeNumber 4
    55 rdf:type schema:PublicationVolume
    56 Ne02ca6f2924b4cf78664754c6ee638c4 schema:name dimensions_id
    57 schema:value pub.1051237471
    58 rdf:type schema:PropertyValue
    59 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    60 schema:name Information and Computing Sciences
    61 rdf:type schema:DefinedTerm
    62 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
    63 schema:name Information Systems
    64 rdf:type schema:DefinedTerm
    65 sg:grant.3788078 http://pending.schema.org/fundedItem sg:pub.10.1007/s12559-012-9172-1
    66 rdf:type schema:MonetaryGrant
    67 sg:journal.1041199 schema:issn 1866-9956
    68 1866-9964
    69 schema:name Cognitive Computation
    70 rdf:type schema:Periodical
    71 sg:person.012254550647.94 schema:affiliation https://www.grid.ac/institutes/grid.7010.6
    72 schema:familyName Grassi
    73 schema:givenName Marco
    74 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012254550647.94
    75 rdf:type schema:Person
    76 sg:person.015207055165.13 schema:affiliation https://www.grid.ac/institutes/grid.7010.6
    77 schema:familyName Nucci
    78 schema:givenName Michele
    79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015207055165.13
    80 rdf:type schema:Person
    81 sg:person.016277275261.20 schema:affiliation https://www.grid.ac/institutes/grid.7010.6
    82 schema:familyName Morbidoni
    83 schema:givenName Christian
    84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016277275261.20
    85 rdf:type schema:Person
    86 sg:pub.10.1007/11893011_80 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023287280
    87 https://doi.org/10.1007/11893011_80
    88 rdf:type schema:CreativeWork
    89 sg:pub.10.1007/978-3-642-18184-9_25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046660846
    90 https://doi.org/10.1007/978-3-642-18184-9_25
    91 rdf:type schema:CreativeWork
    92 sg:pub.10.1007/978-3-642-20795-2_8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036366018
    93 https://doi.org/10.1007/978-3-642-20795-2_8
    94 rdf:type schema:CreativeWork
    95 sg:pub.10.1007/978-3-642-25775-9_9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049185396
    96 https://doi.org/10.1007/978-3-642-25775-9_9
    97 rdf:type schema:CreativeWork
    98 sg:pub.10.1007/s12559-011-9101-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012153753
    99 https://doi.org/10.1007/s12559-011-9101-8
    100 rdf:type schema:CreativeWork
    101 https://doi.org/10.1016/j.websem.2009.07.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011160236
    102 rdf:type schema:CreativeWork
    103 https://doi.org/10.1109/mmse.2004.58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094287004
    104 rdf:type schema:CreativeWork
    105 https://doi.org/10.1109/tsmcc.2011.2109710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061798320
    106 rdf:type schema:CreativeWork
    107 https://doi.org/10.1145/1839707.1839757 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012792698
    108 rdf:type schema:CreativeWork
    109 https://doi.org/10.1145/1873951.1874305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032534743
    110 rdf:type schema:CreativeWork
    111 https://doi.org/10.1145/371920.372166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018835628
    112 rdf:type schema:CreativeWork
    113 https://www.grid.ac/institutes/grid.7010.6 schema:alternateName Marche Polytechnic University
    114 schema:name Semedia (Semantic Web and Multimedia), Polytechnic University of Marche, Via Brecce Bianche I, 60131, Ancona, Italy
    115 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...