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/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1005", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Communications Technologies", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.25A, 1113, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.25A, 1113, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fidanova", 
        "givenName": "Stefka", 
        "id": "sg:person.011173106320.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011173106320.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.25A, 1113, Sofia, Bulgaria", 
          "id": "http://www.grid.ac/institutes/grid.424988.b", 
          "name": [
            "Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl.25A, 1113, Sofia, Bulgaria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marinov", 
        "givenName": "Pencho", 
        "id": "sg:person.010037302031.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010037302031.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "E.T.S.I. Inform\u00e1tica, Grupo GISUM (NEO), University of Malaga, Malaga, Spain", 
          "id": "http://www.grid.ac/institutes/grid.10215.37", 
          "name": [
            "E.T.S.I. Inform\u00e1tica, Grupo GISUM (NEO), University of Malaga, Malaga, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alba", 
        "givenName": "Enrique", 
        "id": "sg:person.013075206405.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013075206405.86"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2012", 
    "datePublishedReg": "2012-01-01", 
    "description": "Telecommunications is a general term for a vast array of technologies that send information over distances. Mobile phones, land lines, satellite phones and voice over Internet protocol are all telephony technologies - just one field of telecommunications. Radio, television and networks are a few more examples of telecommunication. Nowadays, the trend in telecommunication networks is having highly decentralized, multi-node networks. From small, geographically close, size-limited local area networks the evolution has led to the huge worldwide Internet. In this context Wireless Sensor Networks (WSN) have recently become a hot topic in research. When deploying a WSN, the positioning of the sensor nodes becomes one of the major concerns. One of the objectives is to achieve full coverage of the terrain (sensor field). Another objectives are also to use a minimum number of sensor nodes and to keep the connectivity of the network. In this paper we address a WSN deployment problem in which full coverage and connectivity are treated as constraints, while objective function is the number of the sensors. To solve it we propose Ant Colony Optimization (ACO) algorithm.", 
    "editor": [
      {
        "familyName": "Madani", 
        "givenName": "Kurosh", 
        "type": "Person"
      }, 
      {
        "familyName": "Dourado Correia", 
        "givenName": "Ant\u00f3nio", 
        "type": "Person"
      }, 
      {
        "familyName": "Rosa", 
        "givenName": "Agostinho", 
        "type": "Person"
      }, 
      {
        "familyName": "Filipe", 
        "givenName": "Joaquim", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-27534-0_2", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-27533-3", 
        "978-3-642-27534-0"
      ], 
      "name": "Computational Intelligence", 
      "type": "Book"
    }, 
    "keywords": [
      "wireless sensor networks", 
      "sensor nodes", 
      "WSN deployment problem", 
      "multi-node networks", 
      "field of telecommunications", 
      "optimal sensor deployment", 
      "Internet Protocol", 
      "ant colony optimization algorithm", 
      "sensor networks", 
      "colony optimization algorithm", 
      "satellite phones", 
      "full coverage", 
      "telecommunication networks", 
      "telephony technologies", 
      "deployment problem", 
      "sensor deployment", 
      "worldwide Internet", 
      "land lines", 
      "ant algorithm", 
      "mobile phones", 
      "optimization algorithm", 
      "objective function", 
      "telecommunications", 
      "hot topic", 
      "network", 
      "phones", 
      "algorithm", 
      "minimum number", 
      "nodes", 
      "technology", 
      "radio", 
      "connectivity", 
      "Internet", 
      "major concern", 
      "deployment", 
      "more examples", 
      "sensors", 
      "array", 
      "coverage", 
      "protocol", 
      "local area", 
      "vast array", 
      "information", 
      "constraints", 
      "problem", 
      "general terms", 
      "field", 
      "number", 
      "topic", 
      "voice", 
      "terrain", 
      "terms", 
      "example", 
      "objective", 
      "television", 
      "function", 
      "paper", 
      "distance", 
      "research", 
      "evolution", 
      "positioning", 
      "area", 
      "concern", 
      "lines", 
      "trends"
    ], 
    "name": "Ant Algorithm for Optimal Sensor Deployment", 
    "pagination": "21-29", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018675027"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-27534-0_2"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-27534-0_2", 
      "https://app.dimensions.ai/details/publication/pub.1018675027"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-05-10T10:49", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/chapter/chapter_384.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-642-27534-0_2"
  }
]

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

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

157 TRIPLES      23 PREDICATES      91 URIs      84 LITERALS      7 BLANK NODES