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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Macquarie University, Macquarie Park, 2109, NSW, Australia", 
          "id": "http://www.grid.ac/institutes/grid.1004.5", 
          "name": [
            "Macquarie University, Macquarie Park, 2109, NSW, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zheng", 
        "givenName": "Xi", 
        "id": "sg:person.07673312776.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07673312776.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Macquarie University, Macquarie Park, 2109, NSW, Australia", 
          "id": "http://www.grid.ac/institutes/grid.1004.5", 
          "name": [
            "Macquarie University, Macquarie Park, 2109, NSW, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fu", 
        "givenName": "Min", 
        "id": "sg:person.016150437403.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016150437403.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Deakin University, 3220, Geelong VIC, Australia", 
          "id": "http://www.grid.ac/institutes/grid.1021.2", 
          "name": [
            "Deakin University, 3220, Geelong VIC, Australia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chugh", 
        "givenName": "Mohit", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/2192-113x-2-22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043498333", 
          "https://doi.org/10.1186/2192-113x-2-22"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-09-22", 
    "datePublishedReg": "2017-09-22", 
    "description": "As an important service model for advanced computing, SaaS uses a defined protocol that manages services and applications. The popularity of advanced computing has reached a level that has led to the generation of large data sets, which is also called Big data. Big data is evolving with great velocity, large volumes, and great diversity. Such an amplification of data has brought into question the existing database tools in terms of their capabilities. Previously, storage and processing of data were simple tasks; however, it is now one of the biggest challenges in the industry. Experts are paying close attention to big data. Designing a system capable of storing and analyzing such data in order to extract meaningful information for decision-making is a priority. The Apache Hadoop, Spark, and NoSQL databases are some of the core technologies that are being used to solve these issues. This paper contributes to the solutions to the issues of big data storage and processing. It presents an analysis of the current technologies in the industry that could be useful in this context. Efforts have been focused on implementing a novel Trinity model, which is built using the lambda architecture with the following technologies: Hadoop, Spark, Kafka, and MongoDB.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s41650-017-0031-9", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1290433", 
        "issn": [
          "2096-1081", 
          "2509-3312"
        ], 
        "name": "Journal of Communications and Information Networks", 
        "publisher": "Institute of Electrical and Electronics Engineers (IEEE)", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2"
      }
    ], 
    "keywords": [
      "big data storage", 
      "big data", 
      "advanced computing", 
      "data storage", 
      "processing of data", 
      "large data sets", 
      "Lambda architecture", 
      "SaaS applications", 
      "NoSQL databases", 
      "Apache Hadoop", 
      "database tools", 
      "core technology", 
      "service model", 
      "meaningful information", 
      "Hadoop", 
      "computing", 
      "simple task", 
      "data sets", 
      "big challenge", 
      "such data", 
      "large volumes", 
      "current technology", 
      "Spark", 
      "technology", 
      "trinity model", 
      "processing", 
      "architecture", 
      "applications", 
      "task", 
      "storage", 
      "Kafka", 
      "issues", 
      "SAA", 
      "popularity", 
      "services", 
      "data", 
      "capability", 
      "database", 
      "information", 
      "experts", 
      "set", 
      "industry", 
      "model", 
      "protocol", 
      "tool", 
      "challenges", 
      "system", 
      "solution", 
      "context", 
      "management", 
      "order", 
      "efforts", 
      "generation", 
      "priority", 
      "terms", 
      "attention", 
      "close attention", 
      "greater velocity", 
      "analysis", 
      "questions", 
      "diversity", 
      "volume", 
      "great diversity", 
      "levels", 
      "velocity", 
      "amplification", 
      "paper"
    ], 
    "name": "Big data storage and management in SaaS applications", 
    "pagination": "18-29", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1091891150"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s41650-017-0031-9"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s41650-017-0031-9", 
      "https://app.dimensions.ai/details/publication/pub.1091891150"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-08-04T17:06", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_744.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s41650-017-0031-9"
  }
]

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.

144 TRIPLES      21 PREDICATES      92 URIs      83 LITERALS      6 BLANK NODES