{"id":11371,"date":"2026-05-29T21:26:14","date_gmt":"2026-05-29T11:26:14","guid":{"rendered":"https:\/\/casestudyhelp.com\/sample-questions\/?p=11371"},"modified":"2026-05-29T21:26:14","modified_gmt":"2026-05-29T11:26:14","slug":"sem314ds-graphs-and-graph-data-science-assessment-solutions","status":"publish","type":"post","link":"https:\/\/casestudyhelp.com\/sample-questions\/sem314ds-graphs-and-graph-data-science-assessment-solutions\/","title":{"rendered":"SEM314DS Graphs and Graph Data Science Assessment Solutions"},"content":{"rendered":"
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Looking for help with SEM314DS Graphs and Graph Data Science Assessment? Get guidance from experts with years of experience and skill. At Casestudyhelp.com<\/a>, you can get assistance with any College Assignment<\/a> in Computer Science Assignment Help<\/a>, Python Assignment Help, Programming Assignment Help<\/a>, and AutoCAD Assignment Help<\/a>. Book your order today!<\/p>\n<\/blockquote>\n

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ASSESSMENT TASKS<\/h2>\n

Task 1 FORMATIVE TASK Graphs and Graph Data Science Introduced<\/h2>\n

FORMATIVE TASK<\/h6>\n

Instruction: Explain the different types of graphs and their properties to a non-specialist. Your briefing note should contain the following:<\/p>\n

    \n
  • An outline of what is understood by the terms \u2018graph\u2019, \u2018vertex\u2019, \u2018node\u2019 and \u2018edge\u2019.<\/li>\n
  • Identify and explain the problem and solution of the Bridges of Konigsberg<\/li>\n
  • Discuss the various types of graphs, and provide examples for several of<\/li>\n<\/ul>\n

    Task 2 SUMMATIVE TASK Graph Data Science in Your Organisation<\/h2>\n

    SUMMATIVE TASK<\/h6>\n

    Instruction: Evaluate how graph data science can be used to advance the interests of an organisation of your choosing. Your report must contain the following:<\/p>\n

      \n
    • An outline of the various types of graph data models, and of the graph ecosystem as it currently stands (LO 1, 2.2, 2.3, 3.1 )<\/li>\n
    • Identify and explain the advantages and potential uses of LPG database, RDF database and relational databases (LO 3.2, 3.3, 4.2)<\/li>\n
    • A judgment as to the benefits of the use of graph data within the organisation, and the potential impact of this material on future decision making (LO 3.3, 3.4, 3)<\/li>\n<\/ul>\n\n\n\n\n\n\n
      Learning Outcomes: To achieve this unit, the learner must be able to:<\/strong><\/td>\nAssessment Criteria:<\/strong><\/p>\n

      Assessment of these learning outcomes will require a learner to demonstrate that they can:<\/strong><\/td>\n<\/tr>\n

      2.\u00a0\u00a0\u00a0\u00a0 Understand the core types of graph data models.<\/td>\n2.1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Explain what is meant by a \u201cKnowledge graph\u201d.<\/p>\n

      2.2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Explain what is meant by a \u201cLabelled Property Graph\u201d (LPG).<\/p>\n

      2.3\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Explain what is meant by a \u201cResource Description Framework\u201d (RDF) graph.<\/td>\n<\/tr>\n

      3.\u00a0\u00a0\u00a0\u00a0 Understand the graph ecosystem.<\/td>\n3.1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Outline the graph ecosystem from graph databases, graph languages to graph visualisation tools.<\/p>\n

      3.2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyse the features, uses, benefits and drawbacks of LPG databases, RDF databases and relational databases.<\/p>\n

      3.3\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyse the use-cases and applications for LPG and RDF graph databases.<\/p>\n

      3.4\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyse Python graph libraries and their features.<\/td>\n<\/tr>\n

      4.\u00a0\u00a0\u00a0\u00a0 Understand the types of graph data science and graph algorithms.<\/td>\n4.1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Explain what is meant by \u201cgraph data science\u201d.<\/p>\n

      4.2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyse the types of \u201cgraph<\/p>\n

      algorithms\u201d: search and pathfinding,<\/p>\n

      centrality, and community detection.<\/p>\n

      4.3\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Analyse the types of problems and use- cases that can be tackled by graph data science.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n