SAQA All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source.
SOUTH AFRICAN QUALIFICATIONS AUTHORITY 
REGISTERED UNIT STANDARD: 

Aggregate and integrate vector geo-information data 
SAQA US ID UNIT STANDARD TITLE
116835  Aggregate and integrate vector geo-information data 
ORIGINATOR
SGB Geographical Information Sciences 
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY
-  
FIELD SUBFIELD
Field 12 - Physical Planning and Construction Physical Planning, Design and Management 
ABET BAND UNIT STANDARD TYPE PRE-2009 NQF LEVEL NQF LEVEL CREDITS
Undefined  Regular  Level 4  NQF Level 04 
REGISTRATION STATUS REGISTRATION START DATE REGISTRATION END DATE SAQA DECISION NUMBER
Reregistered  2018-07-01  2023-06-30  SAQA 06120/18 
LAST DATE FOR ENROLMENT LAST DATE FOR ACHIEVEMENT
2024-06-30   2027-06-30  

In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise.  

This unit standard does not replace any other unit standard and is not replaced by any other unit standard. 

PURPOSE OF THE UNIT STANDARD 
This unit standard will be useful to people who aim to achieve career advancement in the GISc area by gaining skills to capture Geo-information from secondary data sources under supervision.

A person credited with this unit standard understands and is able to:
  • Combine two or more existing vector data sets with different characteristics.
  • Conflate two or more existing vector data sets with the same characteristics.
  • Aggregate lower level objects into higher-level objects (e.g. Create magisterial districts from municipal boundaries). 

  • LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING 
    The credit calculation is based on the assumption that learners are already competent in terms of the following outcomes or areas of learning when starting to learn towards this unit standard:
  • Basic understanding of the elementary concepts of spatial awareness.
  • Basic understanding of the elementary concepts of GIS data structures for data acquisition.
  • Basic understanding of GIS vector software functions.
  • Basic understanding of metadata. 

  • UNIT STANDARD RANGE 
    Specific range statements are provided in the body of the unit standard where they apply to particular specific outcomes or assessment criteria. These include, inter alia, projections, datums, file format and conflation, co-ordinate systems and scale. 

    Specific Outcomes and Assessment Criteria: 

    SPECIFIC OUTCOME 1 
    Combine two or more existing data sets having different characteristics. 
    OUTCOME RANGE 
    Included but not limited to Scale, Projections, Datums, Accuracy, Currency, Metadata, File formats. 

    ASSESSMENT CRITERIA
     

    ASSESSMENT CRITERION 1 
    The characteristics of source datasets as well as the target dataset are identified. 

    ASSESSMENT CRITERION 2 
    The effects of spatial characteristic differences and compatibilities are understood and explained. 

    ASSESSMENT CRITERION 3 
    Source datasets are converted to target characteristics. 

    ASSESSMENT CRITERION 4 
    Inconsistencies in alphanumeric data between target and source are identified. 
    ASSESSMENT CRITERION RANGE 
    Inconsistencies include but are not limited to: Field name differences, field types, missing contents, missing fields, redundant source fields, and lineage.
     

    ASSESSMENT CRITERION 5 
    Source datasets are combined with the target datasets. 
    ASSESSMENT CRITERION RANGE 
    Datasets include source as well as target data sets.
     

    ASSESSMENT CRITERION 6 
    Update and maintain lineage and metadata records for target data. 

    SPECIFIC OUTCOME 2 
    Conflate two or more existing data sets having the same characteristics. 

    ASSESSMENT CRITERIA
     

    ASSESSMENT CRITERION 1 
    Applicable objects in source datasets to be conflated are identified. 

    ASSESSMENT CRITERION 2 
    Conflation characteristics of identified objects in source datasets are determined. 
    ASSESSMENT CRITERION RANGE 
    Conflation characteristics include: Accuracy, Scale and Lineage.
     

    ASSESSMENT CRITERION 3 
    Conflation characteristics of source datasets are compared in order to identify the preferred objects to be used. 

    ASSESSMENT CRITERION 4 
    Identified objects are combined in the target datasets. 

    ASSESSMENT CRITERION 5 
    Update and maintain lineage and metadata records for target data. 

    SPECIFIC OUTCOME 3 
    Aggregate lower level objects into higher level objects. 

    ASSESSMENT CRITERIA
     

    ASSESSMENT CRITERION 1 
    The applicable common denominator or denominators in the lower level data set to be used for lumping the data into a higher level dataset are determined. 
    ASSESSMENT CRITERION RANGE 
    Common denominator may be spatial, alphanumeric or both.
     

    ASSESSMENT CRITERION 2 
    The unique identifier to be used in the higher level dataset is determined. 

    ASSESSMENT CRITERION 3 
    Aggregate the data. 
    ASSESSMENT CRITERION RANGE 
    Aggregation may be automatic, semi-automatic or manual.
     

    ASSESSMENT CRITERION 4 
    Update and maintain lineage and metadata records for target data. 

    SPECIFIC OUTCOME 4 
    Demonstrate a basic understanding of projections, co-ordinate systems, datums and scale. 

    ASSESSMENT CRITERIA
     

    ASSESSMENT CRITERION 1 
    Types of projections are listed and explained. 

    ASSESSMENT CRITERION 2 
    Types of co-ordinate systems are listed and explained. 

    ASSESSMENT CRITERION 3 
    Types of datums are listed and explained. 

    ASSESSMENT CRITERION 4 
    Scale is explained in the context of projections. 


    UNIT STANDARD ACCREDITATION AND MODERATION OPTIONS 
    Moderation
  • Anyone assessing a learner against this unit standard must be registered as an assessor with the relevant ETQA.
  • Any institution offering learning that will enable achievement of this unit standard must be accredited as a provider through the relevant ETQA by SAQA.
  • Moderation of assessment will be overseen by the relevant ETQA according to the moderation guidelines and the agreed ETQA procedures. 

  • UNIT STANDARD ESSENTIAL EMBEDDED KNOWLEDGE 
    Essential embedded knowledge will be assessed through assessment of the specific outcomes in terms of the stipulated assessment criteria. Candidates are unlikely to achieve all the specific outcomes, to the standards described in the assessment criteria, without knowledge of the listed embedded knowledge. This means that for the most part, the possession or lack of the knowledge can be directly inferred from the quality of the candidate's performance. Where direct assessment of knowledge is required, assessment criteria have been included in the body of the unit standard.

    The following embedded knowledge is addressed in an integrated way in the unit standard:
  • Basic knowledge of geography.
  • Basic knowledge of cartography.
  • Basic understanding of school mathematics (trigonometry and geometry).
  • Basic understanding of surveying principles.
  • Basic understanding of map coordinate systems.
  • Basic understanding of spatial data structures.
  • Basic computer literacy. 

  • UNIT STANDARD DEVELOPMENTAL OUTCOME 
    N/A 

    UNIT STANDARD LINKAGES 
    N/A 


    Critical Cross-field Outcomes (CCFO): 

    UNIT STANDARD CCFO IDENTIFYING 
    Solve problems.
  • The effects of spatial characteristic differences and compatibilities are understood and explained.
  • Source datasets are converted to target characteristics.
  • Inconsistencies in alphanumeric data between target and source are identified.
  • Applicable objects in source datasets to be conflated are identified.
  • Conflation characteristics of identified objects in source datasets are determined.
  • Conflation characteristics of source datasets are compared in order to identify the preferred objects to be used.
  • The applicable common denominator or denominators in the lower level data set to be used for lumping the data into a higher level dataset are determined.
  • The unique identifier to be used in the higher level dataset is determined. 

  • UNIT STANDARD CCFO WORKING 
    Work effectively with others as a member of a team / group / organisation or community.
  • Not assessed by this unit standard. 

  • UNIT STANDARD CCFO ORGANISING 
    Organise and manage oneself and one's activities responsibly and effectively.
  • The characteristics of source datasets as well as the target dataset are identified.
  • The effects of spatial characteristic differences and compatibilities are understood and explained.
  • Source datasets are converted to target characteristics.
  • Inconsistencies in alphanumeric data between target and source are identified.
  • Source datasets are combined with the target datasets.
  • Update and maintain lineage and metadata records for target data.
  • Applicable objects in source datasets to be conflated are identified.
  • Conflation characteristics of identified objects in source datasets are determined.
  • Conflation characteristics of source datasets are compared in order to identify the preferred objects to be used.
  • Update and maintain lineage and metadata records for target data.
  • The applicable common denominator or denominators in the lower level data set to be used for lumping the data into a higher level dataset are determined.
  • The unique identifier to be used in the higher level dataset is determined.
  • Aggregate the data.
  • Update and maintain lineage and metadata records for target data. 

  • UNIT STANDARD CCFO COLLECTING 
    Collect, organise and critically evaluateInformation.
  • The characteristics of source datasets as well as the target dataset are identified.
  • The effects of spatial characteristic differences and compatibilities are understood and explained.
  • Source datasets are converted to target characteristics.
  • Inconsistencies in alphanumeric data between target and source are identified.
  • Applicable objects in source datasets to be conflated are identified.
  • Conflation characteristics of identified objects in source datasets are determined.
  • Conflation characteristics of source datasets are compared in order to identify the preferred objects to be used.
  • The applicable common denominator or denominators in the lower level data set to be used for lumping the data into a higher level dataset are determined.
  • The unique identifier to be used in the higher level dataset is determined.
  • Aggregate the data. 

  • UNIT STANDARD CCFO COMMUNICATING 
    Communicate effectively using visual, Mathematics and language skills in the Modes of oral and written presentations.
  • Not assessed by this unit standard. 

  • UNIT STANDARD CCFO SCIENCE 
    Use science and technology effectively and critically (showing responsibility towards the environment and health of others).
  • The characteristics of source datasets as well as the target dataset are identified.
  • The effects of spatial characteristic differences and compatibilities are understood and explained.
  • Source datasets are converted to target characteristics.
  • Inconsistencies in alphanumeric data between target and source are identified.
  • Source datasets are combined with the target datasets.
  • Update and maintain lineage and metadata records for target data.
  • Applicable objects in source datasets to be conflated are identified.
  • Conflation characteristics of identified objects in source datasets are determined.
  • Conflation characteristics of source datasets are compared in order to identify the preferred objects to be used.
  • Update and maintain lineage and metadata records for target data.
  • The applicable common denominator or denominators in the lower level data set to be used for lumping the data into a higher level dataset are determined.
  • The unique identifier to be used in the higher level dataset is determined.
  • Aggregate the data.
  • Update and maintain lineage and metadata records for target data. 

  • UNIT STANDARD CCFO DEMONSTRATING 
    Demonstrate an understanding of the world as a set of related systems.
  • Not assessed by this unit standard. 

  • UNIT STANDARD ASSESSOR CRITERIA 
    Assessors should keep the following principles in mind when designing and conducting assessments against this unit standard:
  • Focus the assessment activities on gathering evidence in terms of the main outcome expressed in the title to ensure assessment is integrated rather than fragmented. Remember we want to declare the person competent in terms of the title. Where assessment at title level is unmanageable, then focus assessment around each specific outcome, or groups of specific outcomes.
  • Make sure evidence is gathered across the entire range, wherever it applies. Assessment activities should be as close to the real performance as possible, and where simulations or role-plays are used, there should be supporting evidence to show the candidate is able to perform in the real situation.
  • Do not focus the assessment activities on each assessment criterion. Rather make sure the assessment activities focus on outcomes and are sufficient to enable evidence to be gathered around all the assessment criteria.
  • The assessment criteria provide the specifications against which assessment judgements should be made. In most cases, knowledge can be inferred from the quality of the performances, but in other cases, knowledge and understanding will have to be tested through questioning techniques. Where this is required, there will be assessment criteria to specify the standard required.
  • The task of the assessor is to gather sufficient evidence, of the prescribed type and quality, as specified in this unit standard, that the candidate can achieve the outcomes again and again and again. This means assessors will have to judge how many repeat performances are required before they believe the performance is reproducible.
  • All assessments should be conducted in line with the following well documented principles of assessment: appropriateness, fairness, manageability, integration into work or learning, validity, direct, authentic, sufficient, systematic, open and consistent. 

  • REREGISTRATION HISTORY 
    As per the SAQA Board decision/s at that time, this unit standard was Reregistered in 2012; 2015. 

    UNIT STANDARD NOTES 
    Terminology
  • Conflate: Create one dataset from different datasets by using the best records from either.
  • Aggregate: Create one higher level dataset from different lower level datasets by using common denominators. 

  • QUALIFICATIONS UTILISING THIS UNIT STANDARD: 
      ID QUALIFICATION TITLE PRE-2009 NQF LEVEL NQF LEVEL STATUS END DATE PRIMARY OR DELEGATED QA FUNCTIONARY
    Elective  49063   National Certificate: Geographical Information Sciences  Level 5  Level TBA: Pre-2009 was L5  Reregistered  2023-06-30  CETA 


    PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS UNIT STANDARD: 
    This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here.
     
    1. ESRI SOUTH AFRICA 



    All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source.