Published at October 25th, 2025 • Last updated 9 days ago

Data assessment and mapping

Who is this page for?

This page is intended for clients who have recently bought Pure, or a new part of Pure, and are currently or will soon be working on an implementation project with a Pure Implementation Manager. It provides general information that is applicable to all Pures; your Implementation Manager will help you address the details specific to your individual case.

 

 

Introduction

Data assessment is relevant if you intend to synchronize or import data from your existing external source systems, e.g. HR/student/faculty source systems or a legacy publication system.

This activity is done to determine what data can be extracted from your external system(s) and to ensure that data is structured, consistent and of sufficient quality before the next phase is started.

Data assessment

In order for your Implementation Manager (IM) to assess your data, please extract and share samples of your data covering the information listed below (for the integrations/imports that apply to your project):

For publication import

Publications

  • Title
  • Unique ID
  • Type
  • Author(s)
    • Relation between Person/Employee (see above) and publication (e.g. by an ID)
  • Author's organisational unit (for which organisation did the author complete the publication?)
  • Managing organisational unit (which organisation manages the publication, i.e. validation of data etc.?)
  • Additional IDs (e.g. DOI, ISBN, ISSN, Scopus ID)
For Project Integration/Import

Applications

  • Type
  • Title
  • Unique ID
  • Applicant(s) (either person or organisational unit)
    • Relation between Person/Employee (see above) and application
  • Managing organisational unit
  • (Collaborative partners)
  • Funding organisation
  • Applied amount
  • Submission date

Awards

  • Type
  • Title
  • Unique ID
  • Award holder(s) (either person or organisational unit)
    • Relation between Person/Employee (see above) and award
  • Managing organisational unit
  • (Collaborative partners)
  • Funding organisation
  • Awarded amount
  • Award date

Projects

  • Type
  • Title
  • Unique ID
  • Project participant(s) (either person or organisational unit)
    • Relation between Person/Employee (see above) and project
    • if Person: Participant's role in project (Primary Investigator or Co-Investigator)
  • Managing organisational unit
  • (Collaborative partners)
  • Start date
For HR integration

Organisational units

  • Name
  • Unique ID
  • Start date
  • Hierarchy of organisational units
  • (Former organisational units)
  • (Hierarchy of research groups)

Persons (Employees/Students)

  • First name
  • Last name
  • Unique ID
  • E-mail address
  • (Gender)
  • (Date of birth)
  • Related organisational units (where is the researcher "employed"?)
  • Start date of employment at the related organisational unit

Note: () is optional. 

The delivery format of the data sample is optional, but should be legible. Suggested formats are: XML, Excel spreadsheet, the output of a SQL statement or similar.

Once you have completed the data assessment exercise with your Implementation Manager and decided which optional fields in your existing and/or legacy data you want to add to your Pure, you will need to map them to Pure's data model. You can download the full field documentation for your Pure from Administrator > Field and role documentation > Field documentation.

Goals

  • Identify challenges (in the source data) to guide you on how to address these early in the process
  • Avoid unforeseen time spent on improving data quality later in the project

Participants

The following table lists the persons that should participate in the data assessment activity - mandatory participants are emphasised in bold. 

Customer Elsevier
  • IT experts
  • Source data/domain experts
  • Implementation manager

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