welcome to the 2017 pure international conference
TRANSCRIPT
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Kelechi Okere| Global Sales Director, Pure
Welcome to the 2017 Pure International Conference
October 10, 2017
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Pure 101Section 1
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1 Data Aggregation
2 Reporting
4 Live Demo
Presentation Outline
3 Public Access & Sharing
5 Delivery & Service
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1. Data Aggregation
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Pure’s data model captures 20 data types/signals across
the research lifecycle…
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Typical data landscape at typical
university
Research information management
system
Has multiple IDs
Disparate
Is not related
Is not homogeneous
Available at high cost in
FTE
Structured
Uniquely identified
Inter-related
Homogeneous
Available at low cost in FTE
X
Y
Z
X
CAN’T easily be used for
management,
administration, or
showcasing
CAN easily be used for
management,
administration, or
showcasing
…from scattered to structured & holistic view of data
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• Applications
• Grants
• Projects
• Research Output
• Activities
• Datasets
• Persons
• Organizational Units
• External Persons
• External Organizations
• Journals
• Prizes
• Course Taught
• Robust data model
• Customizable quality
assurance workflows
• Interrelated Content
• Performance
Dashboards
• Customized
performance
reports
• View research
grant income
success rates
• Showcasing
• CVs
• Open Access
management
• …
Outputs
Aggregate once, use many times for many things by
many people
• VP of Research
• Deans & dept
heads
• Researchers
• Research
administrators
• Comms office
• Library
• Tech Transfer
• Students
• …
Who benefits
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1a. Getting data into Pure
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Pure is an open research information management
system
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Profile Refinement Services (PRS)
PRS allows you to minimize manual maintenance of
researcher profiles with pre-built, automatically
updated profiles based on Scopus data.
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With PRS, the Elsevier Fingerprint Engine is used to
identify concepts in a researcher’s body of work
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2. Reporting
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Generate and share insightful reports
Generate and distribute validated internal intelligence to accelerate
promotion and tenure evaluations, departmental and institutional
assessments, and other vital requirements
• Pre-defined and advanced report creation capabilities on all Pure content
• Schedule reports to automatically runand be sent to a predefined distribution list
• Apply targets to departments for predetermined research performance indicators such as Snowball Metrics via Pure’s research intelligence capabilities, then track and monitor them throughdashboards
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Example: Tracking researcher output
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View live progress at-a-glance
• Dashboards can be personalized, shared and used for monitoring and reporting
• User controls ensure that only data relevant to the user are visible
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Analyze collaboration networks
Pure visualizes the relationships between each researcher and their collaborators,
including co-authors of applications or publications as well as partners on projects
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3. Public Access/Sharing
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Pure supports sharing of metadata & OA management
Sharing Metadata
Repository connectors (D-space, e-prints, Fedora)
Pure Web Service (REST, SOAP, OAI)
Open Access Tools
Publication data model
SHERPA RoMEO archiving policy (green, blue, yellow, white)
Directory of Open Access Journals
Repository storage conditions: electronic version access
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Pure Portal provides unparalleled visibility to a
university’s research inputs & outputs
• Manual
• Profile Refinement
Services (optional)
Other
• Syncs
Integrations
• Wizards
• File Imports
Bulk import tools
• Scopus
• PubMed
• Web of Science
API Subscriptions
Data Inputs The Pure Portal
The Pure Portal is a public portal that produces concise expertise
results based on Elsevier’s proprietary fingerprint algorithm and
your curated data in Pure’s backend.
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4. Live Demo: Admin, Reporting, Portal
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5. Delivery & Service
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Final hostingTemporary hosting
HR-integration + PRS (if wanted)
HR
Master-list production + PRS (if wanted)
HR data
UNIUNI UNI UNIUNI
Pure can be delivered within 6mos
Teams' Q&A, planning, align resources
Kick-off
SIGNING
FULL
PRODUCTION
OR
EITHE
R
Configuration of Pure instance; modules, etc.
Setup
Legacy imports
Migration
OPTIONA
L
More integrations e.g. finance, PGRs, ethical
Integration
OPTIONA
L
Setup of production instance
Install
User training to specific modules and use-cases
Training
Content review, UAT, legal acceptance
Review
Sign-off, password removal
Go-live
Evaluate process, discuss usage and new use-cases
Follow-up
OPTIONA
L
Main phases
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>230 clients in 33 countries today(More clents than our next five competitors combined)
Pure is currently used to manage profiles of over 640,000 researchers; these profiles are viewed more than 4,400,000 times per month.
Annual Global Pure User Conference; several active regional Pure User Groups
https://www.elsevier.com/solutions/pure/who-uses-pure
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Client’s are supported by a global team…
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…who delivers on our service promise
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Appendix
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Visuaizing Data in Pure
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Data types in Pure
Some examples
Department
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Person
Some examples
Data types in Pure
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Award
Some examples
Data types in Pure
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Publication
Some examples
Data types in Pure
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Dataset
Some examples
Data types in Pure
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Equipment
Some examples
Data types in Pure
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Activity
Some examples
Data types in Pure
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www.elsevier.com/research-intelligence
Thank you.