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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.