DATA
MANAGEMENT
AND
SHARING
2021-09-27
Presenters:
Ali Muhammad (2021A800761004) Pakistan
Safdar Mehmood (2021A8015926007) Pakistan
Madeleine Udahgora (2021A8010210004) Rwanda
Rotamond Twum Barimah (2021B8017708001) Ghana
Lecturer
Moderator
PRESENTATION FLOW
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Introduction
 Data Management & Sharing
 Types of Data
 Goals of Data Management
Research Data Management
Open Science
Data Sharing: Degrees of Openness
Data Sharing Boosts Citation
Goal of Data Management
Data Management Platform
Current Developments
Data Management Processes
The Benefits of Data Management Include
Data Security
Current Developments
References
Data
Facts and statistics collected together for reference or analysis.
Types of Data
 Primary
Data
 Primary
data is an original and unique data, which is directly
collected by the researcher from a source according to his
requirements.
 It
is the data collected by the investigator himself or herself for a
specific purpose.
 Secondary
Data
 Secondary
data refers to the data which has already been
collected for a certain purpose and documented somewhere else.
 Data
collected by someone else for some other purpose (but
being utilized by the investigator for another purpose) is secondary
data.
INTRODUCTION
 Data:
DATA
Facts and statistics
collected together
for reference or
analysis.
KNOWLEDGE
is a combination of
“Data” and
“Information”
combined with
experience, expert
opinion, and skills
resulting in a valuable
asset that helps
decision making.
INFORMATION
Data that has been
categorized, analyzed
and organized to have
structure and meaning
INTRODUCTION
Data
Management:
“Data
management
is
the
practice
of
collecting, keeping, and using data securely,
efficiently, and cost-effectively.”
Why YOU need a data management plan
The following appeared on noticeboards in
the Chemistry Department –
the Panton Arms
https://blogs.ch.cam.ac.uk/pmr/2011
/08/01/why-you-need-a-data-management
-plan/
INTRODUCTION

Data Sharing:
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Data sharing is the practice of making data used for scholarly
research available to other investigators.
 The
method of making data used for your research available to
others through a variety of mechanisms.
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Many funding agencies, institutions, and publication venues
have policies regarding data sharing because transparency
and openness are considered by many to be part of
the scientific method.
INTRODUCTION
Data
Sharing means the provision by a data holder
of data to a data user for the purpose of joint or
individual use of the shared data, based on
voluntary agreements, directly or through an
intermediary;
DATA SHARING
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Data sharing have three types:

Sharing data between functional units.
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Sharing data between management units.

Sharing
data
between
dispersed locations.
geographical
Research Data Management
The active management of data throughout the lifecycle
 Data Management Planning
 Creating data
 Documenting data
 Accessing / using data
 Storage & backup
 Selecting what to keep
 Sharing data
 Data licensing and citation

Preserving data
Open Science
“Science
carried out and interconnected in a way
which permits others to contribute, collaborate and
add to the research effort, with all categories of data,
results and protocols made freely accessible at
different stages of the research process.”
Open Science
“Open data and content can be freely used modified
and shared by anyone for any purpose.” https://opendefinition.org/
 Make your stuff available on the Web (whatever
format) under an open license
Make it available as structured data (e.g. Excel instead
of a scan of a table)
Use non-proprietary formats (e.g. CSV instead of
Excel)

Data Sharing: Degrees of Openness
Open
Content that can be
freely used, modified
and
shared
by
anyone
for
any
purpose Limits on
who can use the data
Restricted
How or for what
purpose - Charges
for use - Data
sharing
agreements
Closed
Unable to share
Open Accessed Data
Examples of Data Catalogue:
 https://dataverse.no/dataset.xhtml?persistentId=doi:10.18710/CZRK
NZ
 https://magda.io/
 https://www.amundsen.io/
 https://atlan.com/
 https://rigorousthemes.com/blog/best-open-source-data-catalog/
 https://ckan.org/
Legal and Ethical Aspects - Licensing
 The given link can help to license your data for reuse.
Useful link: https://www.openaire.eu/guides
Open Accessed Research &Academic Data

Millions of Non-fiction / Sci-tech, Fiction, Scientific articles and
Magazines are freely available on the following link:
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https://libgen.is/
 Numerous

research papers can be retrieved from
https://sci-hub.mksa.top/
Data Sharing Boosts Citation
“studies that made data available in a
public repository received 9% more
citations than similar studies for which the
data was not made available”
For example
Research gate
Goal of Data Management
The
goal of data management is to help
people, organizations, and connected
things optimize the use of data within the
bounds of policy and regulation so that
they can make decisions and take actions
that maximize the benefit to the
organization.
Data Management Platform
 A data management platform is the foundational system for
collecting and analyzing large volumes of data across an
organization. Commercial data platforms typically include
software tools for management, developed by the
database vendor or by third-party vendors. These data
management solutions help IT teams and DBAs perform
typical tasks such as:
 Identifying, alerting, diagnosing, and resolving faults in the
database system or underlying infrastructure
 Allocating database memory and storage resources
 Making changes in the database design
 Optimizing responses to database queries for faster
application performance
Data Management Processes
 Data management involves:
 Deciding
what data standards to follow
 Formatting
data
 Transcribing
and/or translating data
 Anonymizing
 Writing
(if needed)
documentation / providing context
 Creating
 Backing
metadata
up / storing data
 Securing
data
Data Management Processes
 Data
Sharing File Formats:
 Quantitative tabular data with extensive
metadata
 .por , .mdb/.accdb
 Quantitative tabular data with minimal
metadata
 .csv , .tab , .txt , .xls/.xlsx ,
.mdb/.accdb .dbf , .ods
 Geospatial data
 .shp, .shx, .dbf, .prj, .sbx, .sbn, .tif,
.tfw, .dwg
 Data can be shared through Archive
file formats for encypting
 Qualitative
data
 .txt, .xml, .rtf, .html,
.doc/.docx, .tex,
 Digital image data
 .tif, .tiff, .jp2, .pdf
 Digital audio data
 .flac, .mp3, .wav, .aif
 Digital video data
 .jp2, .mj2,
 Documentation & Scripts
 .rtf, .odt, .htm, .html, .txt, .xls/
.xlsx, .xml, .pdf
DATA SHARING
 Organizational

Networking:
It is the concept of sharing vital information, details, stats, or
insights across departments to create a more efficient organization.
 Network
sharing is feature that allows resource to be shared over a
network, be they files, documents, folders, media, etc.
 These
are made accessible to other users/computers over a
network.
The Benefits of Data Management Include
 Improved
operations management.
 More effective marketing and sales.
 Better regulation and compliance controls.
 Enhanced security and privacy.
 Reduction of risk across the board.
 Faster application and system development.
 Improved decision making and reporting.
 Sustained business growth.
 Business and technical alignment.
 Automated and/or streamlined operations.
 Greater collaboration and revenue growth.
 More consistency across all enterprise processes.
DATA SHARING
Returns for institutions:
“If an institution consumed A$10 million on data,
what would be the return? The answer is: more
publications; an increased citation count; more
grants; greater profile; and more collaboration
www.ariadne.ac.uk/issue72/oar-2013-rpt
DATA SECURITY
Common Themes
Loss/Theft of unencrypted data laptops and memory sticks
 Insecure disposal of personal data
 Lost records
 Information posted, faxed, or emailed to the wrong
recipient
 Lack of staff training and proper procedure
 Insecure websites
 Remote working

Current Developments
 Current
Developments in Data Management & Sharing:
In our digital world, data pours into organizations
from many sources – operational and transactional
systems, scanners, sensors, smart devices, social
media, video and text. But the value of data is not
based on its source, quality or format. Its value
depends on what you do with it.
REFERENCES
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Khatiwada, R. P., Pradhan, B. L. & Poudyal, N. (2015). Research
Methodology. KEC Publication, Kathmandu.
Kumar, Ranjit. Research Methodology: A Step-by-Step Guide for
Beginners. Los Angeles: SAGE, 2011. Print.
A Global Health Epidemic Is A Ticking Time Bomb - But Virus Databases
Can And Are Helping To Save Lives". HuffPost UK. Retrieved 2017-09-06.
Managing and Sharing Research Data Sarah Jones DCC, University of
Glasgow
sarah.jones@glasgow.ac.uk
Twitter:
@sjDCC
#fosteropenscience Open Science Days 2015, 21st & 23rd April, Prague &
Brno http://foster.czu.cz/?r=6661
Overview of the workshop • Data sharing policies • Benefits of data
sharing • Data repositories • Preparing data for sharing • Re-using data •
Questions/further information