Botswana 30-31 Oct 2017

1. The Role of libraries and information professionals during the Big Data Era.
Data Awareness and Capacity Building Workshop.
National Workshop on Open Data Open Science (ODOS),
University of Botswana Conference Centre.
30th -31st October 2017. Gaborone Botswana.
By
Poloko Ntokwane-University Librarian

2. Outline of the presentation
1. Introduction
2. Definition of Terms and acronyms
3. Characteristic of Big Data
4. Types of Big Data
5. Benefits of Big Data
6. Opportunities for Libraries
7. Challenges
8. New Roles for information professionals
9. Conclusions and Recommendations

3. Introduction
• Society is undergoing profound and rapid changes resulting
from the development of the information superhighway
• According to Cosby (2001) the revolution in information and
communication technologies (ICT) has created a platform for
the free flow of information, ideas and knowledge across the
globe
• The metamorphosis of the library professional to information
profession largely reflects the shifting in the emphasis and
activities aimed at realizing the basic goal of profession that is
to participate and facilitate the creation, transmission and use
of data

4. Definition of Terms
Dan Ariely, 2013 quotes
“Big data is like teenage sex: everyone talks about it, nobody really knows
how to do it, everyone thinks everyone else is doing it, so everyone claims
they are doing it…”
Big Data: “an all-encompassing term for any collection of data sets so large
and complex that it becomes difficult to process using on-hand data
management tools or traditional data processing applications.”
Open Data: “Open data is the idea that some data should be freely
available to everyone to use and republish as they wish, without
restrictions from copyright, patents or other mechanisms of control”
There are three principles to open data which are:
• Availability and Access: that people can get the data
• Re-use and Redistribution: that people can reuse and share the
data
• Universal Participation: that anyone can use the data
Wikipedia

5. Characteristic of Big Data
Figure 1. Characteristics of big data. Source: Hackemoon.com

6. Characteristics Conti…
Volume
The quantity of generated and stored data. The size of the data determines the value
and potential insight- and whether it can actually be considered big data or not.
Variety
The type and nature of the data. This helps people who analyse it to effectively use the
resulting insight.
Velocity
In this context, the speed at which the data is generated and processed to meet the
demands and challenges that lie in the path of growth and development.
Variability
Inconsistency of the data set can hamper processes to handle and manage it.
Veracity
The data quality of captured data can vary greatly, affecting the accurate analysis

7. Types of Big Data
Data Type Examples
Social interactions Online search activities, online page viewers,
blogs and posts, social media activities, audio
images, videos.
Sensors/meters and activity records from
electronic devices
Mobile phones, satellite/GPS devices, climate
sensors, road traffic sensors
Administrative Data Electronic medical records, insurance records,
tax records
Business transactions Bank transactions , online purchases

8. Benefits of Big Data
• New innovations and
• New product opportunities,
• Cost savings
• Efficiencies
• Use predictive analytics that will enable businesses to
understand what their customers want now as well as
in the future

9. Opportunities for Libraries
Data Issue Libraries and data centres opportunities
Availability Lower barriers to researchers to make their data available
Integrate data sets into retrieval services
Findability Support of persistent identifiers
Engage in developing common meta-description schemas and common
citation practices
Promote use of common standards and tools among researchers
Support crosslinks between publications and datasets
Interpretabil
ity
Provide and help researchers understand meta-descriptions of datasets
Establish and maintain a knowledge base about data and their context
Curate and preserve datasets
Archive software needed for re-analysis of data
Re-usability Be transparent about conditions under which data sets can be re-used
(expert knowledge needed, software needed)
Engage in establishing uniform data citation standards
Citability Support and promote persistent identifiers
Transparency about Curation of submitted data
Promote good data management practice
Curation
/Preservatio
n
Collaborate with data creators
Instruct researchers on discipline specific best practices in data creation
(preservation formats, documentation of experiment,)

10. New Roles for information professionals example of
Librarians
Information
Professional
Managing data
licensed data Build
infrastructure
Data advisory
services
Training and
support
Advice on
intellectual
property rights
Coordinate
research data
support -
Build services to
contribute to
institutional
research

11. Challenges
• Budget
• Communicating about changes in the Library
• Declining patron requests for content
• Career advancement
• Keeping up with changing technical requirements
• Understanding research trends & the librarian’s role in the research cycle
• Staying current on policy changes
• Managing library operations and tracking staff performance
• Conveying the value of librarians to researchers
• Managing continuous transition from a print to a digital-based collection

12. Conclusions and Recommendations
Conclusion
It is evident that information professionals have a key
role to play in the era of open data. A new generation
of data scientists have to combine the skills of a
statistician and software programmer along with the
visualization expertise of a graphic designer and a story
teller.
Recommendations

13. Recommendations
• Information professionals and librarians need to know their community research
practices in regards to information use, production, and sharing, and the platforms, tools
and services that they use.
• Advocating and raising awareness: promotion of the benefits of Open Science should
take place in parallel with the development of tools and services, the incentives and
recognition mechanisms that support excellence in Open Science.
• Libraries can advocate within institutions to develop open access policies and
roadmaps. This will benefit not only researchers, but also other stakeholders at
institutional level and international level, and even the whole society, promoting Open
Science and engaging with citizens
• There is need for them to cultivate skills as “data scientists” as well.