my journey to data science · data science is the extraction of actionable knowledge directly from...
TRANSCRIPT
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A journey into Data
Science in Libraries
Luis Martinez-Uribe
Data Scientist
Library
Fundación Juan March
Photo with CC BY-NC-SA 2.0 licence taken from https://www.flickr.com/photos/bg2axk/
Second EDISON Conference - 16 March 2017
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Outline
Data Science My personal journey
Data Science at Fundación Juan March
Training
Looking ahead
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What is Data Science?
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Data science is the extraction of actionable knowledge directly from datathrough a process of discovery, or hypothesis formulation and hypothesis testing.
National Institute of Standards and Technology (NIST) Big Data Working Group (2015)
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Data Science
Statistics
Computer science
Mathematics
Social science
Software engineering
Ethics
Artificial Intelligence
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What is Data Science for?
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What is Data Science for?
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A pathway to Data Science in Libraries
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BSc Mathematics
Social Science Data Librarian
Research Data Management
Data Scientist
MSc InformationSystems
PhD
Sociology
Big Data
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Klavans, Richard and Kevin W. Boyack. (2006). “Quantitative Evaluation of Large Maps of
Science.” Scientometrics 68 (3): 475-499.
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•
•
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Research Data Management
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•
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CURATION
CAPTURE AND STORAGE
ANALYSIS
VIZ AND BI
Tools
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KnowledgePortals
01Our users and visitors
02Classifiers
03Search & recommend
04Vizs
05Analysis of social networks
06
Examples of Data Science Activities
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Knowledge portals
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Our users and visitors
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Classification of our content
Keyword generation for events
Abstract
FormatTitle
...
EVENTS WITH KEYWORDS
(training set)
WORD PROCESSING
(stopwords, expressions)
STATISTICALINDICATORS
(frequency, word length, position,)
PREDICTIVE MODELS (machine learning)
CLASSIFIER(80% precision)
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Search and recommendation systems
Search
Integrating data from 6.000 events, 500 exhibitions and art catalogues and 5.000 Library items
RecommendationsUsing meaningfull words in the title and keywords.
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Interactive web graphs
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Twitter networks and real time sentiment analysis
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Training and education
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Data Science methods
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Big Data technologies
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PhD in Social Sciences, department of sociology
Develop analitical and visual framework for the social analysis of Big Cultural Data from libraries, archives and museums
Photo with CC BY-SA 2.0 licence taken from https://www.flickr.com/photos/seiho/
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datamonster.co
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• the is to ...learn all you
can about your data…from where it was first created.
•Embrace the broader reality…all the information that is yet to be stored in technology.”
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Looking ahead
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Artificial
intelligence
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Looking ahead
"The best prophet of the future is the past." Lord Byron
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Thanks
@luismart
es.linkedin.com/in/luismartinezuribe