Big  Data  Meets  Computer  Science

Jim HendlerTetherless World Professor of Computer, Web and

Data Sciences

Director, Rensselaer Institute for Data Exploration and Applications

@jahendler

The Rensselaer “IDEA” (idea.rpi.edu)The Rensselaer “IDEA” (idea.rpi.edu)

The Rensselaer IDEA 3

… Across Applications (corresponding to Challenges Identified in the Rensselaer Plan 2024)

HealthcareAnalytics

BusinessSystems

Built and NaturalEnvironments

Virtual and Augmented Reality

Cyber-Resiliency

Policy, Ethics andOpen Government

Materials Informatics

Data-driven Physical/Life

Sciences

The Rensselaer IDEA 4

Developing a Comprehensive “Data Science” Research Agenda

P. Fox and J. Hendler, The Science of Data Science, Big Data, 2(2), in press

The Rensselaer IDEA

Graduate Projects in IDEA

• IDEA and CCI (HPC): technologies to enable Rensselaer researchers to work with data at larger scales and in new ways

• Population-scale cognitive computing models for “human intensive” agent-based simulations

• IDEA and EMPAC (Performing arts center): provide next generation data exploration tools

• Multi-person data visualization tools for big-data applications

• IDEA and Watson: New direction in Cognitive Computation

• How do we go from Question/Answering to Open Web Data exploration?

• IDEA and CBIS (Ctr for Biotechnology & Interdisciplinary Studies): Data-driven Informatics

• Can we couple semantics and big data to find new medical uses for already approved drugs?

The Rensselaer IDEA

External Projects and partnerships

Emergency Room CareLanguage and Agents

Largescale Healthcare Analytics

In Discussion Jumpstart (Proposal underway)

Built and Natural Biome data-driven science and engineering

Cognitive Computing Collaborative Research Initiative

Campus Data Infrastructure

Requires going Beyond the Database

Discovery Integrate Visualize Explain

Thinking outside the Database box

Strata talk, 2013 - https://www.youtube.com/watch?v=Cob5oltMGMc

At new scales (and in new ways)

Fox and Hendler, Changing the Equation on Scientific Visualization, Science, 2/11 - http://www.sciencemag.org/content/331/6018/705.short)

A Whole New World

• But what about undergraduate education– where do we train the students who can take

on projects needing• statistics and analytics• informatics• data science challenges• machine learning• unstructured data• cognitive computation• …

Computer Science Education?

• Programming is a necessary skill– not sufficient

• and we mostly teach it wrong…– (For my heresies about teaching programming, see

“Let’s Help Computer Science Students Crack the Code, 3/13 http://chronicle.com/article/Lets-Help-Computer-Science/137649/ )

• The computing environment of today is nothing like the computing environment of the 70s, – but the curriculum hasn’t changed much since I was in

school – but the fundamentals are NOT all the same– data-oriented computations involve graphs, memory

intensive algorithms, machine learning, …

Deploying these ideas at RPI

• Innovation in the interdisciplinary Information Technology Program– Renamed Information Technology and Web

Science, 2011• for more on Web Science, see

– Berners-Lee et al., Creating a Science of the World Wide Web, Science, 2006, https://www.sciencemag.org/content/313/5788/769.summary;

– Hendler et. al, Web Science: An interdisciplinary Approach to Understanding the Web, CACM, 7/2008, http://cacm.acm.org/magazines/2008/7/5366-web-science/fulltext

IT and Web Science

• First IT academic program in U.S.• First web science degree program in U.S.;

First undergraduate web science degree anywhere

• BS in ITWS (20 concentrations) and MS in IT (10 concentrations)

• PhD in Multi-Disciplinary Sciences• http://itws.rpi.edu

– I was Director 2008-2012– Now directed by Peter Fox (whose slides I stole for this

section)

  

 Technical Track Courses

 

  Concentrations

Computer Engineering Track

1) ECSE-2610 Computer Components and Operations2) ENGR-2350 Embedded Control3) ECSE-2660 Computer Architecture, Networking and

Operating Systems

Civil EngineeringComputer HardwareComputer Networking (hardware focus)Mechanical/Aeronautical Eng.

Computer Science Track 1) CSCI-2200 Foundations of Computer Science2) CSCI-2300 Introduction to Algorithms3) CSCI-2500 Computer Organization

Cognitive ScienceComputer Networking (software focus)Information SecurityMachine and Computational Learning

Information Systems Track 1) CSCI-2200 Foundation of Computer Science2) CSCI-2500 Computer Organization3) Four credits from the following: CSCI-2220 Programming in Java (2 credits) CSCI-2961 Program in Python (2 credits) CSCI-2300 Introduction to Algorithms (4 credits) ITWS-49XX Web Systems Development II (4 credits)

ArtsCommunicationEconomicsEntrepreneurshipFinanceManagement Information SystemsMedicinePre-lawPsychologySTS

Web Science Track 1) CSCI-2200 Foundations of Computer Science2) CSCI-2500 Computer Organization3) One of the following: CSCI-49XX Web Systems Development II Web/Data Course approved by ITWS Curriculum

Committee

Data ScienceScience Informatics Web Technologies 

CHANGES TO THE MASTER’S IN INFORMATION TECHNOLOGY

PROGRAM• In Spring 2013 the MS in IT core curriculum was revised

to include Data Analytics.• Networking core classes were replaced with Data

Analytics core classes: Data Science, Database Mining, X-informatics, and Data Analytics (a new class offered in Spring 2014).

• The MS in IT program also added two new concentrations: Data Science and Analytics and Information Dominance.

• The Information Dominance concentration was developed for a new Navy program that will be educating a select group of 5-10 naval officers a year with the skills needed for military cyberspace operations. Two officers started in Fall 2013 and three began in Spring 2014.

IT Core Area Course Number Course Title Term(s) Offered

Database Systems CSCI-4380 Database Systems Fall/Spring

Data Analytics ITWS-6350 Data Science Fall

Software Design and Engineering

CSCI-4440 Software Design and Documentation Fall

ITWS-6400 X-Informatics Spring

Management of Technology*

ITWS-6300Business Issues for Engineers and Scientists (Professional Track Only)

Fall/Spring

Human Computer Interaction

COMM-6420 Foundations of HCI Usability Fall

COMM-696X Human Media Interaction Spring

MS in IT Required Core Courses

* For the research track, replace ITWS-6300 Business Issues for Engineers and Scientists with one of the two semester courses ITWS-6980 Master’s Project or ITWS-6990 Master’s Thesis.

Advanced Core options for students who have previously completed a Core Course

IT Core Area Course Number Course Title Term(s) Offered

Database Systems

CSCI-6390 Database Mining Fall

ITWS-6350 Data Science Fall

ITWS-696X Semantic E-Science Fall

Data Analytics

CSCI-6390 Database Mining Fall

ITWS-6400 X-Informatics Spring

ITWX-696X Data Analytics Spring

Software Design

CSCI-6500 Distributed Computing Over the Internet Fall

ECSE-6780 Software Engineering II Fall

ITWS-696X Semantic E-Science Fall

Management of Technology

MGMT-6080 Networks, Innovation and Value Creation Fall

MGMT-6140 Information Systems for Management Spring

Human Computer Interaction

COMM-6620 Information Architecture Spring

COMM-6770 User-Centered Design Fall

COMM-696X Interactive Media Design Summer

Concentration Course Number Course Name Term(s) Offered

Data Science and

Analytics

Data and Information analytics extends analysis (descriptive and predictive models to obtain knowledge from data) by using insight from analyses to recommend action or to guide and communicate decision-making. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with an entire methodology. Key topics include: advanced statistical computing theory, multivariate analysis, and application of computer science courses such as data mining and machine learning and change detection by uncovering unexpected patterns in data. Select two or three of the following courses:

ITWS-6350 Data Science Fall

ITWS-6400 X-Informatics Spring

ITWS-696X Data Analytics Spring

ITWS-696X Semantic E-Science Fall

ITWX-696XAdvanced Semantic Technologies*

Spring

If only two of the above were chosen, select one more of the following courses:

COMM-6620 Information Architecture Spring

CSCI-4020 Computer Algorithms Spring

CSCI-4150 Introduction to AI Fall

CSCI-6390 Database Mining Fall

CSCI-4220 or CSCI-6220

Network Programming or Parallel Algorithm Design

Spring

ISYE-4220Optimization Algorithms and Applications

Fall

ISYE-6180 Knowledge Discovery with Data Mining

Spring

MGMT-696XTechnology Foundations for Business Analytics

Fall

MGMT-696XPredictive Analytics Using Social Media

Spring

Concentration Course Number Course Name Term(s) Offered

Information Dominance

The Information Dominance concentration prepares students for careers designing, building, and managing secure information systems and networks.  The concentration includes advanced study in encryption and network security, formal models and policies for access control in databases and application systems, secure coding techniques, and other related information assurance topics.  The combination of coursework provides comprehensive coverage of issues and solutions for utilizing high assurance systems for tactical decision-making.  It prepares students for careers ranging from secure information systems analyst, to information security engineer, to field information manager and chief information officer.  It is also appropriate for all IT professionals who want to enhance their knowledge of how to use pervasive information in situational awareness, operations scenarios, and decision-making.

Select two or three of the following courses:

ISYE-6180Knowledge Discovery with Data Mining

Spring

CSCI-6960Cryptography and Network Security I

Fall

ITWS-4370 Information System Security Spring

CSCI-4650 Networking Laboratory IFall/Spring

MGMT-7760 Risk Management Fall

ISYE-4310Ethics of Modeling for Industrial Systems Engineering

Fall

If only two of the above were chosen, select one more of the following courses:

CSCI-6390 Database Mining Fall

CSCI-6968Cryptography and Network Security II

Spring

CSCI-4660 Networking Laboratory IIFall/Spring

ECSE-6860Evaluation Methods for Decision Making

Fall

ISYE-6500Information and Decision Technologies for Industrial and Service Systems

Fall/Spring

CSCI-496XComputational Analysis of Social Processes

Fall

Two New MS in IT Concentrations

Also at RPI

• Data Science Research Center and Data Science Education Center (dsrc.rpi.edu, 2009)

• http://www.rpi.edu/about/inside/issue/v4n17/datacenter.html– Over 45: research faculty, post-docs, grad students, staff,

undergraduates…

• Data is one of the Rensselaer Plan’s five thrusts• Other key faculty

– Fran Berman (Center for Digital Society and RDA)– Bulent Yener (DSRC Director)– Peter Fox(ITWS Director)

More RPI Curriculua

• Environmental Science with Geoinformatics concentration

• Bio, geo, chem, astro, materials - informatics

• GIS for Science

• Visualization (new summer program)

• Multi-disciplinary science program - PhD in Data and Web Science

• DATUM: Data in Undergraduate Math! (Bennett)

• Missing – intermediate statistics

• Graphs – significant potential here – must teach!

5-6 years in…

• Science and interdisciplinary from the start!– Not a question of: do we train scientists to be

technical/data people, or do we train technical people to learn the science

– It’s a skill/ course level approach that is needed

• We teach methodology and principles over technology

• Data science must be a skill, and natural like using instruments, writing/using codes

• Team/ collaboration aspects are key • Foundations and theory must be taught

– for data, as well as programming

Summary