No Discipline is an Island: Where Computing and Other Disciplines Meet
Lillian (Boots) Cassel
Villanova University

• Questions from the bingo game:
– Have never lived in a big city
• Wilmington DE used to be close to 100,000, but is smaller now
– Can sew
• Purple dragon with pink scales, Williamsburg dresses, …
• Also knit and crochet and make quilts
– Have a pet – Siamese cat, Sofi
– Have roller skated (no roller blades, though)
– HS Graduation class of < 100 (63, actually)
– Wear a ring (married for 44.5 years, 3 sons, 7 grandchildren)
– First in my family to attend college
– Know at least three programming languages
• Assembler, Fortran, COBOL, Algol, Pascal, Python, some Perl, Java,
APL, PL/!, Basic, …
• First Computer: Bendix G15. Paper tape. Then IBM 1620.
• One of the oldest Bachelor’s degrees in Computer Science
– BA

• As Patty Lopez said, it is the journey, not the destination, that makes life interesting
• Professor of Computing Sciences
• Past chair, Computing Accreditation Commission
• Past chair, ACM SIGCSE
• Past Program Officer (Rotator) NSF DUE
• Member ACM Education Board
• Visiting Scholar, DILL program, Parma Italy
• odds and ends of interesting things

• Computing Disciplines: The Identity question
– What constitutes the computing disciplines
– How do we see ourselves and how do others see us?
• Interdisciplinarity
– The growing role of computing in all disciplines
– A two-way relationship
– The challenges
• Computing – the discipline that lets you be in whatever field appeals to you now

• Identity questions
– who are we? what do we contribute?
• Internal divisions
– Computer Science, Computer Engineering, Software
Engineering, Information Systems, Information
Technology, Information Science …
• External views
– Source of tools.
– “Computer expert”
– Way of approaching problems?
• Computational (or Algorithmic) Thinking

• Every field depends on computers
– Not much disagreement with that
• Every field depends on computing
– Not so clear. What is the difference?
• Computing also depends on other fields
– We receive as well as give
– Mathematics, of course
– Also, psychology, linguistics, sociology, communication, ….

• Theory
• Information and Recollection
• Organizational Context
• Social Context
• Computing Infrastructure
• Interaction
• Software Design and Development
See www.distributedexpertise.org/computingontology/

• Every true discipline has a theoretical base
• For computing, this includes
– Algorithms, design strategy and complexity analysis
• How do we approach solving a class of problems
• How practical are the resulting solutions
– Automata and formal language theory
• What types of problems can we express
• How do we distinguish problems that cannot be solved explicitly?
• How do we decide on appropriate approximations when complete solutions are not possible?

• Databases
• Unstructured data
• Understanding data, making it informative
• Addressing a specific information need
• Preservation of materials as technology changes
• Capturing, Organizing, Summarizing,
Analyzing, Visualizing*
* Jim Gray summary

• Privacy, security, integrity of information
• Ethics
• Intellectual property
• Legal frameworks

• Digital Systems
• Machine Organization
• Multiprocessing, parallel systems, cloud computing
• Encoding, representation
• Networks and communication
• Systems Security, authentication, protection

• Communicating a need to a computing system
• Receiving what is needed from a computing system
• Graphics, visualization, multimedia, virtual reality, vision, robotics ….
• APIs and other communication among systems

• Software engineering
• Knowledge representation, reasoning
• Programming languages, and paradigms
• Modeling
• Systems development and life cycle
• Verification and validation

• Policies and Planning
• Forensics
• Requirements analysis and specification
• Systems and project management
• Structure and management of IS functions
• Quality of Service

• Let’s look at a few examples of the ways in which the computing disciplines interrelate with other disciplines
• Let’s start with a very visible impact – information
– Information overload, information avalanche
– The terms vary but the message always suggests a need for something beyond historical methods of dealing with data and information

• First there were theory and experimentation
• Then, in the earliest days of computing, large scale simulation
• Next – the Fourth Paradigm, articulated by
Microsoft Research’s Jim Gray:
The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies.
http://research.microsoft.com/en-us/collaboration/fourthparadigm/

• Who is/was Jim Gray?
• What kind of work best describes his career?
• What is his official status now?
• When did that become official?

Soon most everything will be recorded and indexed
Most bytes will never be seen by humans.
Data summarization, trend detection anomaly detection are key technologies
These require algorithms, data and knowledge representation, and knowledge of the domain
The smaller scale:
Everything
Recorded !
All Books
MultiMedia
All books
(words)
24 Yecto, 21 zepto, 18 atto, 15 femto, 12 pico, 9 nano, 6 micro, 3 milli
See Mike Lesk:
How much information is there: http://www.lesk.com/mlesk/ksg97/ksg.html
See Lyman & Varian:
How much information http://www.sims.berkeley.edu/research/projects/how-much-info /
Slide source Jim Gray – Microsoft Research (modified)
A Photo
A Book
Yotta
Zetta
Exa
Peta
Tera
Giga
Mega
Kilo

• The Large Synoptic Survey Telescope (LSST)
Over 30 thousand gigabytes (30TB) of images will be generated every night during the decade-long LSST sky survey.
LSST and Google share many of the same goals: organizing massive quantities of data and making it useful.
http://lsst.org/lsst/google

This data-driven modeling and discovery linkage has entered a new paradigm. The acquisition of scientific data in all disciplines is now accelerating and causing a nearly insurmountable data avalanche. It is no longer possible for humans to look at any representative fraction of the data.
Instead, we may be looking over the shoulders of assisted learning machines at innovative visualizations of metadata. Discoveries will be made via searches for correlations. The role of the experimental scientist increasingly is as inventor of ambitious new searches and new algorithms. Novel theories of nature are tested through searching for the predicted statistical relationships across big data bases. With this accelerated advance in data generation capability, we will require novel, increasingly automated, and increasingly more effective scientific knowledge discovery systems.
http://www.lsst.org/lsst/science/technology

• “Last year, 161 exabytes of digital information were created and copied, according to research firm IDC.”
• “While nearly 70% of what IDC is calling the digital universe will be generated by individuals over the next three years, most of this content will be touched by a business or government agency network along the way -- it will be held in a data center or at a hosting site, it will travel over a telephone wire or Internet switch, or it will be stored in a backup system.
• Those organizations, IDC said, will be responsible for the security, privacy, reliability, and compliance of at least 85% of the information.” http://www.informationweek.com/news/197800880 -- Information Week - March 7, 2007

• Did you notice the cover of the CACM issue that highlighted biology? What other subject appeared there?
• Computational Journalism
Pages 66-71

• Social Networks
– Much research underway that is fueled by the data available from sites such as Facebook,
LinkedIn, etc.
• Theatre
• Music
Music majors Maggie Dougherty and Mike McKendry work with computer science major Sophanna Son to figure out the best way to implement a composition program that reflects the way a musician thinks about the problem.
http://www.uml.edu/News/stories/2011-
12/Computing-Music.aspx

• It is easy to focus on what computing gives to other disciplines
• The other side is just as important, not so well recognized
– How can we develop social networks, without sociology?
– How can we develop good interfaces, without psychology?
– etc.

• Bottom line –
• The need for computing in nearly everything makes computing a great choice of specialization if you are not sure what interests you most – or what will interest you in a few years
– Study computing …. do anything you like

• Please go to computingportal.org
• Look for the community: Interdisciplinary
Computing
– Join the group
– Read the materials
– Comment, participate in discussions