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

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Presentation on theme: "No Discipline is an Island No Discipline is an Island: Where Computing and Other Disciplines Meet Lillian (Boots) Cassel Villanova University."— Presentation transcript:

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

2 An Introduction - My journey 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 One of the oldest Bachelors degrees in Computer Science – BA

3 The Journey continues 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

4 Plan for this talk 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

5 Computing Disciplines: The Identity question 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

6 Relationship to other disciplines 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, ….

7 Just what is the computing discipline? Theory Information and Recollection Organizational Context Social Context Computing Infrastructure Interaction Software Design and Development See

8 Theory 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?

9 Information and Recollection 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

10 Social Context Privacy, security, integrity of information Ethics Intellectual property Legal frameworks

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

12 Interaction Communicating a need to a computing system Receiving what is needed from a computing system Graphics, visualization, multimedia, virtual reality, vision, robotics ….

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

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

15 How these relate to others Lets look at a few examples of the ways in which the computing disciplines interrelate with other disciplines Lets 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

16 Data-intensive science First there were theory and experimentation Then, in the earliest days of computing, large scale simulation Next – the Fourth Paradigm, articulated by Microsoft Researchs 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.

17 How much information is there? Data summarization, trend detection anomaly detection are key technologies Yotta Zetta Exa Peta Tera Giga Mega Kilo All books (words) All Books MultiMedia Everything Recorded ! A Photo 24 Yecto, 21 zepto, 18 atto, 15 femto, 12 pico, 9 nano, 6 micro, 3 milli Slide source Jim Gray – Microsoft Research (modified) A Book A movie See Mike Lesk: How much information is there: See Lyman & Varian: How much information Soon most everything will be recorded and indexed Most bytes will never be seen by humans. These require algorithms, data and knowledge representation, and knowledge of the domain

18 Astronomy and Computing 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.

19 Biology

20 New Science 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.

21 The Organization Context 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. -- Information Week - March 7, 2007

22 Not just science and organizations Computational Journalism Social Networks Theatre Music Communications of the ACM Vol. 54 No. 10, Pages /

23 A two-way interaction 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.

24 Two examples Joint appointment – Computer Science and Linguistics – Natural language processing specialist Two brothers – Computer science major, English major

25 Challenges Lots of talk about interdisciplinarity Motivation – Faculty – Institution Some issues – Workload – Tenure – Organizational Culture Current NSF project to explore the issues of motivation and the challenges, and what can be done about them.

26 Connected to everything 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

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


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