Pedagogy and Scholarship in the Early 21st Century: Rethinking the Role of Technology in the University - PowerPoint PPT Presentation

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Pedagogy and Scholarship in the Early 21st Century: Rethinking the Role of Technology in the University

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Microsoft Research Rick Rashid Sr. VP. Microsoft Research http://www.research.microsoft.com Microsoft Research Founded in 1991 Staff of over 680 in over 55 areas ... – PowerPoint PPT presentation

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Title: Pedagogy and Scholarship in the Early 21st Century: Rethinking the Role of Technology in the University


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Microsoft Research
  • Rick Rashid
  • Sr. VP. Microsoft Research
  • http//www.research.microsoft.com

3
Microsoft Research
  • Founded in 1991
  • Staff of over 680 in over 55 areas
  • Internationally recognized research teams
  • Research lab locations
  • Redmond, WA
  • San Francisco, CA
  • Cambridge, United Kingdom
  • Beijing, Peoples Republic of China
  • Mountain View, CA

4
MSR 2001A year of continued growth
  • Opened MSR Cambridge building on Cambridge
    University campus next to Computer Laboratory
  • MSR China renamed to MSR Asia with continued
    rapid growth
  • Over 200 international publications
  • 4 papers in SIGGRAPH 2002
  • Growing post-doctoral degree program
  • Established new research lab in Mountain View,
    California focused on distributed systems and
    their theory
  • Overall, MSR grew more than 10

5
MSR 2002Full steam ahead
  • Plan to again grow by more then 10
  • Significant growth in all regions with MSR SVC
    set to nearly double
  • MSR technologies are a critical component of
    Microsofts security and code quality initiatives
  • Huge opportunities to work with MS product groups
    to get new technologies into Longhorn Windows
    release

6
Tooltips
7
MS University Engagement
  • Dramatic increase in funding and people devoted
    to working with Universities worldwide
  • Over 35 overall growth
  • Greatest increases will come in Europe and Asia
  • Focus on moving the state of the art forward in a
    number of areas, accelerating scholarship and
    improving pedagogy

8
Rethinking the role of technology in the
University
  • New hardware and software technologies are making
    it possible to rethink the role of computing in
    our lives.
  • For the University, these technologies open the
    door to new approaches to education and
    scholarship.

9
Today
  • Scientists and scholars
  • gather data by direct observation
  • analyze data
  • publish results
  • We share publications online
  • We share data files
  • through FTP and HTTP download
  • Data formats are usually implicit
  • Each researchers has his/her own data
  • Applications often run on individual computers

10
Today Tomorrow
  • Share publications online
  • Share data files (through FTP and HTTP download)
  • Implicit data formats
  • Each researchers has his/her own data
  • Applications run on individual computers
  • Share and annotate publications online
  • Share scholarly and experimental results stored
    in self-describing data structures and accessible
    remotely by distributed applications
  • Common schema for well-understood data
  • Large data sets federated around the world
  • Applications shared over network via
    self-describing interfaces

11
Using technology to accelerate scholarship
  • Massive storage means
  • All the data I gather, experimental results, etc.
    could be kept in database
  • Web services mean
  • My applications and databases could be made
    available to others online for data mining or use
    by other applications
  • Data and code can be self-describing
  • Digital rights management can be used to control
    access to colleagues and students during
    development and later provide for general sharing
    with others

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Global XML Web Services Architecture
Inter Application Protocols
Reliable Messaging
Eventing
Transactions
Building Block Modules
Directory
Referral
Security

Inspection

Routing
License
Description
SOAP
The Internet
HTTP/SMTP
XML
TCP/IP
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Using Web Services to build Data Federations
  • Massive datasets live near their owners
  • Near the instruments software pipeline
  • Near the applications
  • Near data knowledge and curation
  • Super Computer centers become Super Data Centers
  • Each Archive publishes a web service
  • Schema documents the data
  • Methods on objects (queries)
  • Scientists get personalized extracts
  • Uniform access to multiple Archives
  • A common global schema

Federation
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Example TerraServer The Whole Earth
Database
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TerraServer/TerraService
  • Example .NET Service
  • Fall MIT .NET course built around TerraService
  • Key Links
  • http//terraserver.microsoft.com
  • http//terraserver.microsoft.net

17
Production Applications
USDA Soil Data Viewer
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Another Example National Virtual Observatory
  • Premise Most data is (or could be online)
  • So, the Internet is the worlds best telescope
  • It has data on every part of the sky
  • In every measured spectral band optical, x-ray,
    radio..
  • As deep as the best instruments (2 years ago).
  • It is up when you are up.
  • The seeing is always great (no working at
    night, no clouds no moons no..).
  • Its a smart telescope
  • links objects and data to literature on them.
  • http//www.astro.caltech.edu/nvoconf/http//www.v
    oforum.org/

19
Steps to Virtual Observatory
  • Get SDSS and Palomar data online
  • Alex Szalay, Jan Vandenberg, Ani Thacker.
  • Roy Williams, Robert Brunner, Julian Bunn,
  • Do local queries and crossID matches to expose
  • Schema, Units,
  • Dataset problems
  • Typical use scenarios.
  • Define a set of Astronomy Objects and methods.
  • Based on UDDI, WSDL, SOAP.
  • Started this with TerraService http//TerraService
    .net/ ideas.
  • Working with Caltech (Brunner, Williams,
    Djorgovski, Bunn) and JHU (Szalay et al) on this
  • Each archive is a web service
  • Move crossID app to web-service base

20
Sky ServerFind 1 rare star-like objects.
  • Found 14,681 buckets, first 140 buckets have
    99 time 62 seconds
  • CPU bound 226 k records/second (2 cpu)
    250 KB/s.

Select cast((u-g) as int) as ug, cast((g-r) as
int) as gr, cast((r-i) as int) as ri,
cast((i-z) as int) as iz, count()
as Population from stars group by cast((u-g) as
int), cast((g-r) as int), cast((r-i) as int),
cast((i-z) as int) order by count()
21
Sky ServerFind asteroids
  • Sounds hard but there are 5 pictures of the
    object at 5 different times (color filters) and
    so can see velocity.
  • Image pipeline computes velocity.
  • Computing it from the 5 color x,y would also be
    fast
  • Finds 1,303 objects in 3 minutes,
    140MBps. (could go 2x faster with more disks)

select objId, dbo.fGetUrlEq(ra,dec) as url
--return object ID url sqrt(power(rowv,2)powe
r(colv,2)) as velocity from photoObj --
check each object. where (power(rowv,2)
power(colv, 2)) -- square of velocity
between 50 and 1000 -- huge values error
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Find Fast Moving Objects
  • Find near earth asteroids

SELECT r.objID as rId, g.objId as gId,
dbo.fGetUrlEq(g.ra, g.dec) as url FROM PhotoObj
r, PhotoObj g WHERE r.run g.run and
r.camcolg.camcol and abs(g.field-r.field)lt2
-- nearby -- the red selection criteria and
((power(r.q_r,2) power(r.u_r,2)) gt 0.111111
) and r.fiberMag_r between 6 and 22 and
r.fiberMag_r lt r.fiberMag_g and r.fiberMag_r lt
r.fiberMag_i and r.parentID0 and r.fiberMag_r lt
r.fiberMag_u and r.fiberMag_r lt
r.fiberMag_z and r.isoA_r/r.isoB_r gt 1.5 and
r.isoA_rgt2.0 -- the green selection
criteria and ((power(g.q_g,2) power(g.u_g,2))
gt 0.111111 ) and g.fiberMag_g between 6 and 22
and g.fiberMag_g lt g.fiberMag_r and
g.fiberMag_g lt g.fiberMag_i and g.fiberMag_g lt
g.fiberMag_u and g.fiberMag_g lt g.fiberMag_z and
g.parentID0 and g.isoA_g/g.isoB_g gt 1.5 and
g.isoA_g gt 2.0 -- the matchup of the pair and
sqrt(power(r.cx -g.cx,2) power(r.cy-g.cy,2)power
(r.cz-g.cz,2))(10800/PI())lt 4.0 and
abs(r.fiberMag_r-g.fiberMag_g)lt 2.0
23
Role of Technology in the Pedagogy
  • New approaches to pedagogy link professors and
    students through interactive web of services
  • Web service infrastructure provides the means for
    educators to share pedagogy, for students to
    share knowledge and experience and for
    Universities to share information and best
    practices

24
MIT iLab Expanding the reach of laboratories
with Web Services
  • Aeronautics and Astronautics
  • Mechanical structures
  • Wind tunnel
  • Chemical Engineering
  • Chemical reactor
  • Heat exchanger
  • Polymer recrystallization experiment
  • Civil and Environmental Engineering
  • Instrumented flagpole
  • Centrifuge Shaker station
  • Electrical Engineering Computer Science
  • Microelectronics test station

Courtesy Hal Albelson, MIT
25
Remote Microelectronics Characterization Lab
  • Lab can be accessed from anywhere at anytime
  • Single set-up leveraged among many users
  • Minimum staffing requirements
  • Minimum training
  • No user safety concerns

Courtesy Hal Albelson, MIT
26
Web Services for assessmentMIT Online
Assessment Tool
  • Enable academic institutions throughout the world
    to collaborate in administering and evaluating
    online essay tests
  • Web service built on .NET technology
  • One student 6 months
  • Provides local control of tests and
    administrative policies
  • This summer 5 schools/3000 students tested

Courtesy Hal Albelson, MIT
27
Using Web Services to bolster the Intellectual
Commons
  • MIT OpenCourseWare (OCW)
  • Course materials for all MIT courses on the Web,
    open the world
  • DSpace
  • Digital archive for MIT research papers and other
    publications
  • Open Knowledge Initiative (OKI)
  • Open software architecture for university
    learning management systems

Courtesy Hal Albelson, MIT
28
The Role of MSR
  • Expand the state of the art in each of the areas
    in which we do research
  • Rapidly transfer innovative technologies into
    Microsoft products
  • Work with Universities, professors and students
    to improve education, accelerate scholarship and
    create the technologies that will be the future
    of our field

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