So, you say you are a virtual organization, well ... we all want to change the world. Can we

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So, you say you are a virtual organization, well
... we all want to change the world. Can we?

• Peter Fox (NCAR)
• Virtually in a lot of places

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The long and winding road

• A bit of history
• Some examples
• Some definitions
• Aspects of VOs
• ESIP
• Discussion
• Liner notes

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A bit of history

• 5th Generation of Work
• First generation work was essentially hunting and
  gathering
• Second generation work started farming the land
  and raising crops and other food products
• Third generation work moved to cities with
  factories and small businesses and
• Fourth generation work moved to the office
• Research on organizations dates back to the 50s.

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Examples
The Southern California Earthquake Center (SCEC
http/www.scec.org/) was founded in 1991 to
better forecast and analyze the consequences of
earthquakes, particularly in Southern
California. The collaboration involves more than
600 scientists from 16 core institutions and 46
participating institutions. Over the years, they
have moved toward doing more of their analytical
work through simulations. This workassessing
whether buildings will survive earthquakesrequire
s the integration of multiple disciplines and the
creation of a community modeling
environment. Because building failure is
catastrophic, they need to trust the data they
use in their simulations as well as engender
trust in the professional engineers who rely on
their analyses. Gathering the data that they use
presents challenges for recording, archiving, and
attaching metadata carefully and thoroughly. This
process is even further complicated by the fact
that the occasions to gather data are exactly the
moments when their infrastructure is most likely
to be compromised and when media and emergency
response outlets are most likely to need their
input. This presents unique challenges for
balancing research desires and disaster responses.

• Southern California Earthquake Center

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Examples

• Earth System Grid

The Earth System Grid (ESG http//www.earthsystem
grid.org) was established to enable community
access to, and analysis of, the large data sets
produced by climate simulation models. ESG serves
as a gateway to more than 100 terabytes of
climate model data and supports more than 6,000
registered users. The project team behind this
effort is composed of members from the computer
and computational science, climate, data
management and analysis, and high-end computing
operations communities. The U.S. Department of
Energy funded this collaboration to overcome the
hurdles associated with making environmental
simulation output available to researchers.
Previously, accessing and analyzing the vast
quantities of data produced by the simulations
was cumbersome. To that end, the ESG team has
built a system of rotating storage, deep storage
archives, middleware, databases, and desktop
client applications that alleviate many of the
computational difficulties associated with
climate analysis.
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Examples

• Cancer Biomedical Informatics Grid (caBIG)

The cancer Biomedical Informatics Grid (caBIG
http//cabig.nci.nih.gov) is sponsored by the
U.S. National Cancer Institute (NCI) to support
collaborative cancer research by linking
researchers, clinicians, and patients. Before the
launch of caBIG in 2003, cancer researchers
worked independently, gathering data that could
not be shared across research groups. To address
this problem, caBIG provides open-source software
tools for data collection, management, and
analysis, allowing clinicians to gather, share,
and analyze data more effectively and
efficiently. With these tools, scientists can
search diverse resources for specific data
sources, process large amounts of heterogeneous
data, and coordinate their efforts across
institutions. For the pilot phase from 2004 to
2007, the caBIG community included more than 50
cancer centers and NCI supported research
projects as well as an assortment of 30 Federal,
academic, nonprofit, and industry organizations.
The hope is that with improved interoperability
and affordable tools, the community can meet the
NCI's vision of faster and more effective
treatments for cancer in the years to come.
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Examples

• Lesions (um, I mean lessons) (l)earned
• Users and technologists need each other to
  succeed
• You must have a clear target and know how to
  reach it
• Leadership should be a partnership between
  technologists and domain specialists
• Effective project management is essential at all
  levels
• Clear communication is crucial
• Good software development practices need to be
  established
• Experiment-based software deployment is effective
  for helping users to own the software
• Cyberinfrastructure is a living entity

• Network for Earthquake Engineering and Simulation
  (NEESGrid)

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Definitions

• A VO is a group of individuals whose members and
  resources may be dispersed geographically and
  institutionally, yet who function as a coherent
  unit through the use of cyberinfrastructure (CI).
  
• A VO is typically enabled by, and provides shared
  and often real-time access to, centralized or
  distributed resources, such as community specific
  tools, applications, data, and sensors, and
  experimental operations.

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Another focus on location

• A virtual organization or company is one whose
  members are geographically apart, usually working
  by computer e-mail and groupware - while
  appearing to others to be a single, unified
  organization with a real physical location.

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Another focus on goal

• a geographically distributed organization whose
  members are bound by a long-term common interest
  or goal, and who communicate and coordinate their
  work through information technology

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Roles and relationships

• The virtual research organization in which
  members of various corporate and academic
  research units voluntarily come together to
  advance a technology on an ongoing basis.
• These members assume well defined roles and
  status relationships within the context of the
  virtual group that may be independent of their
  role and status in the organization employing
  them (Ahuja et al., 1998).

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Coupled elements
Technology
Organizational Structure
Communication Patterns
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Communication

• A key feature of virtual organizations is a high
  degree of informal communication
• Because of a lack of formal rules, procedures,
  clear reporting relationships, and norms, more
  extensive informal communication is required.

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Also known as ?

• The term VO can encompass, at least in part,
  systems known by other names such as
  collaboratories Wulf, e-Science or e-Research
  Hey and Trefethen, distributed workgroups or
  virtual teams OLeary and Cummings, virtual
  environments, and online communities Preece.

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Operational Modalities

• Formal or informal
• Planned or unplanned
• Transient or long lived
• May involve, informal exchanges, international
  scientific collaborations, rapid business
  innovation processes, or disaster response teams.

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Characteristics

• Distributed across space, with participants
  spanning locales and institutions
• Distributed across time, with asynchronous as
  well as synchronous interactions
• Dynamic structures and processes at every stage
  of their lifecycle, from initiation to
  termination

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Characteristics

• Computationally enabled, via collaboration
  support systems including e-mail,
  teleconferencing, telepresence, awareness, social
  computing, and group information management
  tools and,
• Computationally enhanced with simulations,
  databases, and analytic services that interact
  with human participants and are integral to the
  operation of the organization.

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Inevitable or enabled?

• The recent blossoming of CI and of Internet
  technologies more generally has put VOs within
  the reach of most people, enabling both the
  support of existing communities through
  technology and the emergence of brand new
  communities.

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Collaboration

• VOs enable, and are enabled by, technologically
  mediated collaboration
• Relationship between VOs and technology
• how information technologies are incorporated
  into, and potentially shape, VO processes and
  procedures, and
• how VO characteristics place demands on
  information technology, and ultimately, how they
  may shape the evolution of that technology

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Collaboration Drivers
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Contrasting
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A few words about leading

• Each instantiation must be led
• Clear role of leader in context of VO and not in
  context of institutional role (unless these
  coincide)
• Some one must have the whole view and be able to
  convey that when required
• Leaders must be able to communicate well and lead
  by example

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Networks versus Webs

• This gets a little too semantic see Julias
  talk
• Network tends to propagate communication through
  it (the network), e.g. an email list, supports
  formal communication
• Web tends to be hyper (more like email)
• Web (and email) supports informal communication
• Network models used extensively, especially
  computing complexity Metcalfes law utility
  of network possible connections O(N2)
• Web model?

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Earth System Grid redux

• Successful but how efficient?
• Multiple leaders
• Communication Post it to the list
• Teams too big, formed, re-formed
• No one with the encompassing view
• Distillation to basic user needs meant success
  high internal to external complexity
• Oh yeah, did I mention the Nobel Prize?

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eGY

• 50th year recognition of IGY
• 2 years of planning for the year (18mo)
• Several themes, 3 successful, 2 unexpected
• Executive played a key role to engender loyalty
  and participation, leadership was key, time and
  effort
• Not a funding program
• Has fringe benefits (like a real organization)
• Definitely a VO! And (in name) it will end!

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Successes focus on value
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Oh yeah VOs and VOs

• Scaling to large numbers of data providers
• Sustainability
• Crossing disciplines and beyond science use
• Data quality
• Branding and attribution (where did this data
  come from and who gets the credit, is it the
  correct version, is this an authoritative
  source?)
• Provenance/derivation (propagating key
  information as it passes through a variety of
  services, processing algorithms, )
• Security, access to resources, policy enforcement
• Interoperability at a variety of levels (3)

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Now for ESIP (dont worry)

• Youve all heard the sausage metaphor
• How does ESIP
• Measure what it does (and who is this reported
  to)?
• Engender loyalty?
• Make it easy to join, leave?
• Carry on activities between bi-annual meetings?

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ESIP consider these

• Organizational structure
• Communication patterns
• Technology
• Goals/Metrics
• Roles and Responsibilities
• Dynamism
• Record
• Place
• Time

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Inventory for your VO
Time
Geographic Place
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Stepping back a bit

• Virtual organization activities know what most
  of them are, learn the new ones adapt
• Is the VO organized so it is agile when needed
  (Teds talk last year)?
• Effective communication is built on content
  manage it, deliver it
• Use cases and baseline metrics value of outcome
  - benefit

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Technology granularity

• Homogeneity versus heterogeneity
• Unsolved e.g.s wikis, languages, identities,
  authentication
• Better e.g.s calendars, timezones
• Virtual machines for specialized functionality
  but how to make the results known to others, and
  even the process

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Concluding remarks (1)

• There as many articles on why VOs fail as there
  are on recipes for success
• Effective, dynamic and agile communication
  patterns seem to underlie success
• Complexity of internals versus externals general
  rules may not apply when the line between
  internal and external is blurred
• VOs seem to be deemed successful when new, or
  limited competition exists

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Concluding remarks (2)

• Are VOs organized or not? Well, yes.
• Large (real) organizations as part of VOs?
• Persistent presence and record of activities and
  process - needed
• Tasks need a means to track them
• Facilitate sustained activities (getting on/
  off), nested VOs
• Be prepared to change your technology, often

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Liner notes

• Material from the NSF workshop BEVO and a report
  from an earlier workshop (Sept. 2007) Beyond
  Being There (2008)
• Material from the NSF solicitation VOSS
• Thanks to the Web! And 4 VOs I work with
• Break-out tomorrow on this subject
• So long and thanks for all the fish