Transcript So, you say you are a virtual organization, well we all want to

A Woods Hole Virtual
Organization?
Peter Fox (RPI and WHOI)
Virtually: in a lot of places
What’s ahead
 A bit of history
 An example
 Some definitions and characteristics
 Aspects of VOs to consider
 Some experience
 Opportunities for Woods Hole
 Discussion and concluding remarks
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 50’s.
Examples
 Earth
System
Grid
The Earth
System Grid
(ESG; http://www.earthsystemgrid.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.
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.
Another – focus on location
 A virtual organization or company is one
whose members are geographically
apart, usually working by computer email and groupware - while appearing
to others to be a single, unified
organization with a real physical
location.
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
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).
Coupled elements
Technology
Organizational
Structure
Communication Patterns
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.
Also known as … ?
 The term VO can encompass, at least in
part, systems known by other names
such as collaboratories [Wulf], eScience or e-Research [Hey and
Trefethen], distributed workgroups or
virtual teams [O’Leary and Cummings],
virtual environments, and online
communities [Preece].*
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.
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;
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.
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.
Collaboration Drivers
Collaboration
 VOs enable, and are enabled by,
technologically mediated collaboration
 Relationship between VOs and technology:
1. how information technologies are incorporated
into, and potentially shape, VO processes and
procedures, and
2. how VO characteristics place demands on
information technology, and ultimately, how they
may shape the evolution of that technology
 VOs are an Informatics field of study
(Re)emergence of
Informatics
There is/- was
still a science
gap between
• Informatics
information
includes the
science
and and)
the underlying
science
of (data
information, the practice
ofinfrastructure
information processing,
and the engineering
and technology
that is
ofavailable
information systems. Informatics studies the
structure, behavior, and interactions of natural
artificial systems thatis
store,
• and
Cyberinfrastructure
the process
new and
communicate
(data and) information.
It also
research environment(s)
that support
develops
its own
conceptual
and theoretical
advanced
data
acquisition,
data
foundations.
Sincemanagement,
computers, individuals
storage, data
data and
organizations
process
information,
integration,alldata
mining,
data
informatics
has computational,
cognitive and
visualization
and other computing
social
including
study of the
social
and aspects,
information
processing
services
impact
information
over of
the
Internet.technologies. Wikipedia.
Fox Informatics and Semantics,
© 2008
19
Contrasting a Virtual Information
Organization with a Traditional one
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
Networks versus ‘Webs’
 This gets a little too semantic …
 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’ & Metcalfe’s law: utility
of network ~ possible connections O(N2)
 What is the law for the web model? Power law?
Earth System Grid redux*
Successful but how efficient?
Multiple leaders
Communication: We had to “Post it to the list”
Teams too big, formed, re-formed
No one with the encompassing view but use
cases may have saved the day
 The distillation to basic user needs meant
success; high internal to external complexity
ratio
 Oh yeah, did I mention the Nobel Prize?

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
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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 work—assessing whether buildings will survive earthquakes—requires
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
Remote Users
(Faculty,
Students,
Practitioners)
Instrumented
Structures
and Sites
NEES Resources
Simulation
Tools
Repository
Lesions (um, I mean lessons) (l)earned
Users and technologists need each other to succeed
2. You must have a clear target and know how to reach it
3. Leadership should be a partnership between technologists and
Laboratory
Equipment
domain specialists
Field Equipment
4. Effective project management is essential at all levels
5. Clear communication is crucial
6. Good software development practices need to be established
7.Curated
Experiment-based
software deployment is effective for helping
Data
Repository
users to own the software
Leading Edge
8. Cyberinfrastructure
is
a
living
entity
Global
Computation
1.
Connections
Remote Users:
Laboratory Equipment
(K-12 Faculty and
Students)
Electronic Geophysical Year

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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
Very simple structure
Not a funding program
Has fringe benefits (like a real organization)
Definitely a VO! And (in name) it has ended!
www.egy.org
Climate and Weather of the
Sun-Earth System (CAWSES)
 2004-2008 (I) and now 2009-2013(II)
 Builds on 3 previous programs –
decades of history but the foci changes
 Tasks (6) (one on eScience and
Informatics! And Virtual Institute)
 International community, regular
meetings and project office
 Has conducted several successful virtual
workshops
Successes focus on value
Use cases
 IMHO: VOs succeed more often when they
are formally use case driven
 Can be used for big goals, small goals,
science and technical (more sustained)
 Are great for capturing state and value
 Have greater value when joined with input
and output metrics (i.e. is anything
valuable being done?)
Short story
 Looking back to look forward; treat VOs
as semi-empirical constructs
 Plenty of experience gained
 delayed value if we learn what outcomes
were valued and what were not and how
the VO achieved that (or not)
Stepping back a bit
 Virtual organization activities: leaders within a VO must
know what most of them are, learn the new ones;
adapt
 It seems essential that a VO is organized so that it is
agile when needed (numerous books on this for
organizations) and sustainable and resilient to when
people are in the VO and when they are not
 Effective communication is built on content; manage it,
deliver it
 Use cases and baseline metrics – value of outcome ->
benefit
Suggest: VOs consider these
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Organizational structure:
Communication patterns:
Technology:
Goals/Metrics:
Roles and Responsibilities:
Dynamism:
Record:
Place:
Time:
Inventory for your VO
Time
Same
Geographic Place
Same
Different
Organizational structure:
Communication patterns:
Technology:
Goals/Metrics:
Roles and Responsibilities:
Dynamism:
Record:
Organizational structure:
Communication patterns:
Technology:
Goals/Metrics:
Roles and Responsibilities:
Dynamism:
Record:
Different Organizational structure:
Communication patterns:
Technology:
Goals/Metrics:
Roles and Responsibilities:
Dynamism:
Record:
Organizational structure:
Communication patterns:
Technology:
Goals/Metrics:
Roles and Responsibilities:
Dynamism:
Record:
State of the VO
 The higher degree of casual exchange
means that it is harder for most (inside
and outside the VO) to know its state
and direction
 All the relevant information on the state
exists but no coherent view of it may
exist
 What is the situation with WH?
A Woods Hole VO?
 Marine Biology Laboratory
 National Academy of Sciences
 NOAA Fisheries
 SEA
 USGS
 Woods Hole Foundation
 Woods Hole Oceanographic Institution
 Woods Hole Research Center … others
Mission clash?
Does funding help or hurt?
Goal, geography, gestalt?
 What are the goals that bring WH
together?
 Ocean/marine data?
 Policy?
 Education?
 …?
 Name it, form it
 Give it a lifetime
Woods Hole <what>
 June 2009-2011
 Consider an eGY/CAWSES approach
 This is what we can discuss afterwards
(a few more slides)
Concluding remarks (1)
 There as many articles on why VOs fail as there
are on recipes for success – likely that there is no
one recipe -> semi-empirical approach
 Effective, dynamic and agile communication
patterns seem to underlie success
 Size and working history are very important (7-9)
 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
Concluding remarks (2)
 Are VOs organized or not? Well, yes.
 Emerging trend for large (real) organizations to be
part of VOs. What have we learned about the rules of
engagement?
 Persistent presence and record of activities and
process – needed: state and metrics/ value
 Facilitate sustained activities (getting on/ off),and
support the notion of nested VOs
 A VO must be prepared to change technology, often
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, talks at ESIP, NSF, CAWSES.
 Thanks to the Web! And > 8 VOs I
work(ed) with
Comment: Translucent VOs
 Along the spectrum from opaque (bad) to
transparent (unsustainable) is a balance
 Applies to (at least) leadership, communication,
feedback
 Posit: balance arises out of flowing
requirements consistently to the working level
of the VO and percolating direct experience and
outcomes up (see state and use cases)
 Usually depends on the right person