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Title: ENVIRONMENTAL INFORMATICS (1)


1
ENVIRONMENTAL INFORMATICS (1)
  •  Draft outline of a discipline devoted to the
    study of environmental information
  • creation, storage, access, organization,
    dissemination, integration, presentation and
    usage
  • Rudolf B. Husar
  • Center for Air Pollution Impact and Trend
    Analysis (CAPITA)
  • Washington UniversitySt. Louis, MO 63130
  • September 1992

2
ENVIRONMENTAL INFORMATICSApplication of
Information Science, Engineering and Technology
to Environmental Problems
  • Rudolf B. Husar
  • Director, Center for Air Pollution Impact and
    Trend Analysis
  • Washington University, St. Louis, MO
  •  
  • Environmental information is becoming
    unmanageable by traditional methods.
  • There is a need to develop effective methods to
    store, organize, access, dessimilate, filter,
    combine and deliver this peculiar resource.
  • Information science is to explain information as
    a resource and the manner in which it is created,
    transformed and used.
  • Information engineering deals with the design of
    information systems, while information technology
    deals with the actual processes of storage
    transformation and delivery
  • Presented topics will include information as a
    resource user driven data model value-added
    processes application of database, geographic
    information systems, hypertext, multimedia,
    expent system technologiesand the integration of
    these technologies into information systems.
  • The principles of Environmental Informatics will
    be discussed in the context of Global Change
    databases organized by ORNL-CDIAS, NASA and by
    Washington University.
  • The talk will be augmented a live demonstration
    of the Voyager 1 Data Delivery System that
    combines database, GIS, hypertext, direct
    manipulation and multimedia technologies.

3
THE PROBLEM
  •  
  • The researcher cannot get access to data
  • if he can, he can not read them
  • if he can read them,
  • he does not know how good they are
  • and if he finds them good
  • he can not merge them with other data
  •  
  •  
  •  
  • Form
  •  
  • Information Technology and the Conduct of
    Research
  • The Users View.
  • National Academy Press, Washington, D.C. 1989

4
 DATA PATHWAY
  •  DATA PATHWAY
  • Monitoring Site
  • Principal Investigator
  • Information Centers

5
INFORMATICS - THE SCIENCE
  • Systems exists that organize, store, manipulate,
    retrieve, analyze, evaluate, and provide
    information in various chunks to a variety of
    people.
  • The practice of informatics has evolved from
    professional know-how and technology, not as a
    product of 'basic' research.
  • Informatics is in a prescientific stage of
    naming, taxonomy, descriptions and definitions.
  • First we need to understand how existing
    information systems work.
  • Next we need to formulate a model of these
    practices components, activities, values added,
    clients served and the problems solved by the IS.
  • Finally, we have to apply the newly gained
    insights (science) to the design of better IS.
  • Note The steam engine was used in practice well
    before the Carnot cycle theory was invented.
  • SCIENCE
  •  
  • The field is in pre-scientific stage. Mostly
    taxonomy of working systems.
  •  
  • Goals Understanding the forms of environmental
    knowledge
  • Usages of environmental knowledge
  • Processes of new knowledge creation
  • Informatics is in a pre-scientific stage of
    naming, taxonomy, descriptions and definitions.
    However, information systems exists that
    organize, store, manipulate, retrieve, analyze,
    evaluate, and provide information to a variety of
    people.
  • Practical information management has evolved from
    professional know-how and technology, not as a
    product of 'basic' research. In order to develop
    the science and engineering
  • First we need to understand how existing
    information systems work.

6
 INFORMATICS - THE ENGINEERING
  •  
  • Information systems exists that organize, store,
    manipulate, retrieve, analyze, evaluate, and
    provide information in various chunks to a
    variaty of people.
  • Design of information storage and flow systems.
    Emphasis on user driven design to complement
    technology and content driven info flows.
  •  
  • Goals Augment human decision and learning
    processes.
  • Unite data and metadata
  • Reduce resistances to info flow
  • The activities of information engineering
    include
  • Matching the information need of the user to the
    information sources, using available technology.
  • Develop methodologies for the organization,
    transformations and delivery of environmental
    data/information/knowledge.
  • Identify the key information values and the
    processes that will enhance those values.
  • Seek out a set of universal values that can be
    added to information, that are independent of the
    user environment ( i.e. accessibility, common
    coding, and documentation).
  • Develop new tools that will enhance and augment
    the human mind in dealing with environmental
    information, e.g. to minimize the 'info-glut'.

7
 INFORMATICS - THE TECHNOLOGY
  • The information revolution is driven by the
    confluence of comuter hardware, software and
    communications technologies.
  • Hardware Computers, communications,
    microelctronics.
  • Software Database, hypertext, geographic
    information systems (GIS), hypertext, multimedia,
    object orientation.
  • Communications Wide area (Internet) and local
    networks bulletin boards, CD ROM.
  • Intellectual Technologies Indexing,
    classification/organisation, searchning,
    presenting.
  • These technologies provide the hope to overcome
    the information/data glut.
  • Develop knowledge and data storage, delivery and
    processing systems.
  • Goals Merge database, hypertext, numerical
    modeling technologies
  • User programmable, socially well behaving info
    systems
  • Ultimately interoperable with the universe
  • Information systems are implemented using
    suitable technologies. The information revolution
    is driven by the confluence of computer hardware,
    software and communications technologies.
  • Hardware Computers, communications,
    microelectronics.
  • Software Database, hypertext, geographic info
    systems (GIS), multimedia, object orientation.
  • Communications Wide area (Internet) and local
    networks bulletin boards, CD ROM.
  • Intellectual Technologies Indexing,
    classification/organization, searching,
    presenting.
  • These technologies along with developments in
    information engineering and science provide the
    hope to overcome the information/data glut.

8
USER-DRIVEN INFORMATION PROCESSING
  •   Action
  • matching goals
  • compromising DECISION
  • bargaining PROCESSES
  • choosing
  • Productive Knownledge
  • presenting
  • options JUDGMENTAL
  • advantages PROCESSES
  • disadvantages
  • Informing Knowledge
  • separating
  • evaluating
  • validating ANALYZING
  • interpreting PROCESSES
  • synthesizing
  • Information
  • grouping
  • classifying ORGANIZING

9
  • VALUE ADDED PROCESSES
  • Metaphors are useful in describing new,
    unfamiliar topics. Environmental Information
    systems can be viewed as refineries that
    transform low-value data into information and
    knowledge through a series of value-adding
    processes.
  • Data constitute the raw input from which
    productive knowledge, used for decision making is
    derived.
  • Data refers to numbers, files and the associated
    labeling that describes it. Data are turned into
    information when one establishes relationships
    among data, e.g. relational database. Informing
    knowledge educates while productive knowledge is
    used for decision making.
  • In fact, one of the practical definitions of
    knowledge is 'whatever is used for
    decision-making'.

10
USES OF ENVIRONMENTAL DATA
  • Environmental data/information is used to
  •  
  • Provide Historical Record
  • Identify Deviation from Expected Trend
  • Anticipate Future Environmental Problems
  • Provide Legal/Regulatory Record
  • Support Research
  • Support Education
  • Support Communication
  •  
  • The main uses are in science, education and to
    support regulations.

11
CONTENT, TECHNOLOGY AND USER DRIVEN DATA FLOWS
  • Most agencies are disseminating information
    relevant to their own domain of activity. Such
    data flow is content driven.
  • New technologies such as the papyrus, printed
    book, CD-ROM and computer networks provide bursts
    of information flow resulting in
    technology-driven information flows.
  • However, in scientific, educational, and
    regulatory use of environmental data, there is a
    need for compatible information from various
    domains, requiring data merging and synthesis.
    Such data flow is user driven since the user
    dictates the form, content and flow of the data.
  • Content and technology-driven data flows are fine
    but they are inadequate to handle modern
    information needs. The challenge is to develop
    the user-driven model and to reconcile and
    integrate it with the other models.

12
ENVIRONMENTAL INFORMATICS
  •  
  • The study of environmental information and its
    use in environmental management, science and
    education.
  • More than the study of computers in
    environmental information. It's focus is on the
    environmental field, rather then on computers and
    the technology.
  • Pressedent Medical Informatics, a mature field
    with a goal, domain, textbooks, college courses,
    research groups and funding agencies.
  • ENVIRONMENTAL INFORMATICS, EI
  • A tentative definition of EI is
  • The study of environmental information and its
    use in decision making, education and science.
  • EI focuses on the environmental field, rather
    then on computers and the technology. It's
    approach is to systematically study environmental
    information, as branches of science, engineering
    and technology.
  • Much of the presentation below is a synthesis of
    ideas 'borrowed' and adopted to the environmental
    field.
  • There is precedent Medical Informatics, a mature
    field with a goal, domain, textbooks, college
    courses, research groups and funding agencies.
  • Other relevant fields include library sciences,
    management sciences, information engineering.

13
INFORMATION AS A RESOURCE
  • Environmental information and information in
    general has several unique characteristics. In
    the post-industrial era, material goods were
    replaced by information as the commodity of
    transactions. It became a resource in itself.
  • As other resources, information needs to be
    acquired, organized and distributed i.e. managed.
    However, it is a remarkable resource
  • It can not be depleted by use.
  • In fact, it expands and gets better with use.
  • Information is not scarce it is in chronic
    surplus.
  • Scarcity is in time to process it into
    knowledge.
  • The processing costs are borne by the info
    user.
  • Info can be owned by many at the same time.
  • It is shared, not exchanged in transactions.
  •  
  • Therefore, one must develop different tools from
    those that proved useful for natural, capital,
    human and technological resource management.

14
 DATA FLOW IMPEDIMENTS
  •  DATA FLOW IMPEDIMENTS

15
 ASSUMPTIONS AND RATIONALE
  • For the foreseeable future, environmental
    information will grow in quantity and quality.
  • Individual agencies are collecting, organizing,
    and disseminating information relevant to their
    own domain of activity.
  • There is not enough manpower and time to digest,
    analyze, integrate, and ultimately make use of
    the accumulated environmental information.
  • Therefore, there is a need for a systematic
    effort to develop suitable data organization,
    manipulation, integration, and delivery system.
  • A possible mechanism for accomplishing these
    task is to form a consortium of
    informatics-minded institutions - the EI Group.
  • For the foreseeable future, environmental
    information will grow in quantity.
  • There is not enough manpower and time to
    analyze, integrate, and use of all the data
  • The problem is not so much the quantity of data,
    but rather the form in which is delivered, e.g.
    the automobile windshield delivers lots of data
    but we can still process it with ease.
  • What is needed is a faster way to metabolize the
    expanding environmental data sets.
  • Therefore, there is a need for a systematic
    effort to better understand environmental
    information its characteristics, use and
    management.

16
USER DRIVEN FLOW OF ENVIRONMENTAL INFORMATION
  • USER DRIVEN FLOW OF ENVIRONMENTAL INFORMATION
  • In scientific, educational, and regulatory use of
    environmental data, there is a need for
    multiplicity of compatible data sets and
    knowledge from various domains.
  • There is a set of universal values that can be
    added to the data such as accessibility, common
    coding, and documentation. These values in
    conjunction with a set of software tools could
    minimize the "info-glut".
  • Use of data for science, education, regulation
    and policy requires
  • Specification of the information need by the
    user
  • An information system (model, educational
    software or a decision support system) that is
    capable of delivering the needed information.
  • Domain data supplied by the producer or brokers.

17
  • POSSIBLE ACTIVITIES OF EI GROUP
  • EI Science Define the domain of EI
    environmental information as a resource seek
    general laws of EI info uses driving forces.
  • EI Engineering Study the components of EI
    systems creation value-added processes
    data/information/knowledge structures for storage
    and transmission design of EI systems.
  • Education Develop educational materials on EI
    conduct workshops, training sessions.
  • Work closely with others on
  • Data Integration Collect, reconcile,
    integrate, document data/information/knowledge
    bases.
  • Data Exchange Foster exchange through
    depositories, data catalogs, transfer mechanisms,
    and nomenclature standards.
  • Tools Development Evaluate and develop
    software tools for the access, manipulation, and
    presentation of environmental information.

18
  • REQUIREMENTS FOR THE EI GROUP
  • The EI GROUP has to have a solid understanding
    of environmental data needs for science,
    education, and policy development, regulations,
    and other uses.
  • Know how to translate the information needs to
    information systems and to design a data flow and
    transformation systems (information engineering).
  • The EI GROUP has to be well versed in modern
    information science and technology as applicable
    to environmental informatics. Where necessary,
    the Group has to develop new concepts and
    technologies.
  • It has to interface with the users of the
    environmental information, to assure the
    usefulness of the effort.
  • Interface with, and utilize the existing
    governmental and private data sources, building
    on and enhance not competing with those effort.

19
  • OUTPUT OF THE EI GROUP
  • Technology Adopt and apply evolving technologies
    for DBMS, GIS, Hypertext, Expert Systems, User
    Interfaces, Multimedia, Object Orientation
  • Public Databases Prepare relevant, high quality,
    well documented, compatible, integrated, raw, and
    aggregated environmental databases to be usable
    for science, education, enforcement, and other
    purposes. Make such high quality-high value data
    environmental information available to many
    users.
  • Software Tools Provide "smart" data
    display/manipulation tools that will help turning
    data into knowledge. e.g. GIS, Voyager, Movie,
    Hypertext, Video/Sound.
  • Federal agencies have recognized these needs
    and formed the Interagency Working Group on Data
    Management for Global Change IWGDMGC
  • The federal effort could be augmented by
    companion academic efforts, possibly through a
    consortium of informatics-minded institutions -
    the EI Group.

20
POSSIBLE ACTIVITIES OF THE EI GROUP
  • Data Integration Collect, reconcile,
    integrate, document information bases.
  • Data Exchange Foster exchange of environmental
    data through depositories, data catalogs,
    transfer mechanisms, and nomenclature standards.
  • Tools Development Evaluate and develop
    software tools for the access, manipulation, and
    presentation of environmental information.
  • End-Use Projects Conduct specific research and
    development projects for science, education, and
    regulations.
  • Education Conduct workshops, training
    sessions, and prepare educational material for
    environmental informatics.

21
REQUIREMENTS FOR THE EI GROUP
  •   The EI GROUP has to have a solid understanding
    of environmental data needs for science,
    education, and policy development, regulations,
    and other uses.
  • Know how to translate the information needs to
    information systems and to design a data flow and
    transformation systems (information engineering).
  • The EI GROUP has to be well versed in modern
    information science and technology as applicable
    to environmental informatics. Where necessary,
    the Group has to develop new concepts and
    technologies.
  • Interface with, and utilize the existing
    governmental and private data sources, building
    on and enhance not competeing with those effort.
  • It has to interface with the users of the
    environmental information, to assure the
    usefulness of the effort.

22
EI GROUP OUTPUT
  • New Developments Environmental Informatics
  • Science Define the domain of EI. Develop new
    methods to classify, organize, and create
    environmental knowledge.
  •  
  • Engineering Create an infrastructure and
    methodology for the organization, transformation,
    and delivery of environmental information.
  •  
  • Technology Examine the evolving technologies for
    Database Management Systems (DBMS), Geographic
    Information System (GIS), Hypertext, Expert
    Systems, User Interface, Multimedia, Object
    Orientation. Apply and adopt these technologies
    to environmental information.
  • Provide High Grade Environmental Databases for
    Public Use
  • Prepare relevant, high quality, well documented,
    compatible, integrated, raw, and aggregated
    environmental databases to be usable for science,
    education, enforcement, and other purposes. Make
    such high quality-high value data environmental
    information available to many users.
  • Provide Software Tools
  • Provide "smart" data manipulation tools that will
    help turning data into knowledge.
  • Provide tools for data access, manipulation, and
    presentation (e.g. GIS, Voyager, Movie,
    Hypertext, Video/Sound).

23
Funding
24
Information and Decision Making (1)Arno Penzias
Ideas and Information
  • An instrument operator, traffic controller,
    economist .... all process information. A common
    thread among these activities is that is decision
    making. A decision may be simple such as
    selecting ....replacing a . or as complex as
    developing a new clean air legislation. Decisions
    are followed by actions and actions generally in
    new information . This rather circular behavior
    keeps the decision process going until some goal
    is met, the task is finished , or the project is
    set aside for a time. Healthy flow of information
    separates winning organizations from losers. (
    More on the flow concept here)
  •  
  •  
  • For quality information, today's consistently
    successful decision makers rely on a combination
    of man and mashine. Getting the best combination
    requires understanding how the two fit together
    and the roles each may play. It also requires
    having an information strategy that is suitable
    for both he decision-maker's preferences and the
    problem at hand.
  •  
  • Knowledge is whatever information is used to make
    decision.
  • "Deciding" is acting on information.
  • Managers are transformers of information
  • pp125

25
Information and Decision Making (2)Arno Penzias
Ideas and Information
  • Information Flow and Decision Making
  • An instrument operator, traffic controller,
    economist .... all process information. A common
    thread among these activities is that is decision
    making. A decision may be simple such as
    selecting ....replacing a . or as complex as
    developing a new clean air legislation. Decisions
    are followed by actions and actions generally
    reswult in new information . This rather circular
    behavior keeps the decision process going until
    some goal is met, the task is finished , or the
    project is set aside for a time.
  •  
  • Barring blind luck, the quality of decision can
    not be any better than the quality of the
    information behind it.
  • Healthy flow of information separates winning
    organizations from losers. ( More on the flow
    concept here)
  •  
  • Knowledge is whatever information is used to make
    decision.
  • "Deciding" is acting on information.
  • Managers are transformers of information
  • pp125
  • Despite the explosive growth in computing, we
    have yet to feel the full impact of the
    information-processing resource that
    microprocessors offer. The computing power will
    immensity the challenge of developing ever more
    powerful methods of telling mashines to do what
    we whish them to do. This requires the solution
    of "the software problem". -
  •  
  • Solving the "the software problem" includes
    producing software more quickly, with fewer bugs
    at lower cost- software that is easier to to
    understand, modify and reuse different
    applications. Give user to customize a system by
    modifying.

26
Information and Decision Making (3)Arno Penzias
Ideas and Information
  • UNIX - Social behavior
  • Most applications use different formats to move
    information between them. UNIX programs
    communicate with each other in a specific way.
    This arrangement allows the programmer to plug
    programs together like Lego sets, without
    worrying about the details of interfacing. UNIX's
    modularity permits users to build customized
    application programs out of modular pars from
    libraries and programs borrowed from friends.
    Convenient "User programmability" has the
    potential to unleash the creative powers of many
    users instead of relying on the program creator
    for all the insights needed to create well suited
    applications
  • What next? Search of nonprocedural programming
    that frees users from worrying about how a given
    task is to be accomplished and allow them to
    merely state what they want.

27
Information and Decision Making (4)Arno Penzias
Ideas and Information
  • Networking
  • To benefit from information created for different
    purposes under different conditions and at
    different location, users need convenient
    interfaces to the systems providing the data.
    Ultimately, the intervening networking technology
    that provides the interface should be flexible
    enough to accept information in whatever format
    the data source provides it and translate it to
    the needed format most suitable for human
    perception.
  • Human pattern recognition skills, tactile
    sensitivities and similar interfaces to the
    external world attest to the massive processing
    power that the brain dedicates to such functions.
  • Evidently, the experience of evolution has
    demonstrated the need for a variety of sensitive
    interfaces, . The greatest subtlety of our own
    human interfaces appears to be in the way we
    effortlessly integrate disparate sensory inputs.
    It is the single good feeling you get in a
    theater or sports arena from words, music,
    spectacle, and someone sitting next to you- all
    at the same time. In contrast, most of our
    present technology tends to deal with each input
    the words the visual input etc. as a separate
    entity.
  • User preferences and productivity needs are the
    driving forces behind the call for better
    interface between people and mashines.
  • Much of the additional computer processing power
    will be devoted to providing better interfaces
    between people and mashine.

28
Information and Decision Making (5)Arno Penzias
Ideas and Information
  • Computers and human information processing
  •  
  • While computers afford humans much valuable help
    in processing massive amounts of data. However,
    mashines are best at manipulate numbers or
    symbols people connect them to meaning.
  •  
  • Machines offer little serious competiion in areas
    of creativity, integration of disparate
    information, and flexible adaptation to
    unforeseen circumstances. Here the human mind
    functions best. Computing systems lack a key
    attribute of human intelligence the ability to
    move from one context to another.
  •  Just-in-time Information processing symbiotinc
    co-evolution
  •  Computers and communiation systems can speed up
    the Connectivity can spped
  •  
  • Today, access to on-line data reduction schemes
    enables us to think of the results as we get
    them. These better tools can profoundly change
    the way we work. Today, we can ask questions in
    time to get answers, make decisions and create
    more powerful ideas. Generate knowledge faster
  • While ideas flow from human minds, computers can
    help shaping much of the information that leads
    to those ideas. By providing needed information
    in timely way and in digestable form, electronic
    data processing and delivery system can someone
    make informed decisions,
  • Tools of the mind , mind ampliing. Same way as
    steam enfine amplies humans physical power, the
    computer/communication technologies can amlify
    its mental powers.
  • In this sence, the goal of the information
    techloogy promoted here is not so much to
    intruduce artificail intelligence, but tho
    amplify the actual intelligence of humans to
    perfom increasingly complex taks.
  •  

29
Information and Decision Making (6)Arno Penzias
Ideas and Information
  • The Software Problem
  •  
  • Despite the explosive growth in computing, we
    have yet to feel the full impact of the
    information-processing resource that
    microprocessors offer. The computing power will
    immensity the challenge of developing ever more
    powerful methods of telling machines to do what
    we whish them to do. This requires the solution
    of "the software problem". -
  •  
  • Solving the "the software problem" includes
    producing software more quickly, with fewer bugs
    at lower cost- software that is easier to to
    understand, modify and reuse different
    applications. Give user to customize a system by
    modifying.
  •  
  • Most applications use different formats to move
    information between them. UNIX programs
    communicate with each other in a specific way.
    This arrangement allows the programmer to plug
    programs together like Lego sets, without
    worrying about the details of interfacing. UNIX's
    modularity permits users to build customized
    application programs out of modular pars from
    libraries and programs borrowed from friends.
    Convenient "User programmability" has the
    potential to unleash the creative powers of many
    users instead of relying on the program creator
    for all the insights needed to create well suited
    applications
  • What next? Search of nonprocedural programming
    that frees users from worrying about how a given
    task is to be accomplished and allow them to
    merely state what they want.

30
Information and Decision Making (7)Arno Penzias
Ideas and Information
  • Data Access
  •  
  • To benefit from information created for different
    purposes under different conditions and at
    different location, users need convenient
    interfaces to the systems providing the data.
    Ultimately, the intervening networking technology
    that provides the interface should be flexible
    enough to accept information in whatever format
    the data source provides it and translate it to
    the needed format most suitable for human
    perception.
  • Human pattern recognition skills, tactile
    sensitivities and similar interfaces to the
    external world attest to the massive processing
    power that the brain dedicates to such functions.
  •  
  • Evidently, the experience of evolution has
    demonstrated the need for a variety of sensitive
    interfaces, . The greatest subtlety of our own
    human interfaces appears to be in the way we
    effortlessly integrate disparate sensory inputs.
    It is the single good feeling you get in a
    theater or sports arena from words, music,
    spectacle, and someone sitting next to you- all
    at the same time. In contrast, most of our
    present technology tends to deal with each input
    the words the visual input etc. as a separate
    entity.
  • User preferences and productivity needs are the
    driving forces behind the call for better
    interface between people and machines.
  • Much of the additional computer processing power
    will be devoted to providing better interfaces
    between people and machine.
  •  
  •  
  •  

31
Spatial Time Series Analysis-Forecasting -
ControlBennett, R.J. Pion Limited, London 1979
  • Description (Characterization)
  • In order to understand the functioning of
    organisms, one has to understand
  • 1. individual holons (downward face)
  • 2. the relationship between the holons (upward)
    Koestlers holarchy
  •  
  • Involves summarizing the response characteristics
    of the system by purely descriptive measures.
  • Description is accomplished by monitoring,
    followed by descriptive statistics.
  • Explanation
  • Associate and explain events that occur in
    space-time. Build assotiative, causal
    relationships, build model. Analysis stages (p.
    20)
  • Stage 1. Prior hypothesis of systems structure
  • Stage 2. System identification and specification
  • Stage 3. Parameter estimation
  • Stage 4. Check of model fit
  • Stage 5. System explanation, forecasting,
    control

32
Moors Law
  • The single most important thing to know about the
    evolution of technology is Moore's Law. Most
    readers will already be familiar with this "law."
    However, it is still true today that the best of
    industry executives, engineers, and scientists
    fail to account for the enormous implications of
    this central concept.
  • Gordon Moore, a founder of Intel Corporation,
    observed in 1965 that the trend in the
    fabrication of solid state devices was for the
    dimensions of transistors to shrink by a factor
    of two every 18 months. Put simply, electronics
    doubles its power for a given cost every year and
    a half.
  • In the three decades since Moore made his
    observation the industry has followed his
    prediction almost exactly. Many learned papers
    have been written during that period predicting
    the forthcoming end of this trend, but it
    continues unabated today. Papers projecting the
    end are still being written, accompanied with
    impressive physical, mathematical, and economic
    reasons why this rate of progress cannot
    continue. Yet it does.
  • Moore's Law is not a "law" of the physical world.
    It is merely an observation of industry behavior.
    It says that things in electronics get better,
    that they get better exponentially, and that this
    happens very fast. Some, even Gordon Moore
    himself, have conjectured that this is simply a
    self-fulfilling prophecy. Since every corporation
    knows that progress must happen at a certain
    rate, they maintain that rate for fear of being
    left behind.
  • It is also possible that Moore's Law is much
    broader than it appears. Possibly it applies to
    all of technology, and has applied for centuries
    while we were unaware of its consequences or
    mechanisms. Perhaps it was only possible to be
    explicit about technological change in 1965
    because the size of transistors gave us for the
    first time a quantitative measure of progress. If
    this is so, then we are embedded in an expanding
    universe of technology, where the dimensions of
    the world about us are forever changing in an
    exponential fashion.
  • The notion of exponential change is deceptively
    hard to understand intuitively. All of us are
    accustomed to linear projection. We seem to view
    the world through linear glasses -- if something
    grows by a certain amount this year, it will grow
    an equal amount the next year. But according to
    Moore's Law, electronics that is twice as
    effective in a year and a half will be sixteen
    times as effective in 6 years and over a thousand
    times as effective in 15 years. This implies
    periodic overthrows of everything we know. An
    executive in the telecommunications industry
    recently said that the problem he confronted was
    that the "mean time between decisions exceeded
    the mean time between surprises." Moore's Law
    guarantees the frequency of surprises.

33
Metcalfe's Law -- Network Externalities
  • There is another "law" that affects the
    introduction of new technology -- this time in an
    inhibiting fashion. Metcalfe's Law, also known to
    economists generally as the principle of network
    externalities, applies when the value of a new
    communications service depends on how many other
    users have adopted this service. If this is the
    case, then the early adopters of a given service
    or product are disincented, since the value they
    would obtain is very small in the absence of
    other users. In this situation innovation is
    often throttled.
  • Metcalfe's law often applies to communications
    services. A classic example, of course, is the
    videotelephone. There is no value in having the
    first videotelephone, and it only acquires value
    slowly as the population of users increases. If
    there are n users at a given time, then there are
    n(n-1) possible one-way connections. Thus the
    value grows as the square of the number of users.
    The value starts slowly, then reaches some point
    where it begins to rise rapidly. It seems as if
    there needs to be a critical mass for takeoff,
    and that there is no way to achieve that critical
    mass, given the burden on initial subscribers.
  • Metcalfe's Law has defeated many technological
    possibilities, left stillborn at the starting
    gate of market penetration. Nonetheless, there
    are important examples of breakthroughs. For
    example, facsimile became a market success, but
    only after decades of technological viability.
    Even so, facsimile is a complex story, involving
    the evolution of standards, the inevitable
    progress of electronics, the equally-inevitable
    progress in the efficiency of signal-processing
    algorithms, and the rise of the business need for
    messaging services.
  • Moore's and Metcalfe's laws make an interesting
    pair. In the communications field Moore's law
    guarantees the rise of capabilities, while
    Metcalfe's law inhibits them from happening.
    Devices that appear to have little intrinsic
    value without the existence of a large networked
    community continue to diminish in cost themselves
    until they reach the point where the value and
    cost are commensurate. Thus Moore's Law in time
    can overcome Metcalfe's Law.

34
Metcalfe's Law -- Network Externalities(2)
  • Economists know it as the law of increasing
    returns, of network externalities, but the idea
    is that the more people that are connected to a
    network the more valuable it is.  Specifically,
    the value of a network grows by the square of the
    number of users.  The value is measured by how
    many people I can communicate with out there, so
    the total value of the network grows as the
    square of the number of users.  Now, what this
    means is that a small network has almost no
    value, and a large network has a huge value. 
    What it gives you is the lock-in phenomenon of
    winner takes all.  You want to have the same
    thing as everybody else.  The idea is that you
    dont want to be the first person on your block
    to get the plague.  But when all your friends get
    it, you think about getting it.  The more people
    have it, the more youre likely to get it and
    suddenly there is this capture effect where
    everybody has it.  This law of network
    externality governs so much of the business and
    is at the heart of the Microsoft trial.  Why does
    Microsoft have a monopoly?  Is this a natural
    phenomenon that has to do with networks?
  • David Reed coined another lawReeds Lawthat
    says theres something beyond Metcalfes Law. 
    There are three kinds of networks. 
  • First, theres broadcast like radio and TV, which
    well call a Sarnoff network.  The value of that
    network is proportional to the number of people
    receiving the broadcast.  Amazon would be this
    type of network, because people shop there but
    dont interact with each other. 
  • Then theres the Metcalfes Law-type network
    where people talk to each other, for example,
    classified ads.  Reed said that the important
    thing about the Internet is neither of those. 
  • The Internet exhibits a third kind of lawwhere
    communities with special interests can form.  The
    thing about communities is there are 2n of them,
    so in a large network the value of having so many
    possible communities and subnetworks is the
    dominant factor.  He predicts a scaling of
    networks, starting with small networks having
    only the Sarnoff linear factor, larger networks
    dominated by the square factor, and giant
    networks dominated by the 2n factor of the
    formation of communities.
  • Napster is another example of whats going on in
    information technology.  First, its an example
    of the kind of network where winner takes all. 
    Napster is where all the songs are, so thats
    where everybody else is.  If Napster goes under,
    when they go under, then all the little sites
    wont be able to replace it because people wont
    find what they want there.  Napster also brings
    up one of the other properties of information,
    which is troublesome and is going to shape our
    society in the coming yearsthe idea that
    information can be copied perfectly at zero
    cost.  That flies in the face of so much of what
    we believe about commerce.  As my friend Douglas
    Adams said to me, we protect our intellectual
    property by the fact that its stuck onto atoms,
    but when its no longer stuck onto atoms, there
    is really no way to protect it.  He would like to
    sell his books at half a cent a page, the idea
    being that for every page you read, you pay him
    half a cent.  If you get into the book 20 pages
    and you say, This book is really bad, you dont
    pay anymore.  That would eliminate the copying
    of information at zero cost issue that he
    experiences as an author.  He says people come up
    to him in the street and say, Ive read your
    book 10 times, and he says, Yes, but you didnt
    pay 10 times.
  • So these are some of the things that trouble me
    about the future of information technology.  What
    are its limits?  Will the laws of network effects
    doom us all to a shared mediocrity?  What will
    happen to intellectual property and its effect on
    creativity?  Is it like the railroads, or is this
    something fundamentally different that will last
    through the next century?

35
The Evolution of the World Wide Web
  • The most important case study in communications
    technology is the emergence of the World Wide
    Web. This revolutionary concept seemed to spring
    from nothingness into global ubiquity within the
    span of only two years. Yet its development was
    completely unforeseen in the industry an
    industry that had pursued successive long and
    fruitless visions of videotelephony, home
    information systems, and video-on-demand, and had
    spent decades in the development of ISDN with no
    apparent application. It now seems incredible
    that no one had foreseen the emergence of the
    Web, but except for intimations in William
    Gibsons science fiction novel Neuromancer, there
    is no mention in either scientific literature or
    in popular fiction of this idea prior to its
    meteoric rise to popularity.
  • There is a popular notion that all technologies
    take 25 years from ideation to ubiquity. This has
    been true of radio, television, telephony, and
    many other technologies prevalent in everyday
    life. How, then, did the Web achieve such
    ubiquity in only a few years? Well, the
    historians argue, the Web relied on the Internet,
    which in turn was enabled by the widespread
    adoption of personal computers. Surely this took
    25 years. We might even carry this further. The
    personal computer would not have been possible
    without the microprocessor, which depended on the
    integrated circuit evolution, which itself
    evolved from the invention of the transistor, and
    so forth. By such arguments nearly every
    development, it seems, could be traced back to
    antiquity.
  • Although the argument about the origin and length
    of gestation seems an exercise in futility, the
    important point is that many revolutions are
    enabled by a confluence of events. The seed of
    the revolution may not seem to lie in any
    individual trend, but in the timely meeting of
    two or more seemingly-unrelated trends. In the
    case of the World Wide Web the prevalence of PCs
    and the growing ubiquity of the Internet formed
    an explosive mixture ready to ignite. Perhaps no
    invention was really even required. The world was
    ready -- it was time for the Web. While this
    physical infrastructure was forming in the
    worlds networks and on the desktops of users,
    there was a parallel evolution of standards for
    the display and transmission of graphical
    information. HTML, the hypertext markup language,
    and HTTP, hypertext transmission protocol, were
    unknown acronyms to the majority of technical
    people, let alone the lay public. But the
    definition of these standards that would enable
    the computers and networks to exchange rich
    mixtures of text and pictures was taking shape in
    Switzerland at the physics laboratory CERN, where
    Tim Berners-Lee was the principle champion.
  • The role of standards in todays information
    environment is critical, but often unpredictable.
    What is really important is that many users agree
    on doing something exactly the same way, so that
    everyone achieves the benefits of
    interoperability with everyone else. It is
    exactly the same concept of network externalities
    that is at work in Metcalfes law. An
    international standard can stimulate the market
    adoption of a particular approach, but it can
    also be ignored by the market. Unless users adopt
    a standard it is like the proverbial tree falling
    in the forest without a sound. Standards are, for
    the most part, advisory. User coalitions or
    powerful corporations can force their own
    standards in a fascinating and ever-changing
    multi-player game. Moreover, de facto standards
    often emerge from the marketplace itself.
  • So in the middle 1980s there was a prevalent
    physical infrastructure with latent capabilities
    and an abstract agreement on standards for
    graphics. One more development and two brilliant
    marketing ideas were required to jumpstart the
    Web. The development was that of Mosaic at the
    National Center for Supercomputing Applications
    at the University of Illinois. Mosaic was the
    first browser, a type of program now known
    throughout the world for providing a simple
    point-and-click user interface to distributed
    information. Following the initial versions of
    Mosaic from NCSA, commercial browsers were
    popularized by Netscape and Microsoft.
  • The revolutionary marketing ideas needed for the
    Web now seem obvious and ordinary. A decade ago,
    however, they were not at all obvious. One idea
    was to enable individual users to provide the
    content for the Web. The other idea was to give
    browsers free to everyone. Between these ideas,
    Metcalfe's Law was overcome. Even though browsers
    initially had almost no value, since there were
    no pages to browse, they could be obtained
    electronically at no cost. The price was directly
    related to the value. Thus browsers spread
    rapidly, just as their value began to build with
    the accumulation of web pages.
  • Allowing the users to provide content was counter
    to every idea that had been held by industry. The
    telecommunications and computer industries had
    tried for a decade to develop and market remote
    access to information and entertainment held in
    centralized databases. This was the cornerstone
    of what were called "home information systems"
    that were given trials in many cities during the
    1970s and 1980s. Later, the vision pursued by the
    industry was that of video-ondemand -- the dream
    of providing access to every movie and television
    show
  • ever made, like a giant video rental store, over
    a cable or telephone line.
  • Virtually every large telecommunications company
    had trials and plans for videoon-demand, and the
    central multi-media servers required for content
    storage were being developed by Microsoft,
    Oracle, and others. The Web exemplifies some
    powerful current trends -- the empowerment of
    users, geographically-distributed content,
    distributed intelligence, and intelligence and
    control at the periphery of the network. Another
    principle is that of open, standard interfaces
    that allow users and third parties to build new
    applications and capabilities upon a standardized
    infrastructure.
  • It is hard to criticize industry for pursuing the
    centralized approach. Imagine proposing the Web
    to a corporate board in 1985, and describing how
    browsers would be given away free, and how
    industry would depend upon the users to provide
    whatever content might appear. Even today many
    corporations wonder and worry about the business
    model for the Web, and few are making any profits
    at all.

36
Information Technology and the Conduct of
Research The Users ViewNational Academy Press,
Washington, D.C. 1989
  • Committee rationale There are serious
    impediments to the wider and more effective use
    of information technology. Committee members were
    active researchers are outside the field of
    "information technology". In the absence of
    considerable knowledge about the field, the panel
    was approaching it by asking the researchers
    about their experiences.
  • p 1. Information technology - the set of computer
    and communications technologies - has changed the
    conduct of scientific, engineering and clinical
    research. New technologies offer the prospect of
    new ways of finding, understanding, storing, and
    communicating information and should increase the
    capabilities and productivity of researchers.
    Among these new technologies are simulations, new
    methods of presenting observational and
    computational results as visual images, the use
    of knowledge-based systems as "intelligent
    assistants" and more flexible and intuitive ways
    for people to interact with and control
    computers.
  • The conduct of research The everyday work of
    researcher involves writing proposals, developing
    theoretical models, designing experiments,
    collecting data, analyzing data, communicating
    with colleagues, studying research literature,
    reviewing colleagues work, and writing articles.
    They look at three particular aspect of research
    data collection and analysis, communication and
    collaboration, and information storage and
    retrieval.

37
Information Technology and the Conduct of
Research The Users ViewNational Academy Press,
Washington, D.C. 1989
  • DATA COLLECTION AND ANALYSIS
  • It is one of the most widespread use of
    information technology in research. Trends
  • Increased use of computers
  • Dramatic increase of data storage and processing
    capacity
  • Creation of new computer controlled instruments
    that produce more data
  • Increase communication among researchers using
    networks.
  • Availability of software packages for standard
    research (e.g. statistical)
  •  
  • Difficulties
  • 1. Uneven distribution of computing resources,
    the has and have-nots
  • 2. Finding the right software. Commercial
    software is often unsuitable for specialized
    needs. Most researchers, although they are not
    skilled software creators, develop their own
    software with the help of graduate students. Such
    software is designed for one purpose and it is
    difficult to understand, to maintain or transport
    to other computing environments.
  • 3. Transmitting data over networks at high speed.
  • COMMUNICATION AND COLLABORATION
  • Routine word processing and electronic mail are
    the most pervasive form of computer use.
    Electronic publishing and data communication-coord
    ination is becoming increasingly used. Trends
  • Information can be shared more quickly
  • New collaborative arrangements
  • Difficulties
  • Incompatibility of technologies
  • Networks are anarchic.

38
Information Technology and the Conduct of
Research The Users ViewNational Academy Press,
Washington, D.C. 1989
  • IFORMATION STORAGE AND RETRIEVAL
  • How it is stored determines how accessible it is.
    Scientific text is stored on print ( hard copy)
    and accessible though indices, catalogs of a
    library. Data and databases are stored mostly on
    computers disks.
  • A database along with the procedures for
    indexing, cataloging and searching makes up an
    information management system.
  • Difficulties
  • The researcher cannot get access to data if he
    can, he can not read them if he can read them,
    he does not know how good they are and if he
    finds them good he can not merge them with other
    data .
  • Difficulty accessing data stored by other
    researchers. Such access permits reanalysis and
    replication, both essential elements of
    scientific process. At present data storage is
    largely an individual researcher's concern, in
    line with the tradition that researchers have
    first right to their data. The result has bee a
    proliferation of idiosyncratic methods for
    storing, organizing, and indexing data, with the
    researchers data essentially inaccessible to all
    other researchers.
  • Formats in data files vary from researcher to
    researcher, even within a discipline. These
    problems prohibit a researcher from merging
    someone else's data in his own database. Hence,
    considerable effort must be dedicated to
    converting data formats. not enough metadata.
  • Finally when a researcher reads another database,
    he has no notion as to the quality of the data it
    contains. The data sets do not have enough QC
    information and descriptive metadata. There is a
    need for evaluated high quality databases.
  • Given a high quality well described database, a
    major difficulty exists in conducting searches.
    Most info searches are incomplete, cumbersome,
    inefficient, expensive, and executable only by
    specialists. Searches are incomplete because the
    databases themselves are incomplete. Updating is
    expensive because data are stored in more than
    one database. Cumbersome and inefficient because
    different databases are organized according to
    different principles. ( data models)
  • Another difficulty in storing data information is
    private ownership. By tradition, researchers hold
    their data privately. In general, they neither
    submit their data to a central archive nor make
    their data available via computer. Increasingly,
    however, in disciplines such as meteorology and
    biomedical sciences, submission of primary data
    into databanks is has become accepted as a duty.
    In some fields, the supporting agencies require
    that the data be archived in machine readable
    format and that any professional article be
    accompanied by a disk describing the underlying
    data. Also, a comprehensive reference service for
    computer-readable data should be developed.
    Master directory
  • In addition, peer review of articles and
    proposals has been constrained by the difficulty
    of gaining access to the data used for the
    analysis. If writer were required to make their
    primary data available, reviewers could repeat at
    least part of their analysis reported. Such a
    review would be more stringent, would demand more
    effort from reviewers and raises some operational
    questions that need to be resolved. but
    arguably lead to more careful checking of
    published results.
  • Underlying difficulties in information storage
    and retrieval are problems in the institutional
    management of resources. . Who is to mange,
    maintain, and update info services.? Who is to
    create and enforce standards? At present, the
    research community has tree alternatives federal
    government which manages resources as MEDLINElt
    and GenBank professional societies such as the
    American Chemical Society which manages the
    Chemical Abstracts Service and non-profit
    organizations such as Institute for Scientific
    Information.

39
Information Technology and the Conduct of
Research The Users ViewNational Academy Press,
Washington, D.C. 1989
  • Recommendations
  • Institutions supporting researchers must develop
    support policies,services standards for better
    use if info technology. The institutions are
    Universities, University Departments, Funding
    Agencies, Scientific Associations, Network
    Administrators, Info Service providers, Software
    vendors and professional groups
  • The Federal Government should support software
    development for scientific research. The software
    should meet standards of compatibility,
    reliability, documentation and should be made
    available to other researchers.
  • Data collected with government support rightfully
    belong to the public domain. with reasonable time
    for first publication should be respected.
  • There is a pressing need for more compact form of
    storage
  • Tool building for non-defense software should be
    encouraged
  • The Federal Government should fund pilot projects
    to on information storage and dissemination
    concepts in selected disciplines and implement
    software markets with emphasis on the development
    of generic tools useful for multiple disciplines.
  • The institutions lead by the federal government
    should develop an information technology network
    for use by all qualified researchers.

40
Measuring for Environmental Resultsby William K.
Reilly, EPA Journal, May-June 1989
  • A key element in any effort to measure
    environmental success is information--information
    on where we've been with respect to environmental
    quality, where we are now, and where we want to
    go. Since its beginning, EPA has devoted a great
    deal of time, attention, and money to gathering
    data. We are spending more than half a billion
    dollars a year on collecting,, processing, and
    storing environmental data. Vast amounts of data
    are sitting in computers at EPA Headquarters, at
    Research Triangle Park, North Carolina, and at
    other EPA facilities across the country.
  • But having all this information--about air and
    water quality, about production levels and health
    effects of various chemicals, about test results
    and pollution discharges and wildlife
    habitats--doesn't necessarily mean that we do
    anything with it. The unhappy truth is that we
    have been much better at gathering raw data than
    at analyzing and using data to identify or
    anticipate environmental problems and make
    decisions on how to prevent or solve them. As
    John Naisbitt put it in his book Megatrends "We
    are drowning in information but starved for
    knowledge."
  • Our various data systems, and we have hundreds of
    them, are mostly separate and distinct, each with
    its own language, structure, and purpose.
    Information in one system is rarely transferable
    to another system. I suspect that few EPA
    employees have even the faintest idea of how much
    data are available within this Agency, let alone
    how to gain access to it. And if that is true of
    our own employees, how must the public feel when
    they ponder the wealth of information lurking,
    just out of reach, in EPA's huge and seemingly
    impenetrable data bases?
  • The strategic information effort I have
    described, however, will require a new attitude
    on the part of every EPA program manager--a
    willingness to break out of the traditional
    constraints of media-specific and
    category-specific thinking.
  • Just as important, we must find ways to share our
    data more effectively with the people who paid
    for it in the first place the American public.
    Eventually, as EPA makes progress in
    standardizing and integrating its information
    systems, the information in those systems--apart
    from trade secrets--should be as accessible as
    possible. Such information could be made
    available through on-line computer
    telecommunications, through powerful new compact
    disc (CD-ROM) technologies, and perhaps a
    comprehensive annual report on environmental
    trends.
  • Sharing information with the public is an
    important step toward establishing a common base
    of understanding with the American people on
    questions of environmental risk. As the recent
    furor over residues of the chemical Alar on apple
    products shows, there can be a wide gap between
    public perceptions of risk and the degree of risk
    indicated by the best available scientific data.
  • EPA must share and explain our information about
    the hazards of life in our complex industrial
    society with others--with other nations, with
    state and local governments, with academia, with
    industry, with public-interest groups, and with
    citizens. We need to raise the level of debate
    on environmental issues and to insure the
    informed participation of all segments of our
    society in achieving our common goal a cleaner,
    ,healthier environment.
  • Environmental data, collected and used within the
    strategic framework I have described, can and
    will make a significant contribution to
    accomplishing our major environmental objectives
    over the next few years. Strategic data will
    help us
  •         Create incentives and track our progress
    in finding ways to prevent pollution before it
    is generated.
  •         Improve our understanding of the complex
    environmental interactions that contribute to
    international problems like acid rain,
    stratospheric ozone depletion and global
  • warming.
  •         Identify threats to our nation's ecology
    and natural systems--our wetlands, our marine
  • and wildlife resources--and find ways to reduce
    those threats.
  •         Manage our programs and target our
    enforcement efforts to achieve the greatest
  • environmental results.

41
USES OF ENVIRONMETAL DATA
  • Environmental data are used for many purposes.
    They may be to support environmental management
    or to the good of the society by by deriving more
    general environmental knowledge
  • Provide Historical Record
  • Identify Deviation from Expected Trend
  • Anticipate Future Environmental Problems
  • Provide Legal Record
  • Support Environmental Research
  • Support Environmental Education
  • Support Communication
  • Record Monitoring and Control Procedures

42
Taylor Model
  • Taylor Model
  • One of the specific tools employed by the staff
    of University Library was the Taylor Model.5
    Taylor's model is a theoretical model and is not
    predictive. The University Library adapted it as
    a working tool and, in turn, adopted the concepts
    of "value-adding" and the importance of
    Information Use Environments as cri
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