Science and Technology

Information Seeking, Scholarly Communication, and Open Access

Florence M. Paisey

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The Web is an information resource of extraordinary size and depth, yet it is also an

information reproduction and dissemination facility of great reach and capability; it is at

once one of the world’s largest libraries and surely the world’s largest copying machine.

“The Digital Dilemma: Intellectual Property in the Information Age”

National Research Council: Committee on Intellectual Property Rights in the Emerging Information Infrastructure, 2000

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Table of Contents

Preface................................................................................................................................4

Information Literacy in Science: The ACRL Definition....................................................6

The ACRL Science and Technology Standards and IS Models........................................13

Unique Characteristics of the ACRL Science and Technology Standards........................15

Communication and Flow of Scientific Information.........................................................17

Patents, Intellectual Property, and Digital Data Depositories............................................22

References..........................................................................................................................27

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Preface

The following essay explores information seeking and the search process characteristic

of academic professionals in the sciences. In addition, it discusses key issues that relate to

scientific information: its ownership, its exchange and production or communication, and

some of the legislation and policy issues that have come into play with the large scale

research needs of megasciences and open access depositories such as SPARC. The essay

commences with the ACRL definition of information literacy in the sciences and a

description of generic information skills that, potentially, bring about effective information

management in the sciences.

It is difficult to speak about information seeking in a generic sense, particularly in the

sciences. Context alone does not explain the differences in information seeking among

scientific disciplines. The force of habit, whether given to optimal results or not, often

plays into how scientists construct their thought and interact with information sources.

While humanities scholars consult definitive works on potential research topics, scientists,

on the whole, first engage in discourse with their peers, and then develop research

methodology and strategy. For those scientists working in applied fields, such as medicine,

roles generate discrete tasks and demand knowledge with the possibility of an information

need and query.

The topics of communication in the sciences as well as property rights to data are also

briefly explored. Communication models are evolving first through modernization with a

view to transformation. Property rights to data, generated by those involved in the

megasciences, are complex with grayed and ambiguous boundaries; there is no simple

answer. Each aspect of information behavior and information seeking explored here is a

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deeply engaging topic in its own right. I have merely identified points, at issue, in an effort

to understand how information impacts individual interaction with sources, the flow of

scholarly communication, and research policy.

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Information Literacy in Science: The ACRL Definition

Information literacy involves recognizing an information need and seeking answers to

that need through questions one asks. It may be viewed as a “generic ability of citizens in a

democratic society to make well informed choices based on the critical evaluation of a

wide range of information sources” (Alexandersson & Limberg, 2005). Fundamentally,

information literacy and information literacy in science involve the same goals: identifying

and satisfying information needs.

Information literacy identifies a general set of cognitive, physical, and technical skills

applicable to unscientific information; information literacy in science deals with cognitive,

physical, and technical skills characteristic of specific disciplines in science and scientific

thought. The generic ACRL Information Literacy Standards set forth broad information

skills and behaviors that will foster the ability to manage and use information in general.

The ACRL Science and Technology Standards distinguish information skills that are

distinctive to the nature of and goals of science.

The ACRL provides a definition of information literacy in science and engineering.

This definition directed the development of the information literacy standards and

performances specific to science and engineering/technology. The ACRL defines

information literacy in science as:

…a set of abilities to identify the need for information,

procure the information, evaluate the information and

subsequently revise the strategy for obtaining information,

to use the information, and to use it in an ethical and legal

manner, and to engage in lifelong learning (ACRL, 2006).

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The Association of College and Research Libraries (ACRL) developed the Science and

Technology Information Literacy Standards (ACRL, 2006) as an outcomes-based

framework for students and professionals in higher education. They include five Standards

and 26 performances or performance indicators with associated outcomes, all intended to

implement the practice of information literacy in science and engineering/technology, as

conceived and described by the ACRL. These Standards are scaffolding upon which

specific, granular performances will bring about meaningful and ethical individual

information management and use as conducted by students, scholars, and researchers in

higher education.

They support in-depth, inquiry-based information searching. This is the fundamental

intent underlying the ACRL Science and Technology Standards. Like the general ACRL

Information Literacy Standards, the science and technology standards derive from

cognitive task analyses of experts or the “analysis of specific sequences of action and

cognitive processes” employed by experts when satisfying an information need (Vakkari,

2003). In the case of the ACRL Science and Technology Standards, the information need

would relate to science and require information searching appropriate to the nature of a

scientific discipline.

Wilson’s model of information behavior and information searching (1999) offers a

cohesive representation or grounding of information behavior and the search process

regardless of the discipline. His description of information behaviors (2000) as

information seeking, information searching, and information use also corresponds to levels

of goal-directed information behavior whether the informational goal is of a scientific

nature or otherwise. The search process itself follows from an information need to the

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satisfying of that need. However, as Vakkari (2003) has pointed out, the search process

and outcome are dependent variables – consistent across searchers, disciplines, and

domains. The independent variable involves user characteristics and those factors in users

that cause “systematic variation in search process and outcome.” The ACRL Science and

Technology Standards may be viewed, basically, as the dependent variable or the search

process, with specific features that directly relate to specialized sources of information and

the character of scientific communication. The independent variable, the user and those

factors, such as the need for scientific information, may be viewed as process variables

that cause “systematic variation” in the search process.

In general, the Standards provide the dependent variable, a search process, though

specific features of the process such as “search tactics” or “term choices” could be viewed

as either dependent or independent variables, depending on the formulation of the problem

(ibid). For example, as a search process, the ACRL Standards for Science and Technology

serve as a template; the characteristics of the user and the information need will determine

variation in the use of the Standards. Within the Standards, Standard 2 includes 5

Performance Indicators. They include the selection of investigative methodology, the

construction of a search strategy, the retrieval of information, refinement of the search (if

necessary), and the use of appropriate technology to record pertinent information. These

performances are consistent; they are dependent variables. However, the methodology one

selects to investigate an inquiry, the terms or vocabulary a user employs or the formulation

of how to pursue a search – whether to refine a search or not, the search strategy – would

be characterized by the user and, as such, would be independent variables.

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The ACRL Science and Technology Standards support the search process in scientific

disciplines. However, they do not identify specific work roles and tasks that would

characterize the user’s information need, interaction with sources of information,

communication cycle, or the outcomes of the search process: the search result. It is this

aspect of information searching, user characteristics, that “cause systematic variation in

search process and outcome – that is, that are systematically connected to searching and

search results” (Vakkari, 2003).

Leckie & Pettigrew (1996) studied the information habits and flow of three professional

groups– engineers, health care workers, and lawyers. Based upon their findings, they

developed a general model of information seeking for professionals, the ISP model. Six

components form the basis of the model, including:

1. Work roles

2. Associated Tasks

3. Information Needs

4. Awareness

5. Sources

6. Outcomes

The first component specifies the varied roles a professional assumes in professional

life. A physician may assume multiple roles such as diagnostician, therapist, medical

administrator, examiner, counselor, researcher, teacher, colleague, manager, medication

therapist, and crisis caretaker. Each of these roles engenders tasks that, in turn, trigger

information needs, giving rise to an information search process (ibid). The information

search process will be shaped by the characteristics of the information need. These needs

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will vary according to many possible factors; both independent and intervening or covert

variables will come to bear.

A note of wariness is worth mentioning here. The independent variable is the user;

intervening variables will affect the user, producing an effect on the dependent variable –

the search process. The independent variable is known, controlled for, and manipulated so

that one can determine its effect on the dependent variable – in this case the search

process. Intervening variables will also produce an effect on the dependent variable or

search process, but will not be immediately accessible; intervening variables are internal,

covert, unobserved factors that can be inferred and identified only by manipulating the

independent variable. A clear distinction between independent and intervening variables

was not clear in Leckie & Pettigrew (1996).

Independent variables might be age, years of medical experience, hours on the job,

specialization, and the frequency with which the physician encounters the task as well as

the information need. Intervening variables might be the degree of information needed, the

confidence level of the physician, the clarity of the information need – does the physician

understand clearly what question to follow or is research required to identify possible

diagnoses, then possible courses of treatment. Personality and preferences in research will

also affect the search process and may be viewed as intervening variables until an

assessment is conducted and one controls for specific variables (Heinström, 2003). An

awareness of one’s expertise or limitations will affect recognition of the information need

as well as the ability to diagnose an ailment accurately; these would be intervening

variables until they become known quantities.

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An awareness of the information sources and one’s perception of the ease or difficulty

in accessing these sources will also affect the search process (Leckie & Pettigrew, 1996).

This level of awareness may be affected by accessibility, familiarity, prior experience,

cost, and timeliness. Where does one find information relating to the need, what is the

currency of the information, how accessible are sources? These are a few of the issues

involved in how information sources are perceived. Leckie & Pettigrew (ibid) identify

sources of information as channels or “formats” of information. These channels or formats

are distinguished as formal and informal, internal and external, oral and written.

Formal channels include conferences and journals; informal channels include

colleagues. Leckie & Pettigrew (ibid) describe the stratification of channels further in

distinguishing between internal (sources within an organization – corporate engineers

frequently utilize internal sources or channels) and external (conference proceedings,

medical literature, the Internet). In addition to these distinctions, sources are viewed as

either oral channels or written channels. One of the characteristics of a user will be their

preference for particular channels or sources of information. These are all variables that

can be controlled for, so user characteristics and the search process can be examined with

greater clarity. However, in order to associate particular user characteristics with a path in

the search process, these variables should not be estimated; rather, they require

identification and control.

The final component in the Leckie & Pettigrew ISP model is outcomes. Outcomes are

defined as the “end-point” of work-related information requirements of “specific roles and

tasks” (ibid). The satisfaction of the information need is recognized as the “optimal

outcome” such as diagnosing an ailment, completing paperwork, submitting an appeal, or

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producing a product. If the satisfaction of the need has not been met, a feedback loop

provides the path to iterate another search process. As repeated searches are carried out,

the user may alter some of the independent variables such as search terms or specific

sources.

The Leckie & Pettigrew model of the information seeking of professionals (ISP) has

been applied to various professions in the sciences, including medicine, biomedicine,

dentistry, nursing, engineering, and software engineering, among others. The notion of

specific roles and associated tasks that give rise to information needs grounds the context

of information seeking by recognizing task goals or in complex tasks the “series of actions

undertaken in pursuit of a goal” (Vakkari, 2003).

The model at issue also discusses the effect of independent and intervening variables on

the search process, though the construct falls short of including likely points of static along

the information search continuum or flow. Its strength lies with recognition that the

interaction of roles and tasks plays a significant role in the formulation of an information

problem, and subsequent need. The Leckie & Pettigrew model (1996) has held up in

limited studies, particularly those studies looking specifically at the relationship between

roles, tasks, and information needs. The model does not provide for a situational context,

reportedly a significant factor in a medical search process (Gruppen, 1990).

However, the Leckie & Pettigrew model provides a valuable dimension to Wilson’s

expansive model. It does not stand an as alternative to Wilson’s information behavior

model; it may be subsumed within this model, along with Ellis’ behavioral micro-search,

in providing further understanding and representation of information behavior, in

particular, the information behavior of professionals.

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The ACRL Science and Technology Standards and IS Models

If one were to layer the Leckie & Pettigrew ISP model (1996) within Wilson’s

information behavior model (1999), one could identify a particular context in which a role

is performed, tasks associated with that role, and the characteristics of the information

needs. Wilson’s model provides for independent and intervening variables along the path

to the search process. This search process, as Vakkari (2003) has pointed out, is the

dependent variable that user characteristics will act on, causing variation in search process

and outcome. As traits of the user become known, a search path becomes more predictable

and systematic. Such knowledge will facilitate the searcher’s understanding of the process,

but will also inform systems designers in their effort to create systems that support search

features with typified search processes.

The ACRL Science and Technology Standards specify standard behaviors,

performances, and performance outcomes that demonstrate competences in a standard or

activities carried out in a search process, particular to disciplines in science. As previously

stated, Wilson’s macro-model (1999) can be layered with dimensions of information

behavior. While the Leckie & Pettigrew (1996) model nests from context to information

need and three aspects of a search, Ellis’ behavioral model of chaining fosters an

understanding of micro-search habits of scientists. The ACRL Science and Technology

Standards offer behaviors, strategies, and values that scientific investigation or the search

process in science requires. These standards can be integrated with Wilson’s expansive

model (1999), Leckie & Pettigrew’s (1996) ISP model, and Ellis’ search chain.

This is not an either-or situation. None of these models or standards is a complete

representation of information behavior and the search process. Each supplies a dimension

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of the search process – in this instance, the search process with features to support

scientific investigation. The ACRL Science and Technology Standards stand as a thorough

account of performances required in such a search process. The degree to which one aspect

of the standards is applied relates to user characteristics, intervening variables, and the

information need.

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Unique Characteristics of the ACRL Science and Technology Standards

Baldwin (2005) identifies several unique characteristics of performances and their

outcomes to information literacy in science and engineering/technology. In Standard 1,

Performance Indicator 2, Baldwin points out that types and formats of sources for

information will be subject specific. She lists several types of source information essential

to study in most of the science disciplines. These sources include “handbooks, patent

literature, standards, specifications, and product literature” (ibid). Each science discipline,

both applied and pure, will have indispensable core reference sources.

In medicine, indispensable sources would include the Physician’s Desk Reference

(PDR), the Merck Manual, Stedmen’s Medical Dictionary, and Mosby's Medical, Nursing,

and Allied Health Dictionary, to name a few. In psychology, the Corsini Encyclopedia of

Psychology and Behavioral Science has been core for several years, while the Mental

Measurements Yearbook and the Diagnostic and Statistical Manual of Mental Disorder

(DSM IV) have been standard information manuals for decades, with periodic updates. In

physics and general sciences, a few core handbooks and manuals would include the CRC

Handbook of Chemistry and Physics, Handbook of Physical Quantities, and the Handbook

of Physics. The Periodic Table is viewed as one of the most important classifications of

the natural world and would be included in all science collections, as would the

Encyclopedia of Associations and Organizations, both National and International. OSHA’s

standards and specifications for safety would also be relevant across all science disciplines

and some social sciences.

In addition to the types and formats of scientific information, Baldwin underscores the

importance of recognizing how “scientific, technical, and related information is formally

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and informally produced, organized, and disseminated” as well as “understanding the flow

of scientific information and the scientific information life cycle” (Baldwin, 2005). This

aspect of Standard 1, Performance Indicator 2, is particularly significant in determining the

credibility and currency of scientific information. What was credible and definitive a

decade ago in physics, chemistry, or medicine may well have changed considerably.

Furthermore, as information and communication technologies have spread and advanced,

communication and the flow of scientific information have altered, though not

fundamentally or universally yet. As this aspect of science will potentially effect dramatic

changes in the information search process of scientists, it merits a bit of discussion.

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Communication and Flow of Scientific Information

Information and communication technologies have changed the way scientists

communicate. However, as Hurd (2000) points out, these changes are incremental and

with a few modifications, fundamental practices still reflect the dominant use of

communication channels established generations ago – weakening the argument for

technological determinism. Scientific communities have integrated ICTs, but such

integration has developed upon existing practice, selectively and gradually. Recent studies

of communication practice support this assertion (Leckie & Fullerton, 1999; Fidel &

Green, 2003).

Hurd (2000) recognizes that ICTs are catalysts that both modernize and will,

ultimately, transform the social networks, information flow, and dissemination of scientific

information. The earlier scientific communication practice referenced above alludes to the

Garvey & Griffith (1964) foundational model of scientific communication, a model that

emerged during the “print-on-paper” era. This model continues to characterize scientific

communication with technologies that support traditional channels or functions, adding

capabilities to an evolving communication system (Hurd, 2000).

More than forty years ago, Garvey & Griffith (1964) conducted a study of the

communication and information needs of scientists. Their initial study focused on the

information behaviors of psychologists (ibid). Their findings were accepted as

representative information searching, exchange, production, and dissemination in both the

physical and social sciences. Garvey & Griffith’s groundbreaking study (ibid), and their

involvement in it, emerged from what had been described as a “scientific information

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crisis” (ibid). They ultimately found, contrary to their initial thought, that “the exchange of

information in research evolves predictably and can be experimentally modified” (ibid).

Garvey & Griffith’s study looked at the information behaviors of scientists as they

attempted to satisfy their information needs. They traced the dissemination process from

the time a researcher starts work until reports of that work have appeared in secondary

publication sources. The processes of scientific communication and information exchange

revealed a dynamic interaction among informal and formal media or information sources.

This interchange typified the means by which scientists mapped investigation that would

satisfy their information needs; it also formed the basis for the study of scientific

communication as a social system or from a sociological perspective. Scientific

communication, exchange and flow, was found to be well organized and predictable with

established communication channels and venues for discourse, review, and eventual

inclusion into an official body of literature.

The Garvey & Griffith model recognizes that the information need precipitates

scientific investigation, but unlike general models of information behavior, it does not look

at individual information seeking and searching or the cognitive field of information

processing. Garvey & Griffith looked at the larger picture, a macro-depiction, identifying

the channels, purposes, and results of discourse within the context of scientific endeavor.

The outcome of these social, contextualized channels of information exchange would be

publication in peer-reviewed journals, then secondary sources. Their model is sociological

in nature, rather than psychological. Such a model is of fundamental importance in

understanding information behavior as a cultural phenomenon as well as an event within a

context, situation, or a profession – in this case, the sciences and the scientific community.

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Information literacy in science, as in all domains, requires an awareness of the culture,

profession, and community in order to understand the nature of a specific – in this case,

scientific – communication interchange and cycle. Such understanding will facilitate all

interaction with information channels and sources within scientific disciplines or contexts,

as well as general information skills. Within the scientific disciplines, knowledge of the

striation or structures of sources that distinguish scientific literature is essential. Of

particular significance is gray literature or “newsletters, reports, working papers, theses,

government documents, bulletins, fact sheets, conference proceedings, and other

publications distributed free, available by subscription, or for sale” (Weintraub, 2000).

Other sources important to distinguish are published monographs, primary and secondary

sources and their place in the flow of information within the cycle. Understanding the

place of an information source within the cycle enables one to formulate sound evaluative

criteria, relevant to one’s information needs.

The sociological aspect of information flow and communication in science has

analogous aspects to individual information behavior. Analogues involve the perception of

one’s information need, formulation of a precise question, the search for information,

development of search strategy, metacognition, and potential revision of the hypothesis,

thesis, or concept. All of these elements of information searching require interaction with

information sources, formal and informal. Generally, the initial phase, or that which

characterizes information seeking, involves informal discussion and debate with one’s

colleagues as a means of negotiating the information question, assessing its value,

identifying pre-existing information sources related to the issue, operationalizing the

question, and devising a methodology to investigate the question. The information need or

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task uncertainty (Fuchs, 1993) may arise out of one’s observation, a diagnostic report,

research report, reflection, or in a tight social network, small world or “invisible college”

(Crane, 1972).

Newman (2001) looked at the social network or collaboration network of scientists,

finding that they form small worlds in which scientists cluster within the proximity of a

few connected acquaintances. The notion that scientists chat, informally, within social

networks, small worlds, or “invisible colleges” supports the Garvey & Griffith model that

scientific investigations, generally, start with the information need, but that the pursuit of

the issue is discussed and hypotheses formulated, informally, collaboratively, or within

small worlds or “invisible colleges” as preliminary dialogue that will direct a course of

scientific investigation. Again, this observation holds up in current practice, as the findings

of numerous studies have concluded (Leckie & Fullerton (1999; Fidel & Green, 2003;

Tenopir & King, 2004).

The Garvey & Griffith model of scientific communication continues to represent the

sociology of scientific communication despite widespread use of ICTs. While scientists

may not write letters as previously, they employ the same means of communicating, but in

a modernized way. Hurd (2000) distinguishes between a modernized and a transformed

communication system. She states:

Modernized features are those that employ

technology to support and update traditional

functions that endure because they continue

to be valued by a community of

scientists (ibid).

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Communication features such as telephones, e-mail, fax, audio and video capabilities

via the Web, and expeditious travel for collaboration update the communication channels

of the Garvey & Griffith model, but the fundamental channels and norms in

communication have not altered. The “invisible college” is broadening its membership to a

“virtual invisible college” where communication relies on the Internet (Hurd, 2000),

including scientists who have, heretofore, been unable to participate in elite collaborative

networks. Yet, these are functional modifications that have simply enhanced

communication. The essential social structure and communication habits remain

unchanged; they are built upon a long-standing scientific communication model, initially

described by Garvey & Griffith.

The fundamental paradigm of scientific communication will transform when scientific

organizations redefine roles and extend collaboration for services. This reorganization is

under way, particularly in big science, characterized by enormous facilities, with vast data

banks. The Scholarly Publishing and Academic Resources Coalition (SPARC) is an

example of “a redefined role for organizations” (ibid); this coalition emerged as an effort

to reduce costs of serials. Gradually, transformation of roles and channels of

communication will materialize, but, as yet, the scientific communication system that has

been in place for generations continues, with updated communication features.

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Patents, Intellectual Property, and Digital Data Depositories

Baldwin (2005) observes a few other unique features of scientific disciplines. Of note is

her reference to Standard 1, Performance Indicator 2, and Standard 2, Performance

Indicator 2. Both of these performances relate to intellectual property – Standard 1 lists

“patent literature”; Standard 2 lists “research data as intellectual property” (ACRL, 2006).

These two performance indicators are closely related and have become critical issues

among scientists, particularly those involved in “megascience.”

The United States Patent and Trade Office (USPTO), an agency of the U.S. Department

of Commerce, includes intellectual property in its concept of a patent. Its purpose “serves

the interest of inventors and businesses with respect to their inventions and corporate

products, and service identifications” (USPTO, 2006). The United States Patent and Trade

Office defines intellectual property as:

Creations of the mind – creative works or ideas embodied

in a form that can be shared or can enable others to

recreate, emulate, or manufacture them (USPTO, 2006).

More fundamentally, intellectual property is a claim to property; it is similar to ownership

of physical property – one has rights of entitlement and controls what happens to such

property within legal parameters. Intellectual property differs from physical property by its

term limits – intellectual property is limited to a specific number of years, depending on

the way one has protected one’s invention, production, or authorship.

According to the USPTO, there are four ways to protect intellectual property – patents,

trademarks, copyrights, and trade secrets (2006). Each form of intellectual property is

purposed to protect a specific form of creation. In science, patents, trademarks, and trade

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secrets apply most frequently. “Raw” scientific data or primary data in science are the

material of scientific discovery and invention; these data have been generated through

scientific investigation and experimentation (often funded by organizational or national

agencies), and is regarded as the wellspring of scientific achievement. Data are

scientifically raw as the producer, the scientist, has not published the findings and

interpreted them within a theoretical or conceptual framework. Customarily, scientists can

protect their data by patenting it.

Patents on data occur most frequently in individual-investigator driven research such as

chemistry or psychology. If patented, such data are granted protection like physical

property. Once acquired, a patent (or trademark) grants a property right for the data to the

inventor, discoverer, or scientist. This grant offers “the right to exclude others from

making, using, offering for sale, selling or importing the invention” (ibid). There is legal

ownership and precedent to claim all rights to the property, though it is incumbent upon

the patentee to enforce the patent, usually with the aid of legal counsel.

There are three types of patents: utility patents, design patents, and plant patents. The

utility patent is defined as “any new and useful process, machine, article of manufacture,

or composition of matter, or any new and useful improvement thereof” (ibid). It is the

utility patent that applies to scientific and technological discovery or invention, in other

words, raw data. Design patents relate to “ornamental design for an article of manufacture”

(ibid), and plant patents relate to the reproduction of “any distinct and new variety of

plant” (ibid).

Information literacy in science requires an understanding of intellectual property as it

pertains to science. The laws and conventions of patents relating to science have now

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become not only arcane, but also rather murky. Over the last two decades, law relating to

patents, particularly when government funding has supported investigation, has become

subtle and unstable. In 1996, the Human Genome Project (HGP) adopted data release

principles, preventing a scientist from acquiring a patent on his/her possible discovery in

genome sequencing. The central principle states,

"human genomic sequence information

generated by centers funded for large-scale

sequencing should be freely available and

in the public domain...."

This policy supports active research and development (R&D), but it is controversial.

The potential for merit and collaborative work is enormous. However, while an open

access depository, in other words data in the public domain, is desirable for large-scale

scientific investigation and advancement, those who have produced valuable data, but have

not finalized interpretation of the data, basically have no legal entitlement as producers of

these data. “There are no formal restrictions on its use” – no proprietary rights (Rowen,

Wong, Lane, & Hood, 2000). All investigative findings, or primary data, deposited in

GenBank, the Humane Genome Project database or depository, are available to the public

as well as the scientific community without any rights of ownership.

Similar conditions apply to several projects that would be classified as “big science” or

“megascience” (Reichman & Uhlir, 2006). Such sciences use large research facilities with

“facility class” instruments usually characterized as “observational and experimental”

(ibid). A notable example of a large-scale observational investigation would be NASA’s

Apollo program. Examples of large observational facilities would include space science

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satellites, earth observation satellites, and automated genome decoding machines. In the

experimental sciences, examples of large-scale facilities include large lasers, high-field

magnet labs, and supercolliders for high-energy particle physics.

Scientific investigation in small, independent, investigator research differs in character

from megascience endeavors. Sciences such as psychology, microbiology, anthropology,

environmental science, or biodiversity do not require a large-scale facility. They are labor

intensive, depend on replicable experiments with replicable findings, require relatively

small samples that are collected individually, and produce small data sets that are analyzed

individually and independently. In this labor-intensive situation, primary data are

traditionally proprietary and rarely deposited in open access databases. Patented or not,

independent, investigative research and data collected are tacitly proprietary.

The Organization for Economic Cooperation and Development (OECD) is actively

involved in setting policy or international rules and guidelines with regard to the exchange

of scientific data, information, and knowledge (OECD, 2004). It is specifically addressing

the establishment of access regulations for digital research data from public funding, and

protecting intellectual property rights including trade secrets with international and

national law. This involves creating new mechanisms and practices supporting

international collaboration in access to digital research data (ibid).

The National Research Council (NRC) has recognized the difficulty inherent in

protecting the rights of those who create information products and services as well as those

scientists contributing to open access depositories. The balance between maximizing

access to digital information and protecting owners is viewed as a significant legal issue,

with “broad implications” (NRC, 2000). Within this context, the federal government has

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added an “Information Sector” (ibid) to the classification of industries. While the

unprecedented production of and access to digital information enriches society, this

enrichment can also be exploited, violating the rights of those who have contributed to

scientific discovery or produced information of use. As stated in The Digital Dilemma:

Intellectual Property in the Information Age:

The Web is an information resource of extraordinary

size and depth, yet it is also an information

reproduction and dissemination facility of great

reach and capability; it is at once one of the world’s

largest libraries and surely the world’s largest

copying machine.

Intellectual property law regarding projects that receive public funding and open

access depositories is still an open issue. No explicit, clear-cut answers or legal recourse

has been established to protect contributing scientists, though legislation, international

lawmakers, and organizations are looking carefully at this dilemma and proposing

solutions. Within the scientific community, tacit law and ethics govern those who would

observe community. Nonetheless, should an imposter claim ownership, the tale would not

be one of an idiot – it would be a word to the wise. The “dark lady” of DNA, Rosalind

Franklin, looms large when one speculates on the meaning of proprietary rights and

scientific data.

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