Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
2000-02-25
2004-12-07
Robinson, Greta (Department: 2177)
Data processing: database and file management or data structures
Database design
Data structure types
C345S215000
Reexamination Certificate
active
06829615
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to a computer- and software-based system and method for viewing a domain of information represented as a network of data objects that are connected or associated by relationships. The domain of information is presented to a computer system user via a graphical user interface permitting the domain to be viewed along various data object type axes so the context and relationships are revealed and both structure and detail are presented at the same time.
BACKGROUND OF THE INVENTION
The so-called modem “information age” has meant that more people have access to more information that at any point in human history. The proliferation of the Internet, World Wide Web, organizational intranets and e-mail has meant that information about nearly any topic is almost immediately accessible.
In fact, information is not merely readily “available.” Huge amounts of information is often targeted to individuals who scarcely have time to view and process it. Thus, the second—and ongoing—stage of the information age revolution is the well-documented problem of “information glut.” In short, so much information is available, much of it targeted, that it overwhelms even the most dedicated person. It is not uncommon, for example, to hear of overwhelmed corporate executives spending hours each day sifting through hundreds of e-mails. Virtually every user of the Internet has experienced the frustration of seeking information on a topic by using a “search engine,” only to receive hundreds of thousands or even millions of “hits.”
In the organizational context, the problem of information glut is particularly acute. For example, a profit-oriented business organization may have hundreds or thousands of employees and support personnel. Each may have a different title, role, specialty, education and job history. Each may work on several different projects. Each may generate thousands of e-mails per year. Each may generate dozens or hundreds of documents per year. Each document may have several recipients. The organization may have several different departments, each having a number of product lines. The organization may have a number of geographically separated sites or factories. The organization may have a number of corporate affiliates, such as partly or wholly owned subsidiaries or parent organizations. The organization may be associated with a number of suppliers, support entities, dealers, distributors, retailers and so forth.
As can be appreciated, the aforementioned various aspects or attributes of an organization represent information or organizational “knowledge.” An organization is more efficient if it can manage—that is, collect and process—this information so as to derive the inherent benefits of this organizational knowledge. In an era where “information is power,” the effective management of organizational knowledge can be the difference between enterprises that fail and those that thrive.
As mentioned above, the problem of “information glut” is particularly acute in the organizational context. This is partly because of the pure “heft” or quantity of information. This is the case also because of the many relationships between discrete pieces of information or “data items.” These relationships not only present issues as to how the data items should be organized and presented; the interrelationships between data items represent information in themselves. In fact, discerning otherwise not-readily-apparent relationships is very often the key to truly understanding data items. The difficulty, however, and the challenge of organizational knowledge management, is that as the number of data items increases, the number of interrelationships tends to increase even faster, to the point where the capacity of the human brain to process and order this information is quickly overrun.
Several approaches to more effectively managing information in the computer age have been proposed and have fallen substantially short. So-called “push” technology has been used to automatically and selectively retrieve information from the Internet so that users receive only what they want. Typically, the user identifies topics or sites of interest, and a server will periodically retrieve updated information to be downloaded in the form of browser pages or a screen saver with summaries and links to additional information. One example of push technology is the product previously marketed as PointCast™ (and, more recently, as EntryPoint™) by PointCast, Incorporated. However, push technology suffers from the drawback that it does not reveal relationships between distinct data items. Nor does it allow for the presentation of multiple data items so as to present detail and structure at the same time. In short, push technology may alleviate some of the information glut for the solitary Internet user, but it has little application to the organizational knowledge problem described above.
Another attempt to solve the information glut problem has been so-called “data mining,” such as the Suite 101™ on-line “community-based web guide” offered by the Mining Company at the site www.suite101.com. In this approach, dedicated editors retrieve and review information on a variety of topics from selected sites on the Internet. Somewhat analogous to the “thumbs-up, thumbs-down” paradigm for reviewing movies and the theater, these editors attempt to direct users to the best of the Internet through the use of summaries and reviews. However, data mining technology suffers from the same drawbacks as push technology when it comes to application in the organizational knowledge context.
Other approaches to processing distinct but interrelated data items include so-called “fuzzy logic” and “neural network” (sometimes loosely referred to “artificial intelligence”) processing algorithms. Speaking broadly, these approaches attempt to emulate the ability, if not the processing “architecture” outright, of the human brain insofar it is able to “sift” and “synthesize” otherwise unconnected pieces of data to discern new and broader meanings. Despite some of the initial fanfare which suggested that such automated systems would be able to “learn” and “think,” they have found little meaningful application outside of the scientific realm.
In sum, in an era that can be characterized as having increased organizational concentration, complexity, and competitiveness, the ability to process and discern the meaning of the huge quantity of organizational information remains a significant and, to date, unsolved problem.
Other problems and drawbacks exist.
SUMMARY OF THE INVENTION
Accordingly, it is one object of the present invention to overcome one or more of the aforementioned and other limitations of existing systems and methods for managing and processing discrete pieces of information, particularly in the context of an organization. The largely unfulfilled promise of artificial intelligence technologies and the like indicates that the human brain can be the superior processor, but only if the information can be presented without overwhelming the user. This is the significant challenge the present invention meets.
For these and like reasons, what is desired is a computer-based system and method for representing a domain of information as a network of data objects connected or associated by relationships so that both detail and structure are discernible.
It is another object of the invention to provide a computer-based system and method for representing such a domain of information where multiple types of data objects can be presented which are associated by multiple types of relationships.
It is another object of the invention to present such a domain of information whereby information can be derived by selecting a node object in a primary object set in order to establish its relationships to other, related node objects in secondary object sets.
It is yet another object of the computer-based system and method to present the domain of information as network in the form of a dynamic table of data objects which can
Goodwin James
Schirmer Andrew L.
Mintz Levin Cohn Ferris Glovsky and Popeo PC
Pannala S R
Robinson Greta
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