Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1999-10-28
2003-02-11
Shah, Sanjiv (Department: 2172)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000
Reexamination Certificate
active
06519603
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to the field of data entry and retrieval. Specifically, the present invention relates to a method and system having the capability to organize an annotation structure and to query both data and annotations in computer systems. More particularly, the present invention enables the annotation of stored information, and permits the capture, sharing, and querying of data and annotations.
BACKGROUND OF THE INVENTION
Successful planning and decision making in many technical and other industries depends on the expeditious and correct interpretation of complex information. For example, in the drug industry the data may have origins as diverse as high throughput screening experiments, clinical trials, patent information and research journals. In the petroleum industry the data may span seismic measurements, aerial surveys, laboratory data and economic forecasts. A system capable of providing unified access to disparate data sources and applications reduces the time spent finding, accessing, preparing, transforming and reformatting data, and allows professionals to focus on the interpretation and extraction of knowledge for planning and decision making.
However, one complication with providing this type of unified access is that the data inevitably spans several disciplines, with an attendant probability of misinterpretation. Extensive knowledge of multiple domains is required if misuse is to be avoided.
Therefore, there is still an unsatisfied need for an information management system that clarifies the generation, use, and purpose of the data. The information management system can capture knowledge about the genesis and history of the data, how analyses are done, how decisions are made, and what the outcomes are. This “corporate memory” forms the basis for the analysis required to make better technical and business decisions.
Several attempts have been made to access information based on annotations. Illustrative attempts are described in the following references:
U.S. Pat. No. 5,404,295 to Katz et al.
U.S. Pat. No. 5,600,775 to King et al.
U.S. Pat. No. 5,832,474 to Lopresti et al.
U.S. Pat. No. 5,548,739 to Yung.
For example, U.S. Pat. No. 5,404,295 describes a method and apparatus for computer retrieval of database material. Annotations are provided for selected database subdivisions and are converted to a structured form and stored in that form along with connections to corresponding subdivisions. Searching for relevant subdivisions involves entering a query in natural language or structured form, converting natural language queries to structured form, matching the structured form query against stored annotations, and retrieving database subdivisions connected to matched annotations.
However, the teaching of this patent is limited to a system with the capability to search the annotations to locate the database material. The system does not have the capability to search the stored information based on both the annotations and database material, or to search on database material to retrieve the annotations. As a result, the system is not suitable for directly locating a subset of data where the filter has predicates on both the annotations and database material. Rather, it will locate all database material that corresponds to the annotation predicates and it would require a second step to filter this subdivision and to apply the data predicates.
SUMMARY OF THE INVENTION
The present invention contemplates a method and apparatus for capturing annotations about database material in a way that allows queries with conditions or predicates on both the database material and the annotations. Database material may be text, graphics, spreadsheets, relational tables or any other material which may be stored and indexed. An annotatable data item (i.e. the subsection of database material that can be annotated) is any entity referenced by an index (e.g. by an object identifier) or any attribute or subcomponent of such an entity, or any arbitrary set of such items. Examples include a table such as a relational table or spreadsheet, a view such as a relational view, a row within a table, a cell within a table (i.e. the intersection of a column and a row), a column within a table, an object, an attribute of an object, a set of rows or columns from one table, or a set of rows from different tables. The annotatable data items may be in a single source or multiple sources, or span such sources. Multiple annotations may be entered for a single annotatable data item.
The annotations, together with the pointer information that relates them to the original database material, may be stored in a separate source so that the data model and operation of the sources containing the original database material is not affected. It is the pointer information that allows formulation of the queries to retrieve either annotations related to specific database material or database material related to specific annotations.
Annotations may be used to capture information such as additional facts about the database material, the opinions and judgments of experts about the database material, and/or links to other related material. Annotations may be entered manually or automatically by an application. Henceforth, the person or application that enters an annotation will be referred to as an annotation author, and the person or application that retrieves annotation and/or database material will be referred to as the reader.
Annotations may be captured in structured form to enhance queryability and semantic interpretation as well as to provide some order for users to enter this additional information content. The entry of comments in an unorganized and undisciplined way can often lead to more data with little useful content. The structure is comprised of labeled categories, to aid semantic interpretation. The annotation structure could be as simple as a “header” category containing attributes (or fields) about whom and when the person or application wrote the annotation, together with a “business meaning” category containing a single “Comment” field for a textual description of the data item being annotated. In this example, the title of the latter category, “business meaning” can aid in the interpretation of the “Comment” field. An annotation structure may be more complicated than the one illustrated above and contain many categories, each of which contains a number of attributes. Some or all of these attributes may have constraints placed on their values. For example, the constraints may be on the datatype (e.g. numeric, character) and/or on their values, so that users have to enter values consistent with a particular datatype or consistent with an input list or pick-list. The constraints enforce more structure and consistency in the annotation content and also enhance the queryability with today's query engines.
It is the capture and query of information from experts represents one important feature of the present invention. To this end, the present method offers the capability to allow standardized structure of annotations based on the “group” to which the author and reader belong, as well as on the data item being annotated. A group can be as small as one person, in which case there can be a personalized annotation structure, or it can contain a “related” set of people, such as people of a particular discipline or performing a particular role. Henceforth, group will be referred to as a “context”. There is a context associated with the annotation author as well as the reader. Thus, it is permitted for the structure for the entry of an annotation about any one data item to be different depending on the context of the author, and for this information to be presented differently on retrieval depending on the context of the reader. These structures that are associated with contexts, can be used to give a level of credibility to the annotations. That is, the annotation structure may be set up such that only experts in a given discipline (context) can enter information or ad
Bays Alan Ronald
Haas Laura Myers
Horn Hans Werner
Rice Julia Elizabeth
Schwarz Peter Martin
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