Abstract:
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, computer programs, graphics, audio, spreadsheets, or any other material which may be stored and indexed. Database material may be in one or multiple sources, and annotations may be stored together with the original material or in a separate store. Annotations can 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 captured in a structured form to enhance queryability and semantic interpretation.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
   The present application is a divisional of U.S. patent application, Ser. No. 09/429,550, filed on Oct. 28, 1999, now U.S. Pat. No. 6,519,603, which is assigned to the same assignee as the present application and which is incorporated herein by reference. 

   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&#39;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 advice pertaining to the expertise understood by that discipline. Filtering and transforming the entered annotation content based on the context of the reader can be used to retrieve only relevant information, or to “hide” information to which this reader context is unauthorised, or to present the information in a form easily understood by the discipline or role of the reader. Multiple annotations from authors with different contexts or within the same context can be attached to a single annotatable data item. 
   It should be understood that the foregoing capabilities encompass a single annotation structure containing an attribute such as “Comment” or “URL” for every annotatable data item, wherein annotations of this type are entered and retrieved in the same way by all author/readers. 
   The method of the present invention is outlined as follows: The type of annotatable data item is identified and the allowed structures for this type are registered. A type may include, but is not limited to, “set of rows of table x” or “any cell in column y of spreadsheet z”. This registration step can be done as a pre-processing step or may be done immediately before annotation entry. 
   For annotation entry, an annotatable data item is chosen (e.g. a 5th cell in column y of spreadsheet z) and an annotation is entered and stored. The annotation is associated with the annotatable data item at the time of entry by including pointer information to the annotatable data item with the annotation. Optionally, the annotation may be “propagated” or automatically associated with additional annotatable data items using extra information defined in the registration step. Once annotations have been stored, queries may be issued to retrieve both the annotation content and/or the database material. 
   There are a number of query modes possible. In the first mode, the reader may browse the annotations in the context of the database material. That is, the reader identifies the specific database material of interest and all accompanying annotations are retrieved. This is achieved by issuing a query using the pointer information stored with the annotations. This mode is useful when the reader is perusing database material and wants to read annotations that contain related information or links to related information. 
   A second mode refers to querying for particular annotations in the context of the data. That is, the reader first identifies the database material of interest. This may include identifying an annotatable data item or a type of annotatable data item. In the case of an annotatable data item, the reader asks for the accompanying annotations with particular characteristics, (e.g. where the author field contains Smith). In the case of a type, the reader may ask for elements of the type whose annotations have particular characteristics. A query is issued that uses the pointer information and specifies a filter on the annotation content. 
   The reader may alternatively ask for only the elements of the type and their annotations where the elements of the type and their annotations both have filters on their content. In this case, a query is issued that uses the pointer information and specifies a filter on the annotation content and also a filter on the data content. 
   The second mode is useful when the reader wishes to review only certain annotations that relate to the data (e.g. all those by expert X) or when the reader wishes to focus on particular database material and annotation content (e.g. find all the data and annotations about drug molecules that have biological activity greater than x (data content) and for which the experts said the experimental measurement was reliable (annotation content)). 
   The third mode involves querying across the full body of annotations, regardless of the database material being annotated. This may be used, for example, for locating all annotations containing a particular category or for locating annotations containing particular content. For example, an exemplary query can be: How many times has Simulation package x been used to generate production estimates? 
   The fourth mode involves querying for particular data in the context of the annotations, is an extension of the third mode. In this case, the query retrieves not only the annotations of interest but also the database material that they annotate. For example, in the fourth mode, the answer to the above exemplary query: “How many times has Simulation package x been used to generate production estimates?” might include not only how many times the package x has been used but also the values of the production estimates. This mode also uses the pointer information in order to formulate the query to retrieve the appropriate database material. 
   According to a preferred embodiment, an information management method is implemented by the information management system, whereby one or more users such as administrators, annotation authors, readers, and/or applications, start the information management method of the present invention by setting up an annotation structure. Using the information management system, a user is capable of performing any one or more of the following tasks or processes:
         Enter annotations about the data or fields by various input means.   Browse annotations in the context of data.   Simultaneously query for both annotations and data.   Query for particular annotations in the context of data.   Query across the full body of annotations.   Query for particular data in the context of the annotations.       

   It is therefore clear that the information management system is not domain specific, in that it can be used in combination with any application regardless of the complexities of the underlying technical or professional fields. The data model for the annotations (i.e., the annotation metadata model) is generic, self-describing, and self-contained. 
   The information management system is adaptable to the user&#39;s query preferences in that the information management system provides the ability to operate in a data-centric mode or in an annotation-centric mode. The data centric-mode will be explained in connection with  FIGS. 5 and 6 , and allows the user to select desired data items and to subsequently query and retrieve data and annotations based on these data items. The annotation-centric mode will be explained in connection with  FIGS. 7 and 8 , and allows the user to select the annotation categories and to subsequently query and retrieve data and annotations based on the content of the selected annotation categories. As a result, the information management system allows both data and annotations to be queried, in that queries can be made over the data content, over the annotation content, or over both simultaneously. This provides the ability to query the annotations, or the annotations and the data, and further provides the ability to retrieve the annotations when their associated data is retrieved. 
   Yet another feature of the information management system is its ability to allow annotations to be targeted to, or associated with data at different levels of granularities, such as: collection/view/table, attribute/column, instance/row, cell, arbitrary combinations thereof, and so forth. 
   Still another feature of the information management system is its ability to support storage and retrieval of annotations with a generic structure or a more specific structure, where the structure can depend on the nature of the data being annotated and the context of the author of the annotation. 
   In addition, the information management system is capable of supporting annotations of data in a variety of sources, formats, and/or data models. The information management system can annotate data in multiple sources when coupled with a data integration engine, in only one source, or in any source regardless of the source&#39;s data model (diverse sources). Further, the information management system can annotate views on the data in these sources, without requiring the data sources being annotated to be modified. The information management system can have multiple annotations for the same data object, and different annotations on the same data item can be entered by different people/applications or by the same person/application at different times. Moreover, when the annotations are retrieved, they can be filtered or modified in a way that depends on the context of the reader. The annotations can also be propagated to specific target data items that can be selected from a drop down list, or by entering a free format text, numeric, document, URL, and so forth. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The various features of the present invention and the manner of attaining them will be described in greater detail with reference to the following description, claims, and drawings, wherein reference numerals are reused, where appropriate, to indicate a correspondence between the referenced items. 
       FIG. 1  is a high level architecture of an information management system according to the present invention. 
       FIG. 1A  is a diagram of an exemplary embodiment of the information management system of  FIG. 1 ; 
       FIG. 2  is a schematic of an exemplary computer screen that can be generated using the information management system of  FIG. 1 . 
       FIGS. 3A–3D  represent a flow chart that illustrates a process of setting up the annotation structure using the information management system of  FIG. 1 . 
       FIG. 4  is a flow chart that illustrates a process of writing an annotation using the information management system of  FIG. 1 . 
       FIG. 5  is a flow chart that illustrates a process of browsing an annotation in the context of data, using the information management system of  FIG. 1 . 
       FIG. 6  is a flow chart that illustrates a process of querying for particular annotations in the context of data, using the information management system of  FIG. 1 . 
       FIG. 7  is a flow chart that illustrates a process of querying across the full body of annotations, using the information management system of  FIG. 1 . 
       FIG. 8  is a flow chart that illustrates a process of querying for particular data in the context of the annotations, using the information management system of  FIG. 1 . 
   

   DETAILED DESCRIPTION OF THE INVENTION 
     FIG. 1  illustrates a system  1  that might be utilized to practice the teachings of the present invention. The system  1  includes a plurality of computers or processors  2 ,  3 ,  4 . While for purposes of illustration the computers  2 ,  3 ,  4  are described as possessing specialized functions, it should be clear that any one, or a combination of the computers  2 ,  3 ,  4  can be used to generate the annotations, and to search the data and annotations sources (e.g. databases) as described herein. 
   As further illustrated in  FIG. 1A , computer  2  hosts an information management system  10  of the present invention, and includes, or is connected to one or multiple databases  14 ,  16  to be searched. Computer  2  is interconnected to computer  3  via an annotation input link  5  for allowing annotations to be inputted from computer  3  to computer  2 . The annotation input can be from a user of, for example, a graphical user interface (GUI) application, or from a software application, running for example on computer  3 . One or more input devices  7  can be used to provide information to computer  3 . These input devices may include, but are not limited to, keyboard devices, pointing devices, monitors, scanners, modems, inputs from other systems, microphones and voice recognition applications, and like devices. 
   Computer  2  is interconnected to computer  4  via an annotation output link  8  for allowing annotations to be outputted from computer  2  to computer  4 . The annotations and/or other data can be retrieved on the request of a user of, for example, a GUI application, or on the request of a software application running for example on computer  4 . The annotations and/or other data that are retrieved from the system  1  may be utilized of displayed by means of one or more of output devices  9 . These output devices  9  may include, but are not limited to, monitors, printers, modems, outputs to other systems, speakers and audio synthesizers, robots, storage systems, and like devices. 
     FIG. 1A  portrays the overall environment in which the information management system  10  can be used according to the present invention. The information management system  10  uses a data integration engine  12  that permits users and/or applications to pose queries against data that may reside in multiple data sources, such as databases  14  and  16 . As used herein, an integration engine can be any application system that can accept a query against one or multiple data sources in any form and that returns the requested data from one or multiple data source in any desired form. An exemplary data integration engine  12  is available from International Business Machines under the trademark DataJoiner®. Using the data integration engine  12 , annotations can be made on data from a broad variety of existing sources, regardless of their locations. It further enables the independent storage of annotations, such as in an annotation database  20 , without impacting the users&#39; applications  22 , or databases  14 ,  16 . In the case where the user/application only wishes to annotate data in a single datasource, it is possible to writes the annotations in the same datasource, and a data integration engine is not needed. 
   A query/browser/annotator  25  is a separate application that provides users (represented by computer  27 ) with a graphical user interface (GUI) to facilitate the interaction with the information management system  10 . Using the query/browser/annotator  25 , the users can find, view, and annotate data. 
     FIG. 2  is a schematic of an exemplary computer screen  50  that can be generated using the information management system  10  of  FIG. 1 . The screen  50  provides an example of how a user  27  can query data in the business area of oil exploration and production. The screen  50  shows a data collection that describes the company&#39;s oil fields. The names of the oil fields are displayed in the first column  88 . The different attributes of the view are shown in the first row  89 . A complex query can be posed by placing predicates in the second row  92  and in block  91 . The query illustrated in  FIG. 2  asks for rows that have a Reserve value that is greater than 300, Units in Bcf, and a Certainty factor that is greater than 70%, as well as a Usage appropriate for Tax Purposes. Usage is actually an annotation category on cells in the Reserve data column. As a result, this exemplary query combines attributes of the data along with the annotation content to qualify the results. 
   The result of this query is shown in the third row. Various annotations on the retrieved values or data of this row are shown attached to the bar. It should be understood that one value or data may have multiple annotations, of multiple types, and that different values may have different sorts of annotations. The formats of the annotations depend on the discipline or context of the persons or applications writing, reading, or entering the annotations. For example, a reservoir engineer might add an annotation about a reserve simulation, but an accountant would add annotations about the financial analysis. 
   In operation, one or more users, such as an administrator  27 , or the client application  22 , start the information management method of the present invention by setting up an annotation structure, as illustrated in  FIGS. 3A–3D  The information management system  10  is capable of performing any one or more of the following tasks or processes, with the understanding that it can perform other tasks as well:
         Entering annotations about the data or fields by various input means, as illustrated in  FIG. 4 . These annotations are preferably stored in a separate database  20 . It should however be understood that the annotations can be stored in the same data sources (i.e.,  14 ,  16 ) as the data.   Browsing annotations in the context of data, as illustrated in  FIG. 5 .   Simultaneously query for both annotations and data.   Querying for particular annotations in the context of data, as illustrated in  FIG. 6 .   Querying across the full body of annotations, as illustrated in  FIG. 7 .   Querying for particular data in the context of the annotations, as illustrated in  FIG. 8 .       

   The foregoing tasks will now be described in greater detail with reference to their respective drawings. Starting with the process of setting up or organizing the annotation structure  100  ( FIG. 3A ), an administrator  27 , for example, identifies data items or data item types to be annotated, as shown in block or step  105 . An annotatable data item can be a table, a view, a row, a cell, a column or 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. Specification of an annotatable data item allows any of a whole set of similar annotatable data items to have the same annotation structure. For example, “any object in class y”, “any row in table x”, “any cell in column a of table b”. This greatly facilitates the annotation structure setup and registers the availability of annotation structures for data that has not yet been input, such as the addition of rows to a table or objects to a class. The data items and data item types can originate from a single source or from multiple sources  14 ,  16 . In the example of  FIG. 2 , one of the data item types to be annotated is any cell which is listed in the column whose attribute is “Reserve”. 
   The annotatable data item to be annotated can be selected by selecting an attribute or attributes of an entity, where the entity can be referenced, for example, by an index, a schema object or objects, or any arbitrary set of such attributes and/or schema objects. As used herein, a schema object can be, for example, a table, a class, an attribute of a class, a view, a column, a function, or any combination thereof. 
   The administrator  27  then selects or enters a context, if one does not already exist, for the annotation author as illustrated in block  110 . The term “context” denotes a discipline, or a role being performed by a person of a particular discipline. In the above example, it is possible to allow persons of different disciplines to annotate various data items. For illustration purposes, it is possible to allow reservoir engineers, geologists and/or chemists to enter different types of information in their annotations. 
   Since multiple types of information can be captured in an annotation about each data item, the administrator  27  can enter a category of information to be captured about the data item, as illustrated in block  115 . These categories can be factual or interpretive in nature. Examples include, but are not limited to the origin of the data (factual), the quality of the data (interpretive), and appropriate use of the data (factual and/or interpretive). The administrator  27  enters a desired category (block  115 ). 
   The method  100  then automatically determines if the selected category already exists (block  120 ). If the selected category does not exist, the administrator  27  enters the list of attributes for this category and how the annotation content will be defined for these attributes (block  125 ). As an example, for the category origin of data, three attributes might be: vendor name, install date, and the name of the person who performed the installation. 
   Annotation content can be associated with these attributes, during subsequent annotation entry, by any of several mechanisms, including but not limited to the following mechanisms:
         A list of values (pick-list) from which an annotation author can select.   Qualifying datatypes for the values, e.g. text, numeric, document, URL, and so forth.       

   The method  100  then automatically inquires the administrator  27  at block  130  if another category is required for the selected data item. If the administrator  27  determines that another category is needed, the method  100  repeats the set of steps or blocks  115 ,  120 ,  125 , and  130 , until the administrator  27  determines at block  130  that no additional categories are needed for the selected data item. 
   If at block  120  the method  100  determines that the selected category already exists, the method  100  proceeds to block  130  and inquires if an additional category is required for the selected data item. If at block  130  the administrator  27  instructs the method  100  that no additional category is needed, the method  100  proceeds to block  135  ( FIG. 3B ), for allowing the administrator  27  to define the annotation structure from the selected categories, to assemble the categories, and to associate the annotation structure with the annotatable data items. 
   In the example of  FIG. 2 , the administrator  27  defines the annotation structure by identifying the desired categories and the order in which the annotation content will be entered and/or displayed. For illustration purposes, the annotation structure for cell  75  includes three categories: The first category  77  represents the annotation author&#39;s category, and provides information (in the form of annotations), for instance, about the author&#39;s name, the context or author&#39;s discipline, and the entry date. The second category  78  represents the simulation category, and provides information about the person who ran the simulation, e.g. reservoir engineer&#39;s name, the type of oil well simulation, the location of the simulation reference files, and the simulation date. The third category  79  represents the usage category, and provides information about the usage of data in cell  75  that can be used for tax purposes, the person who authorized this use of the data, and further comments about the use. While the foregoing example is explained in light of certain specific entries, it should be clear that alternative entries and/or categories can be used. 
   Once the annotation structure is defined at block  135 , the method  100  automatically determines at block  140  whether this annotation structure already exists, since annotation structures can be reused. If the method  100  determines that the annotation structure does not exist, the administrator  27  builds a new annotation structure from the selected categories (block  145 ), as explained above in connection with block  135 . The annotation structure can be built automatically from concatenation of the annotation categories. If the method  100  determines that the annotation structure already exists, it proceeds to block  150 . 
   The method  100  associates the annotation structures with the annotatable data item. Annotation structures can vary according to the data item being annotated and/or to the context of the annotation author. Multiple annotations with differing or identical structures can be assigned to the same data item. It should be clear that the contexts can be defined for groups of people (or applications) or on an individual basis. 
   When the annotation structure assignment is completed at block  150 , the method  100  can proceed to decision block  155  ( FIG. 3C ). Optionally, the method  100  can perform a template transforming (or filtering) loop illustrated by blocks  155 ,  160 ,  165 ,  170 , and/or an annotation propagation loop illustrated by blocks  175 ,  180 . 
   The template transforming loop can be automatically initiated by the method  100  at the decision block  155 , whereby, the method  100  inquires whether the administrator  27  (or application  22 ) wishes to specify a filter or modify a template to reflect the reader&#39;s context. The administrator  27  indicates which categories are to be retained, which attributes within these categories are to be retained, which attribute names are to be changed and how, and more generally transformations that should be applied to the annotation content. 
   For illustration purposes, if the reader is a reservoir engineer, he or she might not be interested in retrieving annotations by accountants, since these may not be relevant to their work. Alternatively, a reader who is a project manager might not be interested in, or may not be allowed to see the simulation category of the annotation. 
   If the administrator  27  determines at decision block  155  that a filter and/or a template is needed, the administrator  27  enters a reader context, such as “Reservoir Engineer” ( FIG. 2 ), as shown by block  160 . The administrator  27  then specifies a corresponding reader template at block  165 , and the method  100  inquires at decision block  170  whether templates for additional reader contexts are desired. 
   If the administrator  27  determines at block  170  that a template for an additional reader context is desired, the method  100  proceeds to block  160  and repeats the reader selection loop comprised of steps  160 ,  165 ,  170 , until the administrator  27  determines at block  170  that no additional templates are desired. 
   When the reader selection loop terminates, or if the method  100  determines at step  155  that neither a filter nor a template is needed, the method  100  proceeds to decision block  175  and inquires whether or not the administrator  27  wishes to propagate the annotations about the selected data item. When the annotation structures are assigned to the data items, the method  100  enables the annotations written through these structures to be propagated to other data items. For example, a data item that describes the depth of an oil well could appear in many views pertaining to oil wells. Annotations about a depth value could be propagated to all of these views, not just the one against which the annotation was entered. In the example of  FIG. 2 , the data in cell  75  could appear in different views suitable for accountants, geologists, chemists, reservoir engineers and/or viewers of other disciplines. In many of these cases, the viewers might also want to see the annotations entered by the reservoir engineer in their views. If at step  175  the administrator  27  determines that no propagation is desired, the method  100  proceeds to decision block  185  and inquires whether or not additional contexts for the annotation authors are desired, as it will be explained later. 
   If at block  175  the method  100  determines that the annotations need to be propagated, the method  100  allows the administrator  27  to specify the target data items or data item types to receive the propagated annotations (block  180 ). These target data items can be selected from a drop down list and/or by entering text. The method  100  then proceeds to decision block  185  and inquires whether or not additional contexts for the annotation authors are desired. If the answer to this inquiry is in the affirmative, the method  100  loops back to block  110 , and performs the loop comprised of the steps between blocks  110  and  185 , as described above, until the administrator  27  determines that no additional context for the annotation authors is needed. 
   When the latter condition is satisfied, the method  100  proceeds to block  190  and inquires whether or not the user  27  needs to select additional data items. If no additional data items need to be selected, the method  100  is terminated at block  195 . If, on the other hand, additional data items need to be selected, the method  100  loops back to block  105 , and performs the loop comprised of the steps between blocks  105  and  190 , as described above, until the method  100  is terminated at step  195 . 
   Once the information management system  10  is set up according to the method  100 , the system  10  will be ready to be used by the annotation authors, readers, and applications.  FIGS. 4 through 8  illustrate exemplary methods of using the information management system  10 . In summary,  FIG. 4  illustrates the process of writing or inputting an annotation,  FIG. 5  illustrates the process of browsing an annotation in the context of data,  FIG. 6  illustrates the process of querying for particular annotations in the context of data,  FIG. 7  illustrates the process of querying across the full body of annotations, and  FIG. 8  illustrates the process of querying for particular data in the context of the annotations. 
     FIG. 4  illustrates a method  200  of writing an annotation using the information management system  10  of  FIG. 1 . The user, such as an author  27  (and/or the application  22 ) starts at block  205  by selecting the data item to be annotated, and further enters the annotation content corresponding to a predefined annotation structure at block  210 . The method  200  then stores the annotations in the data store  20  ( FIG. 1 ), for subsequent retrieval using the browse or query capabilities of the information management system  10 . 
     FIG. 5  illustrates a method  250  for reading or browsing the annotations in the context of the data. For example, if a reader  27  (and/or an application  22 ) wishes to review or browse annotations about members of the data collection or view of interest, the information management system  10  is capable of retrieving and displaying the requested annotations. Structured Query Language (SQL) is an example of a language that can be used to search for, and return the annotations. 
   The method  250  begins at block  255  by having the reader  27  select the data of interest. The method  250  then inquires at block  260  if the reader wishes to view the annotations. If not, the method  250  terminates at block  263 . If the reply to this inquiry is in the affirmative, the annotations corresponding to the data items within the data collection are retrieved on request from the data storage  20 . The annotation content can be returned as written or, alternatively, filtered or modified in a way that depends on the context of the reader. 
   The method  250  proceeds to the decision block  270  and inquires if the requested annotation content is subject to filtering, transformation or modification. If it is, the method  250  proceeds to block  275  and performs the necessary filtering, transformation and/or modification, and then returns or displays the requested annotations at block  280 . If on the other hand, the method  250  determines that filtering, transformation and/or modification is not required, it returns or displays the requested annotations at block  280 . The loop comprised of blocks  270 ,  275 , and  280  will hereinafter be referred to as the transforming loop  290 . 
     FIG. 6  illustrates a method  300  for querying annotations in the context of the data, or in other terms. The method  300  performs a “combined” query, with conditions (predicates) on both data and annotation content. A reader  27  selects a data item type or data collection of interest (block  305 ), and enters query predicates conforming to predefined annotation structures for annotations on the data items in the selected data collection or associated with the data item type (block  310 ). If the reader  27  wishes to enter query predicates on the data items themselves (decision block  315 ), the reader specifies the data item queries (block  320 ). In response, the method  300  retrieves the annotations and data conforming to the reader&#39;s query predicates (block  325 ). The annotation content can be returned as written or, alternatively, filtered or modified in a way that depends on the context of the reader. If the reader  27  does not wish to query predicates on the data items themselves (decision block  315 ), the method  300  proceeds to block  325 . If needed, the method  300  performs the transforming loop  290  as discussed above in connection with  FIG. 5 . 
     FIG. 7  illustrates a method  350  for querying annotations across the full body of available annotations. The reader  27  selects the annotation category or categories of interest (block  355 ), and enters query predicates based on the definition of the selected category or categories (block  360 ). The method  350  retrieves all the annotations that obey the query predicates regardless of the annotation structure (block  365 ). The annotation content can be returned as written or, alternatively, filtered or modified in a way that depends on the context of the reader. If needed, the method  350  performs the transforming loop  290  as discussed above in connection with  FIG. 5 . 
     FIG. 8  illustrates a method  400  for querying for particular data in the context of the annotations, which method  400  is therefore said to be annotation-centric. The reader  27  selects the annotation category or categories of interest (block  405 ), and enters query predicates based on the definition of the selected category or categories (block  410 ). The method  400  retrieves all the annotations and the data items associated with the annotations that obey the annotation query predicates (block  415 ). The annotation content can be returned as written or, alternatively, filtered or modified in a way that depends on the context of the reader. Optionally, the method  400  can sort the retrieved data and annotations by the type of the data collection (block  420 ). If needed, the method  400  performs the transforming loop  290  as discussed above in connection with  FIG. 5 . 
   It is to be understood that the specific embodiments of the invention that have been described above are merely illustrative of one application of the principles of the present invention. Numerous modifications may be made to the information management system and associated methods described herein without departing from the spirit and scope of the present invention. For example, while the information management method is described in terms of a computer, it should be understood that this method can be implemented without the use of a computer, and as such it can cover a method of conducting business and other information management tasks.