Patent Publication Number: US-8122052-B2

Title: Data model simplification through field fallout

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a divisional of co-pending U.S. patent application Ser. No. 10/353,666, filed Jan. 29, 2003, which is herein incorporated by reference in its entirety. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention generally relates to data processing and more particularly to simplifying the process of building database queries by limiting the number of fields presented to a user for building the database queries. 
     2. Description of the Related Art 
     Databases are computerized information storage and retrieval systems. A relational database management system is a computer database management system (DBMS) that uses relational techniques for storing and retrieving data. The most prevalent type of database is the relational database, a tabular database in which data is defined so that it can be reorganized and accessed in a number of different ways. A distributed database is one that can be dispersed or replicated among different points in a network. An object-oriented programming database is one that is congruent with the data defined in object classes and subclasses. 
     Regardless of the particular architecture, in a DBMS, a requesting entity (e.g., an application or the operating system) demands access to a specified database by issuing a database access request. Such requests may include, for instance, simple catalog lookup requests or transactions and combinations of transactions that operate to read, change and add specified records in the database. These requests are made using high-level query languages such as the Structured Query Language (SQL). Illustratively, SQL is used to make interactive queries for getting information from and updating a database such as International Business Machines&#39; (IBM) DB2, Microsoft&#39;s SQL Server, and database products from Oracle, Sybase, and Computer Associates. The term “query” denominates a set of commands for retrieving data from a stored database. Queries take the form of a command language that lets programmers and programs select, insert, update, find out the location of data, and so forth. 
     Queries are constructed of query conditions that serve to filter results returned from the query. Accordingly, a query may be thought of as group of filters put together to sift out only the data in which they are interested. Query conditions are typically constructed by specifying conditional operations on one or more fields in the targeted database. To facilitate query building, some applications may provide the user with a graphical user interface (GUI) presenting the user with a list of fields for use in specifying query conditions. 
     However, as the relative size and complexity of a data model increases, the number of fields presented to the user in the GUI may become unwieldy. In other words, the data model may easily grow beyond the ability for users to understand and use it. Typically, at least some of the fields presented in the GUI may be rarely (or never) used in building a query. By presenting these rarely used fields to the user, usability of the application targeting the data model suffers, as the GUI becomes too complex for the user to be able to see and understand how they might build a query to return desired data. 
     Accordingly, there is a need for an improved method for simplifying the query building process by limiting the number of fields presented to the user for building queries. 
     SUMMARY OF THE INVENTION 
     The present invention generally provides methods, articles of manufacture and systems for simplifying a query building process by limiting the number of fields presented to a user for building queries. 
     For some embodiments, a method of accessing data generally includes providing an interface allowing a user to build a database query based on a plurality of fields, monitoring use of the fields in building queries, and limiting fields presented to the user in the interface based on the monitored use of the fields in building queries. 
     For some embodiments, a method of providing access to data having a particular physical data representation generally includes providing an interface allowing a user to build a database query based on a plurality of logical fields corresponding to physical entities of the particular physical data representation, monitoring use of the logical fields in building queries, and limiting the logical fields presented to the user in the interface based on the monitored use of the logical fields in building queries. 
     For some embodiments, the article of manufacture generally includes a computer-readable medium containing a program which, when executed by a processor, performs operations for accessing data. The operations generally include providing an interface allowing a user to build a database query based on a plurality of logical fields mapped to physical entities of the particular physical data representation, monitoring use of the logical fields in building queries, and limiting the logical fields presented to the user in the interface based on the monitored use of the logical fields in building queries. 
     For some embodiments, the system generally includes a database, a data repository abstraction layer, a query building interface, and a fallout manager. The data repository abstraction layer may generally contain logical fields corresponding to physical entities of the database. The query building interface may be configured to allow a user to build a query to access the database by specifying query conditions based on the logical fields of the data repository abstraction layer. The fallout manager may be configured to control the logical fields presented by the query building interface based on usage characteristics of the logical fields in building queries. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       So that the manner in which the above recited features, advantages and objects of the present invention are attained and can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings. 
       It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments. 
         FIG. 1  is a computer system illustratively utilized in accordance with the present invention. 
         FIG. 2  is a relational view of software components of one embodiment of the present invention. 
         FIG. 3  is a flow chart illustrating exemplary operations for marking as hidden, or removing, fields in accordance with the present invention. 
         FIGS. 4A-4B  are exemplary graphical user interface (GUI) screens for building a database query in accordance with the present invention. 
         FIGS. 5A-5B  are flow charts illustrating exemplary operations for limiting the number of fields presented to a user and updating usage characteristics of fields, respectively, in accordance with the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The present invention generally is directed to systems, methods and articles of manufacture for simplifying the building of queries for accessing data in a data repository by limiting the number of fields presented to a user based on usage characteristics of the logical fields. In some embodiments, a data repository abstraction (DRA) layer provides a logical view of the data repository that is independent of the particular manner of data representation. The DRA layer may be actively managed to hide or remove logical fields that are not accessed often (or are not accessed within a predetermined period of time). By hiding or removing logical fields from the DRA layer, the number of logical fields presented to a user in a query building interface may be limited, thus simplifying the query building process. Further, by removing logical fields from the DRA layer altogether, the size of the DRA layer and associated processing overhead may be reduced, thus improving performance. 
     As used herein, the term database generally refers to any collection of data, regardless of the particular physical representation (or “schema”) and the terms database and data source may be used interchangeably. The term schema generically refers to a particular arrangement of data. In other words, a database may be organized according to a relational schema (accessible by SQL queries), an XML schema (accessible by XML queries), or any other schema presently known or to be developed. The term abstract query generally refers to a query composed of logical fields that may be mapped to physical entities of a database, regardless of a particular underlying physical representation. Embodiments of the present invention may be used to advantage when building abstract queries or conventional database queries. However, to facilitate understanding, embodiments of the present invention will be described below with reference to building abstract queries. Further, the abstract queries described below may target a medical industry database as a particular, but not limiting, application example. 
     One embodiment of the invention is implemented as a program product for use with a computer system such as, for example, the computer system  110  of the data processing environment  100  shown in  FIG. 1  and described below. The program(s) of the program product defines functions of the embodiments (including the methods described herein) and can be contained on a variety of signal-bearing media. Illustrative signal-bearing media include, but are not limited to: (i) information permanently stored on non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive); (ii) alterable information stored on writable storage media (e.g., floppy disks within a diskette drive or hard-disk drive); or (iii) information conveyed to a computer by a communications medium, such as through a computer or telephone network, including wireless communications. The latter embodiment specifically includes information downloaded from the Internet and other networks. Such signal-bearing media, when carrying computer-readable instructions that direct the functions of the present invention, represent embodiments of the present invention. 
     In general, the routines executed to implement the embodiments of the invention, may be part of an operating system or a specific application, component, program, module, object, or sequence of instructions. The software of the present invention typically is comprised of a multitude of instructions that will be translated by the native computer into a machine-readable format and hence executable instructions. Also, programs are comprised of variables and data structures that either reside locally to the program or are found in memory or on storage devices. In addition, various programs described hereinafter may be identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular nomenclature that follows is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature. 
     Referring now to  FIG. 1 , the data processing environment  100  is shown. In general, the data processing environment  100  includes a computer system  110  and a plurality of networked devices  146 . The computer system  110  may represent any type of computer, computer system or other programmable electronic device, including a client computer, a server computer, a portable computer, an embedded controller, a PC-based server, a minicomputer, a midrange computer, a mainframe computer, and other computers adapted to support the methods, apparatus, and article of manufacture of the invention. In one embodiment, the computer system  110  is an eServer iSeries 400 available from International Business Machines of Armonk, N.Y. 
     The computer system  110  could include a number of operators and peripheral systems as shown, for example, by a mass storage interface  137  operably connected to a direct access storage device (DASD)  138 , by a video interface  140  operably connected to a display  142 , and by a network interface  144  operably connected to the networked devices  146 . The display  142  may be any video output device for outputting viewable information. The networked devices  146  may be any combination of any type networked devices, such as networked servers, networked printers, and network accessed storage (NAS) devices. 
     Computer system  110  is shown comprising at least one processor  112 , which obtains instructions and data via a bus  114  from a main memory  116 . The processor  112  could be any processor adapted to support the methods of the invention. The main memory  116  is any memory sufficiently large to hold the necessary programs and data structures. Main memory  116  could be one or a combination of memory devices, including Random Access Memory, nonvolatile or backup memory, (e.g., programmable or Flash memories, read-only memories, etc.). In addition, main memory  116  may be considered to include memory physically located elsewhere in a computer system  110 , for example, any storage capacity used as virtual memory or stored on a mass storage device (e.g., DASD  138 ) or on another computer coupled to the computer system  110  via bus  114 . 
     The main memory  116  is shown configured with an operating system  118 . The operating system  118  is the software used for managing the operation of the computer system  110 . Examples of the operating system  118  include UNIX, Microsoft Windows®, and the like. As illustrated, the main memory  116  further includes at least one application  120  and an abstract query interface  130 . 
     The application  120  and the abstract query interface  130  are software products comprising a plurality of instructions that are resident at various times in various memory and storage devices in the computer system  110 . When read and executed by one or more processors  112  in the computer system  110 , the application  120  and the abstract query interface  130  cause the computer system  110  to perform the steps necessary to execute steps or elements embodying the various aspects of the invention. The application  120  (and more generally, any requesting entity, including the operating system  118 ) is configured to run (i.e., issue/execute) queries against the database  139 . 
     The queries issued by the application  120  may be created and/or specified by a user via a query building interface  122 , which may be included with the application  120 . The queries (referred to herein as “abstract queries”) are composed using logical fields defined by the abstract query interface  130 . The query building interface  122  may allow the user to generate abstract queries by specifying query conditions, based on the logical fields, to be added to the abstract queries. The logical fields used in the abstract queries are defined by a data repository abstraction (DRA) component  132  of the abstract query interface  130 . The abstract queries are executed by a runtime component  136  which transforms the abstract queries into a form consistent with the physical representation of the data contained in the database  139 . The concepts of data abstraction and abstract queries are described in detail in the commonly owned, co-pending application Ser. No. 10/083,075, entitled “Improved Application Portability And Extensibility Through Database Schema And Query Abstraction,” filed Feb. 26, 2002, herein incorporated by reference in its entirety. 
     The abstract queries created by the query building interface  122  and executed by the runtime component  136  may be monitored by a fallout manager  134  of the abstract query interface  130 . As will be described in greater detail below, the fallout manager  134  may be generally configured to modify the DRA component  132  by removing logical fields and/or marking logical fields as hidden, based on usage characteristics of the logical fields as detected in the monitored abstract queries. As previously described, by removing fields from the DRA component  132  and/or marking fields as hidden, the number of fields presented to a user, by the query building interface  122 , for use in building an abstract query by query building interface  122  may be reduced, which may simplify the query building process. 
     Data Model Fallout 
     The fallout manager  134  may limit the number of fields presented to the user by allowing fields that have not been used recently (or are used infrequently) to “fall-out” of the DRA component  132 . As used herein, the term fall-out generally refers to preventing a field from being presented to the user by either marking the field as hidden (referred to as “partial fall-out”) in the DRA component  132  or removing the field completely from the DRA component  132  (referred to as “complete fall-out”). In the case of partial fall-out, a field is hidden from the user (e.g., not presented to the user in the interface), but still remains in the DRA component  132 . In some cases, hidden fields may still be displayed, for example, upon user request. In the case of complete fall-out, the field is actually removed from the DRA component  132  and may not be displayed unless first restored to the DRA component  132 , for example, by an administrator. 
       FIG. 2A  illustrates a relational view of the DRA component  132 , fallout manager  134 , and query execution component  136 , according to one embodiment of the invention. As illustrated, the DRA component  132  includes a set of logical fields corresponding to fields in a physical data representation  214 . The physical data representation  214  may be a relational data representation (as shown), such as SQL, for example. Regardless of the actual physical data representation, a user may generate, via the query building interface  122 , an abstract query  202  including query conditions based on the logical fields of the DRA component  132 , in order to access data stored in the physical data representation  214 . As illustrated, for some embodiments, logical fields may be organized in categories (e.g., Contacts, Birth and Age Related fields, etc.). The concepts described herein may also be applied to limit the number of categories presented to a user. 
     The query execution component  136  is generally configured to execute the abstract query  202  by transforming the abstract query  202  into a concrete query compatible with the physical data representation  214 . The query execution component  136  may transform the abstract query  202  into the concrete query by mapping the logical fields of the abstract query  202  to the corresponding physical fields of the physical data representation  214 , based on mapping information in the DRA component  132 . The mapping abstract queries to concrete queries is described in detail in the previously referenced co-pending application Ser. No. 10/083,075. 
     For example, as illustrated in  FIG. 2B , the DRA component  132  may include, for each logical field, table and field names indicating a corresponding physical field in the physical data representation  214 . The DRA component  132  may also include, for each logical field, a Boolean HIDDEN attribute to indicate to the query building interface  122  whether the logical field should be hidden (not displayed) and a parameter to store a usage characteristic of the logical field. For example, as shown, a value indicative of the last use of the logical field (e.g., as a number of days) may be stored as the usage characteristic parameter. Alternatively, a time stamp indicative of the last use may be stored in the usage characteristic which may be used to calculate the amount of time has past since the last use from a current time stamp. For some embodiments, usage characteristics may include a frequency with which the logical field is used, for example, as defined by a number of times the logical field has been used in a query for a given period. Further, as will be described in greater detail below, for some embodiments, usage characteristics for individual users may be stored in one or more DRA components  132 , allowing for user-specific fallout. 
     Referring back to  FIG. 2A , the fallout manager  134  may decide whether a logical field should partially or completely fallout of the DRA component  132  based on one or more scheduling algorithms  135 . The scheduling algorithms  135  may include a set of parameters that determine how and when logical fields should fallout (partially or completely) of the DRA component  132 . As illustrated in  FIG. 2C , for some embodiments, the scheduling algorithms  135  may include threshold parameters for comparison against the usage characteristic parameters stored in the DRA component  132  to determine fallout. 
     As illustrated, a first scheduling algorithm may cause logical fields whose last use occurred more than 180 days ago to partially fallout. As a result, BIRTH DATE and AGE IN YEARS fields in the DRA component  132 , last used more than 180 days ago, may be marked as hidden (e.g., the HIDDEN attribute may be set to YES). A second scheduling algorithm may cause logical fields whose last use occurred more than 365 days ago to completely fallout. As a result, STREET and AGE IN DECADES fields last used more than 365 days ago may be removed from the DRA component  132 . As illustrated in  FIGS. 2A and 2D , the removed fields and the associated parameters may be stored in the fallout information  138 . 
     Fall Out Maintenance 
     The fallout manager  134  may be generally configured to perform two basic functions: to monitor the query building process to update usage characteristics for logical fields and to maintain (update) the DRA component  132  by allowing logical fields to fall out of the DRA component  132  based on the usage characteristics. For some embodiments, the fallout manager  134  may parse abstract queries  202  issued by the query building interface  122  to determine the logical fields used in constructing the abstract query  202 . For other embodiments, the query execution component  136  may send the fallout manager  134  information regarding the logical fields used to construct the abstract query  202 . Regardless, the fallout manager  134  may update the usage characteristics stored in the DRA component  132  for each of the logical fields used to construct the abstract query  202 . 
       FIG. 3  is a flow diagram of operations  300  that may be performed by the fallout manager  134  for maintaining the DRA component  132 . The operations  300  may be described with reference to  FIGS. 2A-2D . The operations  300  begin at step  302 , for example, in the course of performing periodic maintenance on the DRA component  132  or in response to a request to perform DRA maintenance (e.g., from an administrator). Further, the operations  300  may be performed automatically, for example, prior to invoking the query building interface  122 , to update the DRA component  132 . Regardless, at step  304 , the fallout manager  134  enters a loop of operations (including steps  306 - 326 ) performed for each field in the DRA component  132 . 
     At step  306 , last use data is retrieved for the selected field. At step  308 , the fallout manager  134  determines (based on the last use data) if the field has been used to build a query within a predetermined partial fallout time period (T PARTIAL ). As previously described, last use data may be stored as a usage characteristic parameter for each field in the DRA. As previously described, the last use data may be stored in any suitable format, such as the actual amount of time that has passed since the field was last used (e.g., in days, as shown) or as a time stamp recorded when the field was last used. Regardless of the format, if the field has been used to build a query within T PARTIAL , processing continues to step  304  to select the next field. 
     On the other hand, if the field has not been used to build a query within T PARTIAL , the field is marked as hidden at step  312 . For example, the HIDDEN attribute for the field may be set to YES. At step  314 , the fallout manager  134  determines if the selected field is the last field in a category (or parent field). If so, the category is marked as hidden, at step  316 . For example, while not illustrated in  FIG. 2B , the DRA component  132  may also include, for each category, a HIDDEN attribute similar to the HIDDEN attribute of the logical fields. As will be described in greater detail below, the query building interface  122  may determine whether or not to display a field (or category) based on the value of a corresponding HIDDEN attribute. 
     At step  318 , the fallout manager determines if the field has been used to build a query within a predetermined complete fallout time period (T COMPLETE ). If the field has been used to build a query within T COMPLETE , processing continues to step  304  to select the next field. 
     On the other hand, if the field has not been used to build a query within T COMPLETE , the field is removed from the DRA component  132 , at step  320 . At step  322 , the fallout manager determines if the selected field (removed from the DRA in step  320 ) was the last field in a category remaining in the DRA component  132 . If so, the category is removed from the DRA component  132 , at step  324 . At step  326 , the fallout information  138  is updated and processing continues to step  304  to select the next field for processing. Once all the fields have been processed, the operations  300  are exited at step  330 . 
     As illustrated in  FIG. 2D , the fallout information  138  may contain all the information regarding the removed fields, that was previously contained in the DRA component  132 . An advantage to this approach is that the removed fields may be restored to the DRA component  132  from the fallout information  138 , for example, upon request of a database administrator. Another advantage to this approach is that the last use data may continue to be updated even after a field is removed. Accordingly, if a scheduling algorithm is changed (or a different scheduling is used), resulting in a greater complete fallout time, removed fields that were last used prior to the greater complete fallout time may be automatically restored. 
     Of course, the particular operations  300  illustrated and the particular order of the operations  300  is for illustrative purposes only, and may be modified in various ways. For example, for some embodiments, usage characteristics of a field may be tested for complete fallout prior to testing for partial fallout. As another example, for some embodiments, fallout processing may not be performed on categories (i.e., steps  314 - 316  and steps  322 - 324 ). For example, for some embodiments, fields may not be organized in categories. 
     Query Building Interface 
     The impact of field fallout from a user&#39;s perspective is illustrated in  FIGS. 4A and 4B , which show an exemplary GUI screen  530  for adding search conditions to a query based on fields from the DRA component  132 , without and with hidden fields shown, respectively. The GUI screen  530  for adding search conditions may be accessed, for example, from a main query building GUI screen of the query building interface  122 . Of course, the GUI screen  530  of  FIGS. 4A and 4B  illustrate only one embodiment of the present invention, and many different variations of suitable GUI screens may allow a user to add search conditions to a query within the scope of the present invention. For illustrative purposes only, the  FIGS. 4A and 4B  will be described with reference to building queries to a database containing fields related to the medical industry. Of course, similar GUI screens may be created for building queries to databases containing fields related to any industry. 
     The GUI screen  530  may present to the user fields for use in constructing search conditions to be added to a query being built. As illustrated, the GUI screen  530  may present the fields within a set of categories. The set of categories may depend on the industry for which the database is established. For example, for a medical industry database application, the list of categories may include a BIRTH AND AGE RELATED category  532 , a LABORATORY RESULTS category  534 , a REPORTS category  536 , and a DIAGNOSTIC CODE category  538  (as illustrated, the DIAGNOSTIC CODE category  538  may allow a user to enter government mandated ICD-9 diagnostic codes). Each of the categories may have a list of related fields (or related subcategories with related fields). 
     For example, the BIRTH AND AGE RELATED category  532  may include fields for AGE, BIRTH DATE, and AGE IN DECADES. To construct a query condition based on one of the fields, the end user may select one of the fields (e.g., from a pull down menu). In response to selecting one of the fields, the user may be presented with another GUI screen (not shown) allowing the user to specify a query condition based on the selected field. For example, one such GUI screen may allow the user to enter an age related search condition by specifying a logical operator and a number of years (e.g., AGE&gt;40). Of course, age is typically not stored in a database, but rather calculated from a birth date and current date. However, the query building interface  122  may hide this detail from a user, greatly facilitating the entry of age related conditions. 
     As previously described, a user may be given the option of displaying hidden fields. For example, the GUI screen  530  may include a SHOW HIDDEN FIELDS check box  544 . With the check box  544  unchecked (i.e., SHOW HIDDEN FIELDS disabled), in  FIG. 4A , hidden fields are not presented to the user. For example, a hidden field AGE IN DECADES is not presented in the pulldown menu for the BIRTH AND AGE RELATED categories  532 , and a hidden CONTACTS category  539  (i.e., a category with only hidden fields) is not displayed. As illustrated in  FIG. 4B , however, with the check box  544  checked, the hidden fields (i.e., AGE IN DECADES and the fields of the hidden category CONTACTS) are presented to the user, for example, regardless of the value of the corresponding HIDDEN attributes. 
     It should be noted, however, that fields that were removed from the DRA component  132  (i.e., fields that fell out completely) are not displayed regardless of whether the check box  544  is checked or not. However, as previously described, removed fields may be restored (based on the fallout information  138 ) to the DRA component  132 . For some embodiments, the removed fields may be restored to the DRA component  132  as hidden or unhidden (e.g., by initializing the corresponding HIDDEN attribute accordingly). 
       FIGS. 5A and 5B  are flow diagrams of operations  500  and  550 , respectively, that may be performed as part of the query building process. The operations  500  may be performed, for example, by the query building interface  122 , to limit the number of fields presented to a user, for example, in an effort to simplify the query building process. The operations  550  may performed during normal query building and execution process, for example, by the fallout manager  134 , to continuously update usage characteristics of fields in the DRA component  132 . 
     The operations  500  begin at step  502 , for example, when building a GUI screen (such as the GUI screen  530  of  FIGS. 4A and 4B ) to present fields to the user for use in adding search conditions, or as an initialization routine to identify fields to be displayed at a later time. At step  504 , a loop of operations (steps  506 - 516 ) are performed for each field in the DRA component  132  is entered, to determine which of the fields should be presented to the user. At step  506 , a determination is made of whether a selected field is marked as hidden. For example, the determination may be made by testing the Boolean hidden parameter for the field in the DRA component  132 . If the field is marked as hidden, a determination is made, at step  508 , whether the user has requested that hidden fields be shown (e.g., via the check box  544  of the GUI  530 ). If either the field is not marked as hidden or the user has requested that hidden fields be shown, the field is displayed at step  510  (or added to a list of fields to be displayed) and processing continues to step  504  to select the next field. 
     If, on the other hand, the field is marked as hidden and the user has not requested hidden fields to be shown, the field is not displayed at step  512  (or the field is not added to the of fields to be displayed). Optionally, at step  514 , a determination is made of whether the field is the last field in a category (i.e., all other fields in the category are also hidden). If so, the category is not displayed, at step  516 , and processing continues to step  504  to select the next field. 
     As previously described with reference to  FIG. 3 , categories may also be marked as hidden during fallout processing by the fallout manager  134 . For example, each category may have a Boolean hidden parameter that may be tested to determine if the category is hidden. Therefore, rather than make the determination of step  514 , a determination may be made of whether the category is hidden or not. Of course, this determination may be made in an outer loop (not shown), such that the operations  504 - 510  are not performed for fields of hidden categories. 
     Once it has been determined which fields (or categories) are to be displayed, processing proceeds from step  504  to the operations  550  of  FIG. 5B  for updating usage characteristics of fields, by the fallout manager  134 , during the query building and/or execution process. The operations  550  begin at step  552  when a user builds a query. For some embodiments, the fallout manager  134  may receive the query from the query building interface  122  when a user chooses to execute a query. For other embodiments, rather than receive the query, the fallout manager  134  may receive a list of fields used in the query from the query execution component  136 . Regardless, at step  554 , the fallout manager  134  enters a loop of operations (including steps  556 - 559 ) performed for each field in the query. At step  556 , the usage characteristics (e.g., last use or frequency of use) for a selected field is updated. For example, the last use parameter for the selected field may be updated in the DRA component  132 . 
     For some embodiments, related fields may be correlated, such that the usage characteristics of the correlated fields are updated together. Fields may be correlated if, for example, the use of one of the fields increases the likelihood of the use of another one of the fields. Accordingly, when the usage characteristics of one field is updated, the usage characteristics of any correlated fields may also be updated. Therefore, at step  558 , a determination is made whether the selected field is correlated with other fields. If the selected field is not correlated with other fields, processing proceeds to step  554  to select the next field. If the selected field is correlated with other fields, the usage characteristics of the correlated fields are updated, at step  559 , and processing proceeds to step  554  to select the next field. Once the usage characteristics for each field in the query (and any correlated fields) have been updated, the operations are exited at step  560 . 
     User-Specific Fallout 
     As previously described, for some embodiments, usage characteristics may be maintained for individual users. Thus, for example, the operations  550  may be performed to update usage characteristics for a particular user. In other words, the fallout manager  134  may maintain user-specific usage characteristics for fields in the DRA component  132 , and logical fields may be marked as hidden from specific users (i.e., rather than “globally” hidden from all users). For some embodiments, a separate DRA component  132  may be provided for each user and the fallout manager  134  may maintain and access a separate DRA component  132  to perform fallout for each user. For other embodiments, a global DRA component  132  may include logical fields with separate usage characteristics for each user in a system. 
     Regardless, the operations  500  may be performed to determine which fields are displayed for (or hidden from) a particular user based on the usage characteristics corresponding to the particular user. Thus, different users (running the query building interface  122 ) may be presented with correspondingly different logical fields, based on their individual usage characteristics. In other words, by performing user-specific fallout, one or more logical fields presented to one user may not be presented to another user. User-specific fallout may have the highly desirable result that (eventually) logical fields that are not interesting to a particular user may be hidden from that particular user, without being hidden from other, possibly interested users. 
     As an example, two medical researchers, Researcher A and Researcher B may perform research relating to different families of diseases, for example, heart disease and liver disease, respectively. Accordingly, Researcher A may build queries with conditions based on logical fields related to heart disease, but not liver disease, while Researcher B may build queries with conditions based on logical fields related to liver disease, but not heart disease. Due to user-specific fallout, logical fields related to liver disease may (eventually) not be presented to Researcher A, despite the fact that Researcher B may regularly build queries related to liver disease. Similarly, logical fields related to heart disease may (eventually) not be presented to Researcher B despite the fact that Researcher A may regularly build queries related to heart disease. Of course, logical fields that are not used by either researcher may eventually fallout with respect to both, and may, therefore, not be presented to either. 
     Thus, by performing user-specific fallout, the query building process for Researcher A and Researcher B may be simplified by limiting, independently, the logical fields presented to each. In a similar manner, user-specific scheduling algorithms may also be utilized. For example, the fallout manager  134  may perform DRA maintenance (e.g., operations  300  of  FIG. 3 ) based on scheduling algorithms specific to particular users. For some embodiments, users may be able to control the rate with which logical fields fallout by adjusting scheduling algorithms. For example, one user may reduce a fallout period of a scheduling algorithm to allow logical fields to fallout rapidly (e.g., LAST USE=50 days), while another user may increase a fallout period to allow logical fields to fallout gradually (e.g., LAST USE=100 days). 
     Conclusion 
     By limiting the number of fields presented to a user based on usage characteristics of the fields, the query building process may be greatly simplified. The number of fields presented to the user may be limited by marking fields as hidden and/or removing fields from a data repository abstraction. It should be noted that any reference herein to particular values, definitions, programming languages and examples is merely for purposes of illustration. Accordingly, the invention is not limited by any particular illustrations and examples. For example, while aspects of the present invention have been described with reference to an abstract data model (utilizing a data repository abstraction component containing logical fields), the aspects may also be applied with advantage to conventional data models having fields corresponding to a particular physical representation. In other words, any type of query building interface may be simplified by limiting the number of fields presented to a user, regardless of the underlying data model. 
     While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.