Patent Application
20080069132
A more complete understanding of the present invention and the advantages thereof may be acquired by referring to the following description, taken in conjunction with the accompanying drawings in which like reference numbers indicate like features and wherein:
Skilled artisans appreciate that elements in the figures are illustrated for simplicity and clarity and are not necessarily drawn to scale.
Preferred embodiments of the present invention and the various features and advantageous details thereof are explained more fully with reference to the examples illustrated in the accompanying drawings where like numerals are used to refer to like and corresponding parts or elements. Descriptions of known computer languages, data structures, programming techniques, operating systems, network protocols, and the like are omitted so as not to unnecessarily obscure the invention in detail. Skilled artisans should understand, however, that the detailed description and the specific examples, while disclosing preferred embodiments of the invention, are given by way of illustration only and not by way of limitation. Various substitutions, modifications, additions or rearrangements within the scope of the underlying inventive concept(s) will become apparent to those skilled in the art after reading this disclosure.
Each of client computers 12 and 16 is an example of a data processing system. ROM 122 and 162, RAM 124 and 164, HD 126 and 166, and database 18 include media that can be read by CPU 120 or 160. Therefore, each of these types of memories includes a data processing system readable medium. Within this disclosure, the term “data processing system readable medium” is used interchangeably with the term “computer-readable storage medium.” These memories may be internal or external to computers 12 and 16.
Embodiments described herein may be implemented in suitable software code that may reside within ROM 122 or 162, RAM 124 or 164, or HD 126 or 166. In addition to those types of memories, some instructions implementing embodiments disclosed herein may be contained on a data storage device with a different data processing system readable storage medium, such as a floppy diskette.
In an illustrative embodiment, the computer-executable instructions may be lines of compiled C++, Java, or other language code. Other computer architectures may be used. For example, some functions of client computer 12 may be incorporated into server computer 16, and vice versa. Further, other client computers (not shown) or other server computers (not shown) similar to client computer 12 and server computer 16, respectively, may also be connected to network 14.
Communications between client computer 12 and server computer 16 can be accomplished using electronic, optical, radio frequency, or other signals. When a user is at client computer 12, client computer 12 may convert the signals to a human understandable form when sending a communication to the user and may convert input from a human to appropriate electronic, optical, radio frequency, or other signals to be used by client computer 12 or server computer 16.
Embodiments of Hub 300 provide accurate, scalable, and deployable solutions for customer-centric master data management as Hub 300 enables business entities to create complete, real-time views of data from various data sources 350 and applications 360 to more effectively manage, control, analyze and integrate customer, patient or constituent information and relationships while protecting data privacy. In particular, Hub 300 has the ability to handle hundreds of millions of records in sub-second response times with unique proprietary matching and linking technology that identifies and resolves information routinely, even when there is duplicate, fragmented or incomplete data. Within this context, Manager 330, embodied in a software application, enables administrators and implementers (i.e., system administrators, application administrators, database administrators, software developers, software engineers, system architect, and those responsible for implementing Initiate™ software applications) to easily manage Hub 300 software environment via a user interface. In this example, Manager 330 is installed on a server and accessible via an Intranet. In some embodiments, Manager 330 can be installed and run directly on a workstation.
Data segments or simply segments coincide with data schema of Hub 300 to define behavior of Engine 320 and member information. In some embodiments, a set of pre-defined (“fixed”) segments are created and packaged with Hub 300 prior to deployment. In some embodiments, implementers can add member-attribute implementation defined (“custom”) segments through Manager 330 upon/after deployment. Within this disclosure, each segment is a data structure which encapsulates a single row from the coinciding database table. In embodiments disclosed herein, segments are used as data storage structures for data that may be read from a database (e.g., database 350), or sent in from a client application (e.g., application 360). When Engine 320 operates on data, it passes around a set of these segment objects (i.e., they are Shared Objects).
In some embodiments, there are three types of segments: dictionary segments, member segments, and audit segments. Audit segments enable reporting and tracking. Member segments define individual entities (i.e., members and members associated with an entity), member attributes, and task workflow. In some embodiments, only member attribute segments can be defined at the time of implementation. Dictionary segments contain type definition and lookup values. These values define customer specific data, engine behavior, and other segment types. Dictionary segments can be divided into five sections.
a. Type Definition—provides lookup values to define data types used by Hub 300;
b. Segment Definitions—enable the definition of internal (internal to Hub 300) and customer-specific (i.e., implementation defined) segments that are maintained by Hub 300;
c. Source Definitions—enable the definition of source systems recognized by Hub 300 and the interactions therebetween;
d. Use Segments—provide Hub 300 specific configuration that defines behavior of Engine 320, which includes comparison, derived data, and standardization strategies, as well as linkage rules and other behavior rules; and
e. User Access Definition Segments—define valid Hub 300 users and their associated access control rules, including user IDs and permissions.
In
In the past, a segment was defined by what was referred to as a package. Packages were hard-coded C language structures that defined the data fields, what data type those fields were, and how the system should treat those fields. Packages proved to be a very powerful way to describe data in a manner that the rest of the Initiate Identity Hub™ software could use to operate on the data. However, because these packages were hard-coded C language structures, if a new segment definition is needed, a code change had to be made in the Initiate Identity Hub™ engine, a database table that matched the change had to be made, and any API changes needed for others to be able to access the new segment also had to be made.
Embodiments of an Implementation Defined Segments subsystem disclosed herein represent an innovative way to support new segments without having to ship and support new code at each customer site that has unique data requirements. Instead of the package mechanism described above, a set of database tables, also referred to as metadata tables, would be read at system start-up to define the shape of the package data structures. If an implementer or administrator needs to change a segment, or add a new one, the implementer/administrator could just add the proper data to the database, and on the next restart of Engine 320, Hub 300 would behave exactly as if the segment information had been hard-coded in the packages.
Part of the IDS metadata defines how the data should be stored and persisted in a database. The mpi_seghead table gives the table name, and the segXfld table identifies the field name, the field data type, and field length (if needed). The tables defined above include flags which allow a user to define a segment that contains virtual fields, or virtual attributes. At a field level, the mpi_segxfld.isvirtual flag defines whether or not a data field should be stored. If it is marked as virtual, the Identity Hub engine will create space to store values, and will transport the values to and from any calling client application, but it will not save those values in the database. At an attribute level, the mpi_segattr.isvirtual flag says that the Identity Hub should not store the entire attribute. The IDS meta-data stores a generic data type that is not specific to any given relational database that the Identity Hub has been ported to. A mechanism in the Identity Hub engine translates from this generic data type to a RDBMS specific type through the use of a lookup file that is contained outside the database. A sample section of this file for the Oracle database is given below:
The IDS sub-system looks up the generic data type on the left from the mpi_segxfld table, and it is translated to the RDBMS specific type on the right. The reason this file is not stored in the database is that Engine 320 needs the RDBMS specific types prior to creating the segment metadata tables when the system is first installed. Hub 300 has utility programs that can create a database from the generic data types for any RDBMS that Hub 300 has been ported to. When defining a new segment, Manager 330 will export the generic DDL statement used to make the database specific table and indexes. An example is show below for a fictional customer segment that contains a customer name, phone number, a customer id number, and date that shows when the customer first started doing business:
The generated DDL statement above contains not only the fields defined by the user, but also the fields used to join this data table to the rest of the data model of Hub 300 and to provide for attribute-level auditing. The additional scaffolding is generated automatically and may change as future versions of Hub 300 may need to change the data model. As discussed above, these Data Definition Language (DDL) statements are sent to the file system instead of the database, so that they can be used to create the empty tables before the database is fully populated.
In some embodiments, every segment used by Hub 300 could be built by the IDS technology disclosed herein. In some embodiments, the scope of the IDS capability of Manager 330 is limited to a sub-section of the data model called Member Attributes. Member Attributes are data segments that contain the demographic data used for comparison by Hub 300. They are the most likely point in the data model for a customer to want to customize or add additional capability. However, as one skilled in the art can appreciate, the scope of the IDS capability may be extended to include all but a small kernel of segments that will need to remain pre-defined so that the system may bootstrap itself at startup.
In some embodiments, Manager 330 is programmed to enable an implementer or an administrator to define Implementation Defined Segments and the attributes that use these segments. As an example,
The IDS subsystem described above provides a way to programmatically access the IDS metadata and determine what data segments are available, and what data fields they are made up of. Hub 300 includes a set of programming APIs (Application Programming Interfaces) as libraries that can be called from the C++ or Java programming language. These same APIs are used on pre-built applications so they can adapt to new data segments in the same manner that a custom built client application would. In some embodiments, the APIs have metadata classes that allow a programmer to find out at run-time how many segments are defined in the system, and for each of those segments, what fields and data types are they made up of. Additional classes allow the creation of an Implementation Defined Segment, and access to the data in each of the fields in either its native data type or as a generic string representation. When writing data to Hub 300, the programmer most often knows the shape of the attribute (what fields exist and their data type). In some cases, the incoming data may be in string format. and the API can convert it to the proper underlying data type for the caller. The dictionary store contains the metadata required to figure out what attribute is linked to a particular segment and the API will ensure that the proper amount of storage to hold that segment is allocated. By interrogating the metadata tables, knowledge of the shape of a particular segment can be obtained, as well as the number of segments defined (e.g., for an embodiment of Engine 320).
When a user initiates an action (e.g., a retrieve), a specific interaction (e.g., MEMGET) sends the retrieve criteria to Hub 300. The returned data includes segments (e.g., MEMHEAD, MEMATTR, MEMNAME, MEMADDR, MEMPHONE, MEMTYPE, and/or MEMIDENT) containing the requested member data from the applicable tables (e.g., mpi_memhead, mpi_memattr, mpi_memname, mpi_memaddr, mpi_memphone, mpi_memtype, and/or mpi_memident). Depending upon the interaction, the specific criteria, and the information stored in Database 340 about a member, multiple segments may be returned. This process is illustrated in
Although the present invention has been described in detail herein with reference to the illustrative embodiments, it should be understood that the description is by way of example only and is not to be construed in a limiting sense. It is to be further understood, therefore, that numerous changes in the details of the embodiments of this invention and additional embodiments of this invention will be apparent to, and may be made by, persons of ordinary skill in the art having reference to this description. It is contemplated that all such changes and additional embodiments are within the scope of the invention as detailed in the following claims.
This application claims priority from U.S. Provisional Application No. 60/845,073, filed Sep. 15, 2006, entitled “METHOD AND SYSTEM FOR IMPLEMENTATION DEFINED SEGMENTS USING META-DATA,” which is fully incorporated by reference herein.
| Number | Date | Country | |
|---|---|---|---|
| 60845073 | Sep 2006 | US |
