Abstract:
Methods and apparatus, including computer program products, for distributing data. In one aspect, a computer program product includes instructions. The instructions can be operable to cause a processor to perform operations. The operations can include receiving historical distribution information for a data assembly and determining if distribution of at least a portion of a current version of the data assembly to a target component is warranted based on the historical distribution information. The historical distribution information can identify one or more components that have previously received some version of the data assembly. The product can be tangibly stored on a computer-readable medium.

Description:
BACKGROUND 
   This disclosure relates to data processing, and more particularly, to data management systems and techniques. 
   Information technology (“IT”) environments can include different systems performing processes, such as business processes, on common master data. The different systems can belong to a single entity or to several different entities (such as vendors and contractors for a single, large company). The master data in the IT environment can be stored in a number of different locations, systems, and/or formats. For example, branch offices of a company can work with largely independent systems, adopted companies can introduce new software solutions to a group of affiliated companies, and systems from different vendors can be linked. Disparate master data models can make it difficult to integrate business processes across such diverse IT environments. 
   Disparate master data can be stored in different systems in an IT environment. Such disparate master data can lead to data redundancies and the storage of irrelevant or incorrect information. For example, if two branches of a single company each collaborate with the same entity, a separate master data object for the entity may be maintained by each of the two branches. This redundancy can result in high content maintenance costs. Further, business analyses performed using redundant or disparate information can lead to poor business decisions. For example, a company-wide analysis of collaborators can fail to identify the correspondence between the two redundant master data objects and business value can be lost. 
   SUMMARY 
   The present invention provides methods and apparatus, including computer program products, for distributing data in a data management system. 
   In one aspect, a method includes adding redundant data to a data assembly based on a characteristic of a component targeted for receipt of the data assembly. The addition is performed in anticipation of distribution of the data assembly. 
   This and other aspects can include one or more of the following features. The redundant data can be added to the data assembly comprises duplicating a second data assembly referenced by the data assembly. The data assembly, including the redundant data, can be distributed. The redundant data can be added based on a technical characteristic of the component. For example, the redundant data can be added based on a technical ability of the component to handle complex data objects. The redundant data can be added to a data object. 
   In another aspect, a computer program product includes instructions. The instructions can be operable to cause a processor to perform operations. The operations can include receiving valuation information relating to an appraisal of the appropriateness of a portion of a data assembly for distribution and modifying the data assembly for distribution based on the received valuation information. The product can be tangibly stored on a computer-readable medium. 
   This and other aspects can include one or more of the following features. The operations can also include receiving an indication of invalidity of the portion of the data assembly and eliminating the invalid portion of the data assembly for distribution. An indication of a change to the portion of the data assembly can be received. The change can relate to an update to a version of a device described by the data assembly. 
   The operations can also include eliminating, for distribution, the portion of the data assembly that describes a previous version of the device described by the data assembly. The data assembly can be automatically identified for distribution upon receipt of the indication of the change to the portion of the data assembly. The complexity of the data assembly can be reduced, for example, by eliminating an object from the data assembly. Plural references to a single data object can also be eliminated. The valuation information can be received as metadata included in the data assembly. The valuation information can relate to a context of a target component, such as an application performed at the target component. 
   In another aspect, a computer program product includes instructions. The instructions can be operable to cause a processor to perform operations. The operations can include receiving historical distribution information for a data assembly and determining if distribution of at least a portion of a current version of the data assembly to a target component is warranted based on the historical distribution information. The historical distribution information can identify one or more components that have previously received some version of the data assembly. The product can be tangibly stored on a computer-readable medium. 
   This and other aspects can include one or more of the following features. The operations can include receiving historical distribution information identifying a distributed version of the data assembly and determining if a current version of the data assembly includes changed data for which distribution to the target component is warranted. The distributed version can be previously distributed to the target component. 
   The operations can also include determining if the current version of the data assembly includes data associated with an updated lifecycle characteristic, and determining if the update to the lifecycle characteristic makes distribution of the associated data to the target component warranted. 
   The operations can also include determining if the current version of the data assembly includes data applicable to a role of the target component. The current version of the data assembly can be modified for distribution to the target component. The operations can also include identifying a second data assembly related to the data assembly and determining if distribution of the second data assembly is warranted based on the relationship with the data assembly. 
   In another aspect, a computer program product includes instructions. The instructions can be operable to cause a processor to perform operations. The operations can include receiving a data assembly identified for distribution, extracting a characteristic of the content of the data assembly, and determining if distribution of at least a portion of the data assembly to a target component is warranted based on the characteristic of the content. 
   This and other aspects can include one or more of the following features. The characteristic of the content can be compared with a characteristic of the target component. The content of the data assembly can be searched for a keyword relevant to the target component or language in the content of the data assembly can be parsed for language relevant to the target component. The operations can include comparing the characteristic of the content with a characteristic of the target component or with a role of the target component. The current version of the data assembly can be modified for distribution to the target component. 
   These and other aspects can be implemented to realize one or more of the following advantages. A tool for distributing data can assist a central data storage component in the distribution of data to client systems. The tool can use one or more rules to assist in this distribution. The rules can be directed to identifying target components for data distribution or modifying data for data distribution. For example, the format of the sent data can be transformed to a format that the client system is configured to receive. 
   The details of one or more implementations of the invention are set forth in the accompanying drawings and the description below. Other features and advantages of the invention will become apparent from the description, the drawings, and the claims. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a block diagram illustrating an implementation of a data management system. 
       FIG. 2  is a block diagram illustrating an implementation of a source component in the data management system. 
       FIG. 3  is a flow chart illustrating a process for distributing data. 
       FIG. 4  is a schematic representation of a replication table for use in distributing data. 
       FIG. 5  is a flow chart illustrating an implementation of a process for determining targets. 
       FIG. 6  is a schematic representation of one implementation of routing data used in determining targets. 
       FIG. 7  is a flow chart illustrating another implementation of a process for determining targets. 
       FIG. 8  is a schematic representation of one implementation of data used in determining targets. 
       FIG. 9  is a flow chart illustrating another implementation of a process for determining targets. 
       FIG. 10  is a schematic representation of one implementation of data used in determining targets. 
       FIG. 11  is a flow chart illustrating an implementation of a process for modifying data. 
       FIG. 12  is a schematic representation of one implementation of data used in modifying data. 
       FIG. 13  is a flow chart illustrating another implementation of a process for modifying data. 
       FIG. 14  is a schematic representation of one implementation of data used in modifying data. 
       FIG. 15  is a schematic representation of a bill of materials data object. 
       FIG. 16  is a schematic representation of a recipe table data object. 
       FIG. 17  is a schematic representation of a vendor data object. 
       FIG. 18  is a flow chart illustrating another implementation of a process for modifying data. 
       FIG. 19  is a schematic representation of the vendor data object of  FIG. 18  after explosion. 
       FIG. 20  is a schematic representation of another implementation of a process for modifying data. 
   

   Like reference numbers and designations in the various drawings indicate like elements. 
   DETAILED DESCRIPTION 
     FIG. 1  shows a data management system  100  in which data is distributed. Data management system  100  includes a source component  105  and one or more target components  110 . Source component  105  and target components  110  exchange data by way of a data link  115 . For example, data management system  100  can be a product creation system, a project management system, a human resources management system, a customer management system, or any other system in which data is exchanged by the components. 
   Source component  105  can be a central database system or other data processing system that includes information (in the form of machine-readable data) that is potentially relevant to operations performed at target components  110 . Target components  110  can be application servers, clients, or other data processing systems that perform operations in accordance with the logic of a set of machine-readable instructions. Target components  110  can be dedicated to the performance of particular aspects of a shared objective. For example, the target components  120  can be a procurement component, a sales component, a sourcing component, a collaborative engineering component, a manufacturing component, or an enterprise resource planning (“ERP”) component involved in a shared product creation objective. Data link  115  can be the Internet, a LAN, a WAN, a collection of wireless transmitters and receivers, or other system for exchanging data. 
     FIG. 2  shows an example implementation of source component  105 . Source component  105  includes a data processor  205  and a data store  210 . Data processor  205  can be a data processing device and/or software that performs processing activities, for example a modification tool  215  and a routing tool  220 , in accordance with the logic of a set of machine-readable instructions. Data store  210  is a repository of machine-readable information, including data and instructions for processing activities, for example, a collection of one or more data objects  225 , a set of routing rules  230 , a set of routing data  235 , a set of modification rules  240 , and a set of modification data  240 . 
   Modification tool  215  implements one or more approaches to modifying data, for example, data objects from data object collection  225 , for distribution. Modification tool  215  can implement the approaches using modification data  240 . Routing tool  220  implements one or more approaches to designating one or more target components  110  ( FIG. 1 ) for receipt of the modified data. Routing tool  220  can implement the approaches using routing data  235 . 
   Data object collection  225  can include master data. Master data, also known as standing data, represents information that does not change with the workday transactions of a data processing system. For example, in a enterprise resource planning (ERP) system, master data can include the product information, vendor information, and material information that does not change with workday transactions such as product sales. 
   Data object collection  225  can include complex data objects. A complex data object is a data object that includes a structured set of other objects or structures. For example, structures and internal tables are complex data objects. A structure is an object that includes two or more elementary data objects in a particular order. An internal table includes two or more data objects with the same configuration. Complex data objects can be used to extend the functionality available to a set of machine-readable instructions. For example, a vendor object can include a first current address of the vendor and a second, future address that becomes effective on the date of the vendor&#39;s move. 
     FIG. 3  shows a flowchart of a process  300  for distributing data. Process  300  can be performed by a data processing system such as source component  105  ( FIGS. 1 and 2 ). 
   The system performing process  300  identifies an object for distribution (step  305 ). 
   The system can identify the object in response to one or more triggers. For example, an object can be identified for distribution in reaction to a change to the object or based on a predefined schedule for distribution of the object. Changes in an object that can trigger distribution include the creation of the object, the release of the object, or a change that meets certain criteria. For example, a price change can trigger distribution of a product object that includes the changed price. 
   The object can be identified through the use of a replication table, such as replication table  400  shown in  FIG. 4 . Replication table  400  includes information identifying one or more objects  405 , information identifying one or more targets  410 , information identifying a date on which an identified object was last distributed to an identified target  415 , and information identifying the state of identified object that was last distributed to an identified target  420 . 
   A system can use replication table  400  to identify an object for distribution, for example, by comparing the date on which an identified object was last distributed with a schedule for distribution of the object, or by comparing the changes made in the most recent version(s) of an object with the state of the object last distributed to determine if distribution of the most recent version is warranted. 
   As shown in  FIG. 3 , the system also determines one or more targets for the identified object based on one or more routing rules (step  310 ). Routing rules are governing procedures for identifying target components that are to receive a distribution of data, such as the object identified in step  305 . Example routing rules are described in further detail below. 
   The system can also modify an object based on one or more modification rules (step  315 ). A modification rule is a governing procedure for adapting an object to the particularities associated with a distribution. For example, an object can be modified for distribution to a particular target component. A modification rule can also stipulate that no adaptation of an object is warranted by a distribution. Example modification rules are described in further detail below. 
   The source system can distribute the modified object to one or more targets determined by the routing rules (step  320 ). This distribution can be performed over a data link such as data link  115 . 
     FIG. 5  shows an implementation of a process  500  for determining one or more targets for an object based on one or more routing rules. Process  500  can be performed as part of step  310  in process  300  ( FIG. 3 ). 
   The system can receive a historical distribution record for the object (step  505 ). A historical distribution record is a collection of information that identifies one or more targets that have previously received the object. A historical distribution record can be included in a collection of data that is used to implement approaches for determining one or more targets, such as routing data  235  ( FIG. 2 ). Replication table  400  ( FIG. 4 ) can act as a historical distribution record since replication table  400  includes dates  415  identifying which targets  410  received objects  405 .  FIG. 6  shows another implementation of a historical distribution record in the form of tables  605 . Tables  605  each identifies an object  610  and one or more target components  615  that have previously received object  610 . 
   As shown in  FIG. 5 , the system can determine targets for an object based on the historical distribution record of the object (step  510 ). For example, the system can determine that all prior recipients of the object are again targets for distribution. 
     FIG. 7  shows another implementation of a process  700  for determining one or more targets for an object based on one or more routing rules. Process  700  can be performed as part of step  310  in process  300  ( FIG. 3 ). 
   The system can identify one or more objects that are related to an object to be distributed to a target (step  705 ). The related objects can relate to the object to be distributed in a variety of ways. For example, the related objects can be components or subcomponents of the object to be distributed, the related objects can include information describing elements that are similar to or associated with an element described in the object to be distributed, or the related objects can describe alternative versions of an element described in the object to be distributed. 
   The relationships between objects can be described in the objects themselves. For example, a bill of materials for a product can identify objects that correspond to constituent parts of the product. As another example, a recipe object describing a process flow for a production process can identify equipment objects that describe equipment for the performance of the process flow. Alternatively, the relationships between objects can be described in a collection of data that is used to implement approaches for determining one or more targets, such as routing data  235  ( FIG. 2 ).  FIG. 8  shows example tables  805  that store information identifying an object to be distributed  810  and one or more other related objects  815 . 
   As shown in  FIG. 7 , the system can determine a target for the related objects based on their relationship to an object to be distributed (step  705 ). For example, when a relationship between two objects is identified in table  805 , the system can determine that joint distribution of any objects identified in information  810 ,  815  is warranted. 
     FIG. 9  shows another implementation of a process  900  for determining one or more targets for an object based on one or more routing rules. Process  900  can be performed as part of step  310  in process  300  ( FIG. 3 ). 
   The system can extract characteristics of the object that are useful in determining targets (step  905 ). The system can extract the characteristics using one or more techniques such as keyword searches, language parsing, and rule-based systems for identifying one or more characteristics of the object. For example, the system can use language parsing to identify that an object includes language relevant to a sales brochure or other marketing material. As another example, a keyword search may determine that an object such as a process flow recipe or a material includes information relevant to operations at a particular processing plant. 
   The system can use the extracted characteristics to determine targets for distribution of the object (step  910 ). For example, the system can compare the extracted object characteristics with characteristics of one or more potential targets. The characteristics can be predetermined and included in a collection of data that is used to implement approaches for determining one or more targets, such as routing data  235  ( FIG. 2 ).  FIG. 10  shows example tables  1005  that store information identifying a target  1010  and one or more characteristics of the target  1015 . Target characteristics  1015  are suitable for comparison with the characteristics extracted from an object for determining targets for distribution of the object. 
   One particular class of object characteristics that is useful in determining targets is the class of object lifecycle characteristics. The lifecycle of an object can be described in terms of stages through which the information in the object passes. For example, a product specification may pass through a planning stage, a development stage, a testing stage, a released-for-production stage, a released-for-marketing stage, and an archived stage as the product is created, produced, and retired. A lifecycle characteristic can identify the lifecycle of information in the object. Lifecycle characteristics can be extracted from the object in the same manner that other characteristics are extracted. For example, the lifecycle of an object can be identified in a dedicated lifecycle field in the object. 
   A system can use an extracted lifecycle characteristic to determine targets for distribution of the object. For example, if a product specification object is still in the planning stage, targets that participate in the planning and conceptualization of the product can be identified as suitable targets for distribution. As another example, if a product specification object has been released for production, targets that participate in the production of the object can be identified as suitable targets for distribution. 
   Lifecycle characteristics can also be used when modifying an object based on one or more modification rules.  FIG. 11  shows such a process  1100 . Process  1100  can be performed as part of step  315  in process  300  ( FIG. 3 ). 
   The system can extract one or more lifecycle characteristic of the object that are useful in modifying the object (step  1105 ). The extracted lifecycle characteristic can relate to the stage of the entire object or to the stage of a portion of the object, such as one or more fields in the object. 
   The system can use the extracted lifecycle characteristic to modify the object based on one or more modification rules (step  1110 ). The modification can include changing or withholding portions of the object from distribution based on characteristics of the target system and a lifecycle characteristic of the withheld portion. For example, a portion of an product specification object that relates a preliminary design can be withheld from distribution to a target at a production site. However, when the same preliminary design is released for production, that portion of the product specification object can be distributed to the target. 
   The target characteristics can be predetermined and included in a collection of data that is used to implement approaches for modifying objects, such as modification data  235  ( FIG. 2 ).  FIG. 12  shows example tables  1205  that store information identifying a target  1210  and one or more characteristics of the target  1215  that are relevant to determining if modification of an object based on the lifecycle of the object is warranted. For example, target characteristics  1215  can be compared with one or more lifecycle characteristics extracted from the object to determine if all or a portion of the object is to be distributed to the target. 
     FIG. 13  shows another implementation of a process  1300  for modifying an object based on one or more modification rules. Process  1300  can be performed as part of step  315  in process  300  ( FIG. 3 ). 
   The system can determine the role applicability of data in an object (step  1305 ). The role applicability of an object is the pertinence of the object to certain activities. Roles can be defined in accordance with the departmental structure of an organization. For example, research and development, production, distribution, marketing, and sales roles can be defined. Role applicability can be determined by extracting one or more role characteristics of the object. Role characteristics can be extracted from the object in the same manner that other characteristics are extracted. Role characteristics, and hence role applicability, can relate to the entire object or to a portion of the object, such as one or more fields and/or field groups in the object. 
   The system can use the role applicability of data to modify the object based on one or more modification rules (step  1310 ). For example, the system can compare the role applicability with role characteristics of one or more potential targets. The target role characteristics can be predetermined and included in a collection of data that is used to implement approaches for modifying objects, such as modification data  235  ( FIG. 2 ). 
     FIG. 14  shows example tables  1405  that store information identifying a target  1410  and one or more characteristics of the target  1415 . Target characteristics  1415  are suitable for comparison with the role applicability of data in an object for determining if modification of the object is warranted. 
   As discussed above, the modification of a data object for distribution can include changing or withholding portions of the object from distribution based on characteristics of the target system. The portions of the object that are to be withheld can be determined using an approach called valuation. Valuation is an appraisal of the appropriateness of a portion of an object, or the object itself, for distribution. Valuation can be used to determine a perspective on an object for distribution based on the context. The perspective can be simpler that the object itself, making the object understandable to and compatible with a target component. The context can include, for example, a date, an application performed at the target component (for example, manufacturing or sales), or a specific configuration of the target component. The resulting perspective can be determined using metadata included in the object model. 
   For example, Valuation can be based on metadata that identifies the validity of a portion of an object.  FIG. 15  shows a bill of materials object  1500  that identifies four elements  1505 ,  1510 ,  1515 ,  1520  and metadata  1525 ,  1530 ,  1535 ,  1540  relating to the respective of elements  1505 ,  1510 ,  1515 ,  1520 . In particular, metadata  1525  indicates that element  1505  is valid, metadata  1535  indicates that element  1515  is valid, metadata  1540  indicates that element  1520  is valid, and metadata  1530  indicates that element  1510  is invalid. Element  15   10  may be invalid, e.g., because data in element  15   10  has expired (i.e., passed beyond a validity lifespan) or simply because element  15   10  is not available at the present time and hence not part of the corresponding (real world) bill of materials. A system that is modifying bill of materials object  1500  can withhold element  1510  from distribution based on the invalidity indicated by metadata  1530 . 
   Valuation can also be based on metadata that identifies the version of a portion of an object.  FIG. 16  shows a recipe table  1600  that includes three different versions of a recipe  1605 ,  1610 ,  1615 . A recipe is a collection of data for use in the manufacture and production of products. The information included in the recipe can describes, for example, the manufacturing or production process, raw materials, and processing equipment. 
   Recipes can include a hierarchical description of a process flow. Recipes generally include several different classes of process elements that are arranged in the recipe hierarchy and describe the process flow at various levels of detail. Recipes can also include definitions of resource, input, and output requirements for the process flow. 
   In  FIG. 16 , recipes  1605 ,  1610 ,  1615  each include an identification number  1620 , a product class description  1625 , a product name description  1630 , a formula  1635 , and an element hierarchy  1640 . A formula is a list of inputs and outputs of a recipe. Identification numbers  1620  can each include a suffix  1645 ,  1650 ,  1655  that identifies the version of the respective of recipes  1605 ,  1610 ,  1615 . In particular, suffix  1655  identifies that recipe  1615  is the most current version, whereas suffices  1645 ,  1650  identify that recipes  1605 ,  1610  are older, but still valid, versions. A system that is modifying recipe table  1600  can withhold recipes  1605 ,  1610  from distribution based on the version information provided in suffices  1645 ,  1650 . The system can also subsequently deliver recipes  1610 ,  1615  as separate entities if the information in recipes  1610 ,  1615  is desired at a target component. 
   Valuation can also be based on metadata that identifies the configuration of a device described by an object. The configuration of a device is the structural arrangement of parts or elements of the device. A device can be described in terms of a configurable product model that describes two or more different configurations of the device. For example, if a coffee machine is configurable to have five different arrangements as described in a configuration model, a system can separate the five variants into five discrete coffee machine configurations for distribution. Any or all of the separate configurations can subsequently be distributed. 
   The modification of a data object can also include exploding portions of the object for distribution.  FIG. 17  shows a vendor record object  1700  that includes a collection of attributes  1705  and values  1710  that together describe a vendor. Attributes  1705  are traits of vendors while values  1710  are denominations of the traits of the particular, described vendor. 
   Among attributes  1705  are the street  1715 , the city  1720 , the state  1725 , the zip postal code  1730 , and the country  1735  of shipping address of the vendor. Attributes  1715 ,  1720 ,  1725 ,  1730 ,  1735  are denominated by corresponding values  1740 ,  1745 ,  1750 ,  1755 ,  1760 . 
     FIG. 18  shows a process in which a data object, for example, data object  1700 , can be exploded for distribution to a target system. The explosion of a data object generally involves adding redundant data to a data object. Redundant data is data that exceeds the minimal amount of data necessary to describe the subject of an object to a given extent. By adding redundant data during an explosion, the format of a data object can be configured for distribution to a target component. The explosion process in  FIG. 18  can be performed as part of step  315  in process  300  ( FIG. 3 ). 
   The system receives information regarding the target system (step  1805 ). The received target system information can describe the technical capabilities of the target system to handle data objects. For example, the system can receive information identifying the attribute fields and their format in a particular class of data objects in the target system, or the system can receive an example object and then extract field and format information for written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network. 
   Method steps of the invention can be performed by one or more programmable processors executing a computer program to perform functions of the invention by operating on input data and generating output. Method steps can also be performed by, and apparatus of the invention can be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). 
   Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. Information carriers suitable for embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in special purpose logic circuitry. 
   To provide for interaction with a user, the invention can be implemented on a computer having a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. 
   The invention can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or an Web browser through which a user can interact with an implementation of the invention, or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), and the Internet. 
   The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. 
   The invention has been described in terms of particular implementations. Other implementations are within the scope of the following claims. For example, the steps of the invention can be performed in a different order and still achieve desirable results.