Abstract:
Embodiments relate to systems and methods for object-based modeling using modeling objects exportable to external modeling tools. A modeling client can host modeling logic and an application programming interface (API) to create, access, manipulate, and import/export modeling objects used in modeling applications, such as engineering, medical, financial, and other modeling platforms. In aspects, the source data accepted into the modeling client can be consumer or business-level applications, whose cell, database, or other data content can be extracted and encapsulated in an object-oriented format, such as extensible markup language (XML) format. The modeling client can exchange one or more resulting modeling object directly with external platforms, such as mainframe platforms, middleware databases, and others, via the application programming interface (API) on a programmatic basis. Costs and maintenance savings over mainframe-based modeling tools can thereby be achieved, while providing greater power than consumer or business-level tools.

Description:
FIELD 
     The present teachings relate to systems and methods for object-based modeling using model objects exportable to external modeling tools, and more particularly to platforms and techniques for dedicated modeling of technical, medical, financial, and other systems which are configured to programmatically import and export modeling objects to external enterprise resource planning systems, and other resources. 
     BACKGROUND OF RELATED ART 
     A spectrum of modeling platforms and options exist today for engineers, managers, developers and other professionals. In the case of engineering, medical, technical, financial, and other advanced modeling resources, a range of platforms are available for users interested in setting up, running and maintaining financial modeling systems. For example, organizations interested in relatively sophisticated modeling applications, such as geophysical models for detecting oil reserves or other geologic features or equity market analysis based on Black-Sholes option pricing models, a company or other organization may choose to install advanced modeling software on mainframe-class computers to run those classes of models and obtain various projections, reports, and other results. Such mainframe platform and related installations, however, can involve costs on the order of millions of dollars or more, and may require the full time attention of highly skilled professionals, including programmers and managers with advanced training. As a consequence, putting a mainframe-based ERP modeling operation into place may not be practical or possible for many organizations or users. 
     On the other end of the spectrum, managers, engineers and others may employ widely available entry-level applications to capture operational data and attempt to develop predictive models for engineering, financial, medial, and other applications. That class of applications can include, for example, consumer or business-level spreadsheet, database, or data visualization programs for technical, financial, and other purposes. For instance, a manager of a manufacturing facility may use a commercially available spreadsheet application to enter production numbers, schedules, and other details of that site. However, attempting to extract useful modeling outputs from those classes of applications can be difficult or impossible. For one, spreadsheet, database, and other widely available applications are typically built to produce reports based on already existing data, but not to generate modeling outputs or objects that represent predictive outputs or scenarios. For another, existing spreadsheet, database, and other applications typically involve limitations on cell size, number of dimensions, overall storage capacity, and other program parameters which, in the case of large-scale modeling operations, may be insufficient to operate on the data sets necessary to produce and run meaningful models. 
     For another, the data structures and outputs of existing spreadsheet, database and other entry-level or commonly available applications are typically arranged in proprietary format, rather than a widely interoperable object-based or other universal format. As still another drawback, the cells, rows, columns, and other data elements within commonly available spreadsheets, databases, and other entry-level programs can not be extracted as separate units and exported to other modeling or analytic tools. In short, the use of spreadsheet, database, and other consumer or business-level applications to conduct modeling operations involves significant shortcomings, due in part to the fact that those classes of platforms are not designed to reliable handle modeling functionality. 
     At present, therefore, a manager, developer, engineer, or other professional or user with modeling requirements is faced with a choice between installing a large and expensive mainframe-based ERP solution with its attendant infrastructure, a spreadsheet or database-based entry level solution with its attendant limitations on power and data handling, or a combination of those two types of platforms. It may be desirable to provide object-based or object-compatible modeling platforms capable of generating modeling objects which encapsulate various modeling features, and which are exportable to other external modeling tools. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the present teachings. In the figures: 
         FIG. 1  illustrates an overall system for a modeling network including various hardware and connectivity resources that can be used in systems and methods for object-based modeling using modeling objects exportable to external modeling tools, according to various embodiments of the present teachings; 
         FIG. 2  illustrates an exemplary modeling network including a modeling server and connectivity resources, according to various embodiments; 
         FIG. 3  illustrates an exemplary hardware configuration for a modeling server that can be used in systems and methods for object-based modeling using modeling objects exportable to external modeling tools, according to various embodiments; 
         FIG. 4  illustrates a flow diagram of overall modeling processing for object-based modeling using modeling objects exportable to external modeling tools, according to various embodiments. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Embodiments of the present teachings relate to systems and methods for object-based modeling using modeling objects exportable to external modeling tools. More particularly, embodiments relate to platforms and techniques that can access, extract, and exchange modeling objects in a native object-based or object-compatible format. The modeling objects produced via a modeling client or other modeling tool according to the present teachings can encapsulate both source data describing a physical, medical, technical, financial, or other process or phenomena, and modeling attributes that relate the source data to predictive scenarios, specific models, and other features. These and other embodiments described herein address the various noted shortcomings in known modeling technology, and provide a user or operator with enhanced modeling power on a desktop or other client, while allowing seamless communication of model objects to backend mainframe platforms, data centers, middleware servers, other modeling clients, and/or other local or remote modeling, storage, or data processing resources. 
     Reference will now be made in detail to exemplary embodiments of the present teachings, which are illustrated in the accompanying drawings. Where possible the same reference numbers will be used throughout the drawings to refer to the same or like parts. 
       FIG. 1  illustrates an overall network  100  in which systems and methods for object-based modeling using modeling objects exportable to external tools can be implemented, consistent with various embodiments of the present teachings. In embodiments as shown, a modeling client  102  can communicate with a variety of local and remote resources, including an mainframe platform  202  via one or more network  112 . Client  102  can be or include, for instance, a personal computer, a server, a dedicated workstation, a mobile device, or other machine, device, hardware, or resource. One or more network  112  can be or include, for example, the Internet, a virtual private network (VPN), a local area network such as an Ethernet™ network, or other public or private network or networks. Mainframe platform  202  can be or include commercially available platforms or installations, such as, merely for example, mainframe or enterprise platforms available from SAP Inc. of Walldorf, Germany, and other sources. 
     Mainframe platform  202  can include modules, logic, and functionality to perform an array of computation and data storage tasks, including data warehousing, data mining, statistical analyses, financial planning, inventory management, customer resource management, engineering design, and other applications. In implementations as shown, mainframe platform  202  can host or communicate with a variety or resources including, merely illustratively, a mainframe data store  206 , and logic or applications including an analytic module  204 . Mainframe platform  202  can contain, host, support, or interface to other data processing hardware, software, and other resources. In embodiments, modeling client  102  can likewise communicate with other local or remote resources, such as a middleware server  208  hosting or interfacing to a set of data stores for online analytical processing (OLAP) or other functions. Modeling client  102  can also communicate or interface with other local or remote servers, services, data stores, or other resources. 
     In embodiments as shown, modeling client  102  can operate under an operating system  118 , such as a distribution of the LInux™, Unix™, or other open source or proprietary operating system. Modeling client  102  can present a user interface  130 , such as a graphical user interface or command line interface, operating under operating system  118  to receive commands and inputs from a user, and operate modeling client  102 . Modeling client  102  can communicate with storage resources including a modeling store  104 , such as a local or remote database or data store. Modeling store  104  can store a set of modeling objects  106 , in which data, functions, procedures, attributes, and/or other information related to one or more modeling object  110  can be encapsulated and stored. In embodiments, modeling object  110  can be encoded in extensible markup language (XML) format. In embodiments, modeling object  110  can be encoded in other object-based or object-compatible formats or data structures. Modeling client  102  can communicate with mainframe platform  202  via a modeling application programming interface (API)  108 . Modeling application programming interface (API)  108  can include, for instance, defined function calls or calls to other routines, calculations, or features, as well as data structures and parameters associated with modeling operations. For example, modeling application programming interface (API)  108  can include a function call to invoke a Monte Carlo simulation model based on a set of supplied data, such as an identified set of dimensions extracted from a spreadsheet or database. Other functions, routines, resources, and features can be called, invoked, or instantiated via modeling application programming interface (API)  108 . According to embodiments in various regards, one or more local or remote modeling packages, modules, or other supporting applications can be instantiated via modeling module  120  and modeling application programming interface (API)  108  to manipulate source data and resulting one or more modeling object  110 . 
     In embodiments, a user of modeling client  102  can access, modify, or add data modeling objects to a set of data modeling object  106  via a modeling module  120  hosted in modeling client  102 . Set of data modeling objects  106  can include data objects that the user of modeling client  102  has directly entered, or, in aspects, which the user of modeling client has imported or extracted from sources such as consumer or business-level spreadsheet, database, and/or other applications or platforms. Modeling module  120  can itself be or include applications, software modules or hardware modules, or other logic or resources to operate on set of modeling objects  106 . Modeling module  120  can, merely illustratively, include or access logic or modules for invoking and manipulating a variety of scientific, technical, engineering, medical, financial, manufacturing, or other modeling operations. For instance, modeling module  120  can be or include applications or logic for performing Monte Carlo simulations, finite element analyses, Black-Scholes option pricing or other market analyses, epidemiological projections, geophysical models or simulations, or other simulations, models, trend mappings, projections, or other predictive processes. In embodiments in one regard, after invoking modeling module  120  and performing any modeling task, the user of modeling client  102  can export one or more modeling object  110  to external platforms or resources. 
     In embodiments as shown, the user of modeling client  102  can for instance export or communicate one or more modeling object  110  to mainframe platform  202  via modeling application programming interface (API)  108 , for storage and use at a local or remote location from within that platform. In aspects, mainframe platform  202  can receive modeling object  110  directly, without a necessity for translation, re-formatting, or invoking any spreadsheet, database, or other application from which data encapsulated in one or mode modeling object  110  originated. In aspects, mainframe platform  202  can operate on one or more modeling object  110 , and transmit or return that data or other results to modeling client  102  via modeling application programming interface (API)  108 . Thus, according to aspects of the present teachings, modeling objects can be exchanged directly and programmatically between modeling client  102 , mainframe platform  202  or other larger-scale or remote platforms, including for instance middleware server  208  or other comparatively large-scale or higher-capacity modeling or analytic tools. 
     In terms of operating on source data and generating one or more modeling object  110  for exchange with mainframe platform  202  or other platforms, and as shown for instance in  FIG. 2 , according to various embodiments, a user of modeling client  102  can invoke modeling module  120  to manipulate a set of source data  114  to identify, configure, and/or extract the functional objects, attributes, or other features of a set of data to produce a modeling output. In embodiments as shown, modeling module  120  can access a set of source data  114 , from which data, attributes, and/or other metadata can be extracted to generate one or more modeling object  110 . In aspects, set of source data  114  can be generated, hosted, or stored by or in a local application  134 , such as a spreadsheet, database, accounting, word processing, presentation, or other application or software. In aspects, set of source data  114  can comprise data previously or newly generated in the form of an object-based modeling object, such as a modeling object entered, imported, or specified by the user of modeling client  102 . 
     In aspects, set of source data  114  can comprise data originally stored or generated in a consumer or business-level spreadsheet, database, and/or other application or software. In aspects, set of source data  114  can be initially formatted or encoded in a non-object oriented format, such as in a cellular array or in a relational database format. In aspects, set of source data  114  can be initially formatted or encoded in an object-oriented format, such as extensible markup language (XML) format. In aspects, a user of modeling client  102  can highlight, select, or otherwise specify all or a portion of set of source data  114  to generate one or more extracted functional object  116 . For instance, a user can highlight a column of set of source data  114  to identify and extract data as well as functional relationships of interest, to the user, as a unified object. Thus, purely illustratively and as shown, a user may wish to obtain a view on a current month&#39;s sales figures including gross sales, tax, production or delivery costs, and cost basis, as well as other parameters related to sales activity. In aspects as shown, a user can, for instance, highlight those functional relationships by dragging a cursor or otherwise selecting a set of cells to group together, and form one or more extracted functional object  116 . 
     In aspects, selection can include the extraction of set of data elements  136 , such as values stored in spreadsheet cells or database entries. In aspects, once a set of data elements  136  are selected, the functional, computational, or other modeling parameters associated with that data can be stored or associated with one or more extracted functional object  116 . For instance, modeling module  120  can store associated routines, computations, processes, or other attributes or functional specifications for one or more extracted functional object  116  in set of attributes  122 , which can be stored or associated with one or more extracted functional object  116 . In aspects, set of attributes  122  can include the identification of or linkage to any routines, interlaces, or other functional or computational resources that will be associated with one or more extracted functional object. According to various embodiments, analytic module  204  of mainframe platform  202 , or other resource or platform receiving one or more extracted functional object  116  from modeling client  102  can thereby obtain both data values derived or obtained from set of source data  114 , as well as functional or procedural resources and relationships associated with that data. One or more extracted functional object  116  along with any associated set of attributes  122  can be encoded or stored in one or more modeling object  110 , which can thereby be transparently exported to mainframe platform  202 , middleware server  208 , or other platforms or destinations for further modeling operations. In embodiments, one or more model object  110  can be consumed or accessed by modeling client  102  itself, or other local or remote clients. 
       FIG. 3  illustrates an exemplary diagram of hardware, software, connectivity, and other resources that can be incorporated in a modeling client  102  configured to communicate with one or more network  112 , including to interface with mainframe platform  202 , middleware server  208 , and/or other local or remote resources, according to various embodiments. In embodiments as shown, modeling client  102  can comprise a processor  124  communicating with memory  126 , such as electronic random access memory, operating under control of or in conjunction with operating system  118 . Operating system  118  can be, for example, a distribution of the Linux™ operating system, the Unix™ operating system, or other open-source or proprietary operating system or platform. Processor  124  also communicates with a model store  104 , such as a database stored on a local hard drive, which may store or host set of modeling objects  106 . Processor  124  further communicates with network interface  128 , such as an Ethernet or wireless data connection, which in turn communicates with one or more networks  112 , such as the Internet, or other public or private networks. Processor  124  also communicates with modeling module  120  along with modeling application programming interface (API)  108  and/or other resources or logic, to execute control and perform modeling calculation, translation, data exchange, and other processes described herein. Other configurations of the network modeling client  102 , associated network connections, and other hardware and software resources are possible. While  FIG. 3  illustrates modeling client  102  as a standalone system comprises a combination of hardware and software, modeling client  102  can also be implemented as a software application or program capable of being executed by a conventional computer platform. Likewise, modeling client  102  can also be implemented as a software module or program module capable of being incorporated in other software applications and programs. In either case, modeling client  102  can be implemented in any type of conventional proprietary or open-source computer language. 
       FIG. 4  illustrates a flow diagram of overall processing that can be used in systems and methods for object-based modeling using modeling objects exportable to external modeling tools, according to various embodiments. In  402 , processing can begin. In  404 , a user of modeling client  102  or other client or device can invoke or instantiate modeling module  120  or other logic, to perform modeling operations. In  406 , modeling module  120  can access model store  104  and extract one or more modeling object  110  from set of modeling objects  106 . In  408 , modeling computations or other operations can be performed on one or more modeling object  110 . For example, a modeling operation can be performed to project or predict the output of a factory based on various supply scenarios for parts, materials, energy costs, or other variables. In  410 , the values, functions, linkages, or other attributes of one or more data modeling object  110  that were accessed, produced, or modified by the modeling operations can be captured, fixed, or locked down by modeling module  120 . For instance, the resulting one or more modeling object  110  can be stored to set of modeling objects  106  in model store  104 , or other databases or data stores. 
     In  412 , modeling application programming interface (API)  108  can be invoked by modeling module  120 , by mainframe platform  202 , or other resources to transfer one or mode modeling object  110  to mainframe platform  202 . In embodiments, one or more modeling object  110  can for instance be communicated to mainframe platform  202  via a secure connection or channel, such as a secure socket layer (SSL) connection, via a channel encrypted using a public/private key infrastructure, or other channel or connection. In  414 , one or more model object  110  can be received in modeling module  120  from mainframe platform  202  or other resource, as appropriate. For example, an updated version of one or more model object  110  reflecting new data, new modeling results, or other information can be received in modeling module  120 . In  416 , the resulting new, updated, or modified one or more model object  110  can be stored to set of modeling objects  106  in model store  104 , as appropriate. 
     In embodiments, one or more model objects  110  can in addition or instead be stored to mainframe data store  206 , to middleware server  208 , to another modeling client or other client, or other site or destination. In  418 , modeling module  120  can convert one or more model objects  110  to spreadsheet, database, or other format, and export any converted data as a set of cell-formatted information, or data encoded in other formats. For instance, modeling module  120  can convert or translate one or more model objects to cell data values or database entries, and export that data to client-level applications on modeling client  102  or other local or remote devices or storage. In  420 , processing can repeat, return to a prior processing point, jump to a further processing point, or end. 
     The foregoing description is illustrative, and variations in configuration and implementation may occur to persons skilled in the art. For example, while embodiments have been described wherein one or more model object  110  is accessed and manipulated via one modeling client  102 , in embodiments, one or more users can use multiple modeling clients, or networks including modeling clients or other resources, to operate on model object data. For further example, while embodiments have been described in which modeling client  102  may interact with one mainframe platform  202  and/or one middleware server  208 , in embodiments, one or more modeling client  102  can interact with multiple mainframe platforms, middleware servers, and/or other resources, in various combinations. Yet further, while embodiments have been described in which a modeling client  102  interacts with a mainframe platform  202  and/or middleware server  208 , in embodiments, rather than interact with large-scale enterprise platforms or middleware servers, modeling client  102  can interact with other local or remote modeling clients, networks of those clients, or, in embodiments, can operate to perform modeling operations on a stand-alone basis, without necessarily communicating with other modeling platforms. Other resources described as singular or integrated can in embodiments be plural or distributed, and resources described as multiple or distributed can in embodiments be combined. The scope of the present teachings is accordingly intended to be limited only by the following claims.