Embodiments are related to uniquely identifying and distinguishing multiple instances, objects or other data structures of or based on the same schema element or term for the same type of electronic tax return data, e.g., for when a user may have a Form W-2 from multiple employers, and distinguishing non-binding suggestions of what to present to a user when suggestions may involve the same tax topic, question or form.
Embodiments are also related to generating instance identifiers that are utilized by or circulated among multiple processing components of a tax return preparation application and eventually circulated back to the source that generated the instance identifier.
Embodiments are also directed to generating instance identifiers before and independently of generation of the instance for which the identifier is generated.
Embodiments are also directed to a source component generating an instance identifier and later receiving question or topic identified or referenced by the same instance identifier that may be presented to the user through an interview screen generated or selected by the source component.
Embodiments are also directed to generating and utilizing instance identifiers within a tax return preparation application in which a logic agent including a rule engine is loosely coupled to a user interface controller, and both of which share a data store to which the user interface controller writes data and from which the logic agent reads data for rule execution and selection of questions or topics to provide to the user interface controller.
Embodiments are also related to using instance identifiers for synchronization of electronic tax return data across different computing devices that are utilized to prepare different portions of an electronic tax return.
One embodiment is directed to a computer-implemented method for identifying different instances of a schema element, term or topic during preparation of an electronic tax return and comprises a user interface (UI) controller receiving first and second inputs related to respective first electronic tax return data and second electronic tax return data for the same element, term or topic of the schema utilized by a data store. For example, the first and second data may be for different Form W-2s for different jobs the user had during the past year. The method further comprises the UI controller generating a first instance identifier and a second instance identifier different than the first instance identifier for respective first and second electronic tax return data and writing the first electronic tax return data and the associated first instance identifier and the second electronic tax return data and the associated second instance identifier to the data store. A first instance for the first electronic tax return is generated from the schema element and identified by the first instance identifier, and a second instance for the second electronic tax return data is generated from the same schema element and identified by the different, second instance identifier. Thus, the data store contains two instances for the same question or topic as defined by the schema (e.g., for multiple Form W-2s), and these instances are uniquely identified for use by other components involved in processing the instance or runtime data.
Other embodiments are directed to systems for identifying different instances of a schema element, term or topic during preparation of an electronic tax return. A system may include a UI controller, or a UI controller and one or more other system components including a logic agent, a calculation engine and a data store shared among the UI controller, logic agent and calculation engine. One embodiment of a system comprises the UI controller, data store and logic agent. The system is structured or configured such that the UI controller can receive inputs related to respective first electronic tax return data and second electronic tax return data for the same element, term or topic of the schema utilized by a data store and generate different instance identifiers for the first and second electronic tax return data. The UI controller is configured or programmed to write the first electronic tax return data and the associated first instance identifier and the second electronic tax return data and the associated second instance identifier to the data store, and the logic agent is configured or programmed to read runtime data including the first instance data and the associated first instance identifier and the second instance data including the second instance identifier from the data store to determine non-binding suggestions for the UI controller based on use of a plurality of rules and runtime or instance data that serve as answers to questions.
Other embodiments are directed to a non-transitory computer-readable medium comprising instructions, which when executed by a processor of a computing device, causes the computing device to execute a process for identifying different instances of a schema element, term or topic during preparation of an electronic tax return. Embodiments may be executed by different types of computing devices including a desktop or laptop computer, a tablet computing device, or a mobile communication device such as a smartphone.
In a single or multiple embodiments, the first and second instances are generated from the same schema element or term involving the same electronic tax form such that first and second instances are generated from the schema for the same type of electronic tax form and are identified by different respective first and second instance identifiers. For example, if a user had multiple jobs, different instance identifiers would be generated and used for different instances for different Form W-2s. As another example, if the user had multiple sources of dividend income, different instance identifiers would be generated and used for different instances for different Form 1099.
In a single or multiple embodiments, the UI controller generates an instance identifier in response to certain pre-determined input triggers. An input trigger may be a user's request that is submitted through the user interface controller to enter or import data into an electronic tax form of the electronic tax return, e.g., to direct the user to a particular form so that data can be entered into the form, or to import data from a prior electronic tax return or from an electronic file generated by a financial management system such as QUICKEN, QUICKBOOKS or MINT financial management systems utilized by the user. QUICKEN, QUICKBOOKS and MINT are registered trademarks of Intuit Inc., Mountain View, Calif. Further, the UI controller may generate an instance identifier in response to an input trigger of receiving data from other data resources such as an account the user has with an online social networking site such as linkedin.com or facebook.com. The input triggers may be a request to enter data or to be directed to a certain form, or actual entry or importation of data through the UI controller, or certain navigation actions by the user such as clicking or selecting a pre-determined button or field within an interview screen generated by the UI controller.
In a single or multiple embodiments, multiple identifiers for respective instances of the same schema element are generated by the UI controller using a random number or other random identifier generator. In a single or multiple embodiments, the instance identifiers are universally unique identifiers (UUID) or Global Unique Identifiers (GUID). Given the manner in which instance identifiers are generated, they are unique so as to ensure that duplicate instance identifiers are not utilized. While the probability that all identifiers are different and unique may not be 100%, the probability is sufficiently high such that the identifiers that are generated are considered unique, particularly in the context of a particular user or particular electronic tax return. In a single or multiple embodiments, the same type of instance identifiers is generated, e.g., all instance identifiers generated by the UI controller are UUIDs, or all instance identifiers are randomly generated numbers. In other embodiments, in order to provide further reduce the likelihood that the already very low likelihood that a duplicate instance identifier would be utilized, the UI controller can alternate between instance generation methods such that one instance identifier may be a first type (e.g., randomly generated number), whereas another instance identifier is a different, second type (e.g., UUID).
In a single or multiple embodiments, an instance identifier is based at least in part upon one or more of time stamp data of when the instance identifier is generated, an identifier of a hardware component of a computing device utilized to generate the timestamp data or the instance identifiers, and electronic tax return data or an encoded form thereof.
In a single or multiple embodiments, after an instance has been generated from the schema and stored to the data store such that the generated instances include the electronic tax return data and instance identifiers or instance identifiers are associated therewith, other components of the tax return preparation program can read runtime data including the instance data and instance identifiers from the data store for subsequent processing. For example, a calculation engine may read runtime data including data of various instances and their associated instance identifiers from the data store, execute one or more calculations, and write the results back to instances within the data store using the applicable instance identifiers. Further, a logic agent can read runtime data from the data store including respective instance data and respective associated instance identifiers, and which may include a result generated by the calculation engine, and use the runtime data and rules to select a question or tax topic and generate non-binding suggestions for the UI controller regarding which question or topic to present to the user. For this purpose, the logic agent may access a decision table that specifies rules and a plurality of questions and respective answers to respective questions, wherein whether a rule applies is based at least in part upon an answer to at least one question, and the runt time data read from the data store serves as answers to the questions.
The suggestion may include a question or tax topic and the associated instance identifier so that the UI controller can differentiate suggestions involving the same topic or tax document, e.g., if a particular suggestion involves a first instance for Form W-2, but not a second instance for Form W-2, then the instance identifiers can be utilized by the UI controller for differentiation.
In a single or multiple embodiments, the generated instance identifiers are used for synchronization across multiple computing devices that are utilized to prepare the electronic tax return. For this purpose, one computing device may synchronize with another computing device utilizing instance identifiers, which may involve transmitting or receiving instance data and identifiers. In this manner, instance data and the associated instance identifier is within a data store of a tax return preparation application utilized by one computing device, and the same instance data and associated instance identifier is within a data store of a tax return preparation utilized by another computing device. A shared data store may also be utilized so that the different computing devices can connect to the data store to read/write instance data and identifiers for subsequent retrieval or read by another computing device for synchronization. Thus, for example, a user may begin to prepare an electronic tax return using a tax return preparation application executing in a laptop computer, but continue preparing the electronic tax return using the tax return preparation application executing on a tablet computing device. Instance identifiers can be received or transmitted to ensure that the correct and updated data is being utilized on both computing devices, and that respective data is for the correct form, e.g., in the event that the user has multiple Form W-2s, and the unique instance identifiers will be used to ensure that data from a first Form W-2 is synched to the first Form W-2 on the other computing device, and data from a second Form W-2 is synched to the second form W-2 on the other computing device by use of the instance identifiers identifying the different Form W-2 objects.
Embodiments are directed to computer-implemented methods, computerized systems and articles of manufacture or computer program products for uniquely identifying and distinguishing instances or objects generated from the same schema element for the same type of electronic tax return data during preparation of an electronic tax return. A data store or “dictionary” of terms or schema elements and associated data may be structured according to a schema or data model. For a schema element “Form W-2,” for example, when data of Form W-2 is received at the data store, an instance identifiers for that Form W-2, or data thereof, is generated and populated with the data, and when data for another Form W-2 is received, a different instance identifier is generated for that other Form W-2, or data thereof. Embodiments are implemented in a tax return preparation application structured in a modular manner and that includes a logic agent, a user interface controller and a calculation engine that share a data store. The UI controller and the logic agent are loosely coupled to each other such that the logic agent informs the UI controller potential questions or topics to ask the user of the tax return preparation application in the form of non-binding suggestions, and the UI controller determines whether/when those suggestions will be processed. Thus, the UI controller is not controlled by the logic agent or logic agent suggestions.
In one embodiment, referring to
For example, referring to
For example, processing may involve, the logic agent 210 determining one or more non-binding suggestions 211 based at least in part upon the runtime or instance data 242, and providing the non-binding suggestions 211 including or associated with one or more of the instance identifier 222a,b to the UI controller 230 (which was the source or generator of the instance identifiers 222).
Processing may also involve the calculation engine 280 reading the runtime or instance data 242, including the associated identifiers 222, and performing calculations using the data to generate calculation results 281, which are written back to the instances 242/data store 240 and with reference to the identifiers 222, and then the runtime data 242 including the new result 281 is read by the logic agent 210. Thus, not only does the UI controller 230 generate the instance identifiers 222 for received electronic tax data 231, but other components utilize that identifiers 222, and the identifiers 222 are later utilized by the UI controller 230 when the UI controller 230 determines whether or how to process the received non-binding suggestions 211. Further details regarding embodiments are described with reference to
The rule engine 412, is operable to receive runtime or instance data 442 (generally, runtime data 442) that is based on a “dictionary” of terms of a data model or schema 446 (generally, schema 446) and use that runtime data 442 to analyze rules 461 of a decision table 460. For example, the schema 446 may specify, define or list tax-related concepts or terms, e.g., by names, type or category and hierarchy such as “name,” “social security number,” “citizenship,” “address,” “employer,” “interest,” “dividends,” “mortgage,” “deduction,” “tax credit,” “capital gain,” etc. An instance 442 is instantiated or created for the collection of data received and for each term or topic of the schema 446. The schema 446 may also specify a certain format of questions and answers (e.g., answer is binary (Y/N) or a number/value). It will be understood that the schema 446 may define hundreds or thousands of such concepts or terms and may be defined in various ways, one example is based on an Extensible Markup Language (XML) schema. Non-limiting examples of schemas 446 that may be utilized in embodiments include Modernized E-File (MeF) and MeF++ schemas. It will be understood that embodiments may utilize various other schemas, and that these schemas are provided as a non-limiting example of a schema 446 that can be utilized in embodiments.
The runtime data 442 stored in the shared data store 440 is used to populate corresponding fields of an electronic tax return or electronic tax form used to prepare an electronic tax return and may be received from or based on data from various data electronic data sources 450a-d (generally, electronic data source 450). Examples of electronic data sources 450 include user input, such as a user answer to a question presented in an interview screen, data imported from a prior year electronic tax return, data from online resources (such as online social networks or other online resources) and third parties databases or resources (such as government databases or documents, such as property tax records, Department of Motor Vehicle (DMV) records, etc. The rule engine 412 reads runtime data 442 including generated identifiers 422 from the shared data store 440 and utilizes the decision table 460 including rules 461 to determine, based on the runtime data 442, which rules 461 still require data or which questions 462 still need to be presented to the user based on the runtime data 442 being answers to various questions 462, or data for the rules 461, of the decision table 460.
Various types of rules 461 may be utilized by embodiments. For example, “tax” rules 461 that are utilized by the rule engine 412 may specify which types of data or tax documents are required, or which fields or forms of the electronic tax return should be completed. One example is if a taxpayer is married, then the electronic tax return is required to include information about a spouse. A tax rule 461 may involve if a certain box on a form (e.g., Box 1 of Form W2) is greater than a pre-determined amount, then certain fields of the electronic tax return (e.g., withholding fields) cannot be left empty and must be completed. Thus, tax rules 461 may reflect various tax requirements and are expressed using the concepts or terms of the data model or schema 446. As another example, other rules 461 may specify tax consequences or calculations and for this purpose, the logic agent 410 may be in communication with other modules or services 470a-d (generally, “Additional Services” such as printing, e-filing, tax recommendations, calculation).
Rules 461 can be used for identifying or narrowing which questions 462 are identified as potential questions to be presented to the user. This may involve utilizing rules 461 based on one or more associated data structures such as a decision table 460, which is based on a completion graph 465, which recites, for example, the requirements of a tax authority or a tax authority rules or laws. The decision table 460 may be used for invalidation of potential questions 461 or topics and input or runtime data 442 requirements.
For example, referring to
The logic agent 410 may also receive or otherwise incorporate information from a statistical/life knowledge module 490. The statistical/life knowledge module 490 contains statistical or probabilistic data related to the current or other users of the tax return preparation application and/or other taxpayers. For example, statistical/life knowledge module 490 may indicate that taxpayers residing within a particular zip code are more likely to be homeowners than renters. The logic agent 410 may use this knowledge to weight particular topics or questions related to these topics when processing rules 461 and questions 462 and generating non-binding suggestions 411 of a question, declarative statement or identification of a topic to ask the user.
For example, questions 461 about home mortgage interest may be promoted or otherwise given a higher weight for users in particular zip codes or income levels. The statistical knowledge may apply in other ways as well. For example, tax forms often require a user to list his or her profession. These professions may be associated with transactions that may affect tax liability. For instance, a taxpayer may list his or her occupation as “teacher.” The statistic/life knowledge module 490 may contain data that shows that a large percentage of teachers have retirement accounts, and in particular, 403(b) retirement accounts. This information may then be used by the logic agent 410 when generating its suggestions 411. For example, rather than asking generically about retirement accounts, the suggestion 411 can be tailored directly to a question about 403(b) retirement accounts.
The data that is contained within the statistic/life knowledge module 490 may be obtained by analyzing aggregate tax data of a large body of taxpayers. For example, entities having access to tax filings may be able to mine their own proprietary data to establish connections and links between various taxpayer characteristics and tax topics. This information may be contained in a database or other repository that is accessed by the statistic/life knowledge module 490. This information may be periodically refreshed or updated to reflect the most up-to-date relationships. Generally, the data contained in the statistic/life knowledge module 490 is not specific to a particular tax payer but is rather generalized to characteristics shared across a number of tax payers although in other embodiments, the data may be more specific to an individual taxpayer.
In one embodiment, the rule engine 412 reads the runtime data 442 and uses that data 442 as answers or inputs to the decision table 460 to eliminate rules 461 that may apply which, is used to eliminate candidate questions 462 from consideration rather than requiring the user to step through each question of a pre-determined sequence of questions in order to conclude that a particular tax situation or topic applies to the user.
For example, continuing with the example shown in
The logic agent 410 provides to the UI controller 430 a non-binding suggestion 411 comprising a selected question or topic 461 to be addressed. In the illustrated embodiment, the UI controller 430 includes a UI or user experience manager 436 that determines how to process the non-binding suggestions 411 with the selected questions or topics 461 and generates an interview screen 432 for the UI or selects an interview screen 432 of the UI based on the question or topic 461 of the non-binding suggestion 411. For ease of explanation, reference is made generally to a UI controller 430.
The UI controller 430 suggestion resolution element, a generator element, and an interview screen management element or flow/view management” module as described in U.S. application Ser. No. 14/206,834, previously incorporated herein by reference, the suggestion resolution element is responsible for resolving the strategy of how to respond to incoming non-binding suggestions 441 provided by the logic agent, and for this purpose, the suggestion resolution element 341 may be programmed or configured or controlled by configuration files 433 that specify whether, when and/or how non-binding suggestions 411 are processed (e.g., priority, sequence, timing, in a current, next or subsequent interview screen, random, never or ignore, not until additional data received or other tax forms are completed).
For example, a configuration file 433 may specify one or more or all of how to process the non-binding suggestion 411 based on whether to consider or ignore the non-binding suggestion 411, when the non-binding suggestion 411 should be processed, content of an interview screen 432 based on the non-binding suggestion 411, how to present content or interview screens 432 based on the non-binding suggestion 411 in view of a form factor or type of a computing device utilized by the user of the tax preparation application or that executes the tax return preparation application embodying system components described above, which non-binding suggestion(s) 411 have priority over others or a sequence of non-binding suggestions 411, which configuration files 433 have priority over others or a sequence of configuration files 433 in the event that multiple configuration files 433 may potentially be used for purposes of configuration conflict resolution. For example, a configuration file 433 may specify that a non-binding suggestion 411 should be processed or addressed immediately or on the spot, next, at a later time, after certain or other additional tax return data has been received, or at the end of the process. Configuration files 433 may also specify whether non-binding suggestions 411 should be processed individually or aggregated for processing as a group with resolution of any priority issues. As another example, a configuration file 433 may specify that content should be adjusted or whether or how non-binding suggestions 411 should be processed in view of a screen size or dimension of a type of computing device that executes the tax preparation application since questions or more content may be more suitable for computing devices such as laptop and desktop computers, which have larger screens than smaller mobile communication devices such as smartphones.
The UI controller 430 generates the resulting user interaction or experience or creates or prepares an interview screen 432 or content thereof based on a library of visual assets such as pre-programmed interview screens or interview screens that are templates and that can be populated by the UI controller with a question 461 or topic of a non-binding suggestion 411.
With continuing reference to
Thus, in contrast to the rigidly defined user interface screens used in prior iterations of tax preparation software, embodiments of the current invention provide tax preparation software that runs on computing devices that operates on a new construct in which tax rules and the calculations based thereon are established in declarative data-structures, namely, completeness graph(s) and tax calculation graph(s). Use of these data-structures permits the user interface to be loosely connected or even divorced from the tax calculation engine and the data used in the tax calculations. Tax calculations are dynamically calculated based in tax data derived from sourced data, estimates, or user input. A smart tax logic agent 410 running on a set of rules 461 can review current run time data 442 and evaluate missing data fields and propose suggested questions 411 to be asked to a user to fill in missing blanks. This process can be continued until completeness of all tax topics reflected in decision tables 460 has occurred. An electronic return can then be prepared and filed with respect to the relevant taxing jurisdictions.
Additionally, according to embodiments, the UI controller 430 includes or utilizes an identity generator module 420 (generally, ID generator 420) as shown in
Referring to
Continuing with reference to
According to one embodiment, an instance identifier 422 is generated for each data element received, e.g., for each specific piece of data (name, SSN, income, etc.) as well as for a collection or aggregation or collection of data (e.g., a separate instance identifier 422 for schema 466 element Form W-2 that includes a collection of other data that have their own instance identifiers 422). According to one embodiment, the instance identifier 422 that is generated is a Universally Unique Identifier (UUID), which is represented by 32 hexadecimal digits, resulting in approximately 3.4×1038 possible UUID combinations. While this specification refers to a “unique” instance identifier 422, it will be understood that the probability of an instance identifier 422 being unique or not being duplicated is 99.99%+ (e.g., for when UUIDs are utilized), and while there is a minute possibility that there could be a duplicate UUID, for purposes of explanation, reference is made to a unique UUID or unique instance identifier 422.
According to another embodiment, the instance identifier 422 is generated by the UI generator 430 utilizing a random generator, such as a random number generator of a suitable number of digits to provide a suitable number of number possible instance 422 variations to provide for “unique” instance identifiers 422. UUIDs may also involve randomly generated numbers.
Certain embodiments may utilize instance identifiers 422 that embody or incorporate other aspects of the system, such as timestamp data of when a user request was made through the UI controller 430, when electronic tax return data 431 was received or imported, and timestamp data of when an instance identifier 422 was generated. UUIDs may also use or be based at least in part upon these or other types of timestamp data. Certain embodiments may also embody or incorporate other system aspects such as an identifier, such as a network address, of a computing component that generated the instance identifier 422. UUIDs may also be based on a Media Access Control (MAC) address of the computing component that generated the UUID. Certain embodiments may also utilize an instance identifier 422 that embodies or encodes the electronic tax return data 431 itself. Embodiments may also utilize one or more of these identifier generation methods. Moreover, while
Continuing with reference to
At 808, the first electronic tax return data 431a and the first instance identifier 422a generated by the UI controller 230 are written to the shared data store 240 which, at 808, generates a first instance 442a from a schema 446 element or term including first electronic tax return data 431a and including or associated with previously generated first instance identifier 422a. As noted above, the first electronic tax return data 431a may involve different numbers of instance identifiers 422, and for ease of explanation, reference is made to first electronic tax return data 431a and a first instance identifier 422a.
Referring to
Thus, referring to
Referring to
Depending on runtime data 442 was initially available and calculations that were performed, the calculation engine 480 may operate on only first electronic tax return data 431a, only on second electronic tax return data 431b, or both. Thus, at 1206, the calculation engine 480 determines first instance identifier 222a and writes result 481a of calculation involving first electronic tax return data 431a to shared data store 440 to update corresponding first instance 442a identified by first instance identifier 422a. Similarly, at 1208, the calculation engine 480 determines second instance identifier 422b and writes result 481b of calculation involving second electronic tax return data 431b to shared data store 440 to update corresponding second instance 442b identified by second instance identifier 422b. In this manner, the calculation engine 480 utilizes the generated instance identifiers 422a,b to distinguish a calculation involving, for example, one Form W-2, but not another Form W-2, and is able to write a result 481 back to the correct instance 442 utilizing the generated instance identifiers 422, thus preventing or reducing the possibility that calculation results for one form will be inadvertently written to the data store 440 for another form.
While certain embodiments are described with reference to performing calculations involving both first and second electronic tax return data 431a,b and writing back results 481a,b to the data store 440 with reference to respective first and second instance identifiers 422a,b, it may be the case that the calculations involve one or some of the electronic tax return data, but when the calculations are performed and results are written back to the data store 440, the instance identifier 422 for that data is still utilized to ensure that the result 481 data is written back to the correct location within the data store 440. For example, first electronic tax return data 431a may have been processed first, and then a calculation was performed on that first electronic tax return data 431a, and later, the user entered data for a second form, and a subsequent calculation may involve involved only the second electronic tax return data 431b, or both the first and second data. Or, a calculation may involve the first electronic tax return data 431a again. Thus, reference is made to processing involving both the first and second electronic tax return data 431a,b for ease of explanation, not limitation, and it will be understood that the calculation engine 480 may operate on various types and combinations of electronic tax return data 431 that was written to or available from the data store 440 at various times.
Referring to
At 1310, the logic agent 410 determines which questions or topics 462 remain or are eligible to be asked of the user, and these questions or topics 462, at 1312 are the subject of one or more non-binding suggestions 411 generated by the logic agent 410 and provided to the UI controller 430. According to embodiments, the suggestion 411 generated by the logic agent 410 includes or is associated with the instance identifier 422, such that the instance identifier 422 that was originally generated by the UI controller 430 for electronic tax return data 431 is also part of or associated with a non-binding suggestion 411 generated by the logic agent 430 based at least in part upon that same electronic tax return data 431.
Referring to
As discussed above with reference to
With continuing reference to
With embodiments, the instance identifier 422 is utilized to differentiate objects or non-binding suggestions 411 involving the same tax topic or question. For example, if the user has three Form W-2s from three employers, the UI controller 430 is able to differentiate which of two of the three Form W-2s requires action or is the subject of a non-binding suggestion 411 and which ones are not.
With continuing reference to
Continuing with reference to
At 1418, for non-binding suggestions 411 and responses/answers 431 that are already associated with instance identifiers 422, the processing described above in which the calculation engine 480 accesses the data store 440, generates a calculation result 481, writes the calculation result 481 to the data store 440, the logic agent 410 reads runtime data 442 from the data store 440 and generates non-binding suggestions 411, which are processed by the UI controller 430 is repeated. At 1418, when the trigger detect module 425 detects an input trigger to generate a new instance identifier 422, the process described above in which the UI controller 430 generates the instance identifier 422, updates the identifier table 427, writes electronic tax return data 431 and the instance identifier 422 to the data store 440, and generation of an instance 422 including the electronic tax return data 431 and associated instance identifier 422 are repeated. It will be understood that whether an instance identifier 422 has already been generated for an answer or response or whether a new instance identifier 422 is generated by the UI is based at least in part upon how the schema 446 is configured, and what the input triggers are, e.g., an input trigger may be for data input into a specified field that was not answered such that a new instance identifier 422 is not yet needed, but if the specified field was answered, then the UI controller 430 would generate a new instance identifier 422 based at least in part upon the selection or entry of data for that specified field.
Referring to
The first user may prepare a portion of the electronic tax return 1520 using a laptop computer 1510a, and the second user may prepare a portion of the electronic tax return 1520 using a tablet computing device 1510b. At 1608, the second UI controller 430b of the second tax return preparation application 1530 executing on the second computing device 1510b generates instance identifier(s) 422c for electronic tax return data 431c. At 1610, a network or communication connection 1540 between first and second computing devices 1510a,b is established, and the tax return preparation applications 1530a,b communicate with each other to synchronize electronic tax return data 431a,b and 431c between first and second computing devices 1510a,b using respective instance identifiers 422a,b and 422c at 1712. Synchronization may involve one-way synchronization or two-way synchronization.
For example, synchronization may involve the laptop computer 1510a and the tablet computing device 1510b being connected to each other through a wired network connection or a wireless network connection 1540, and according to one synchronization embodiment, the first UI controller 430a of the first tax return preparation application 1530a executing on the first computing device 1510a accesses the second table 427b managed by the second UI controller 430b and/or the second data store 440b of the second tax return preparation application 1530b executing on the second computing device 1510b. The first UI controller 430a determines whether there are any instance identifiers in the second table 427b or the data store 440b that the first UI controller 430a did not generate. This may involve the first UI controller 430a comparing instance identifiers 422 maintained in the first table 427a managed by the first UI controller 430a and the instance identifiers 422 maintained in the second table 427b managed by the second UI controller 430b and/or the second data store 427b. For any instance identifiers 422 that are not present within the first table 427a managed by the first UI controller 430a, this indicates electronic tax return data 431 on the second computing device 1510b that is not on the first computing device 1510a. The first UI controller 430a then requests the second tax return preparation application 1530b, e.g., through one or more of the second UI controller 430b and the second data store 440b, to transfer electronic tax return data 431 and respective instance identifiers 422 from the second computing device 1510b to the first computing device 1510b so that the first computing device 1510a will then include any instance data 442 of the second computing device 1510b identified by instance identifiers 422 not generated by the first computing device 1510a.
Similarly, the second UI controller 430b of the second tax return preparation application 1530b executing on the second computing device 1510b accesses the first table 427a managed by the first UI controller 430a and/or the first data store 440a of the first tax return preparation application 1530a executing on the first computing device 1510a. The second UI controller 430b determines whether there are any instance identifiers 422 in the first table 427a or the first data store 440a that the second UI controller 430b did not generate. This may involve the second UI controller 430b comparing instance identifiers 422 maintained in the second table 427b managed by the second UI controller 430b and the instance identifiers 422 maintained in the first table 427a managed by the first UI controller 430a and/or the first data store 440a. For any instance identifiers 422 that are not present within the second table 427b managed by the second UI controller 430b, this indicates electronic tax return data on the first computing device 1510a that is not on the second computing device 1510b. The second UI controller 430b then requests the first tax return preparation application 1530a, e.g., through one or more of the first UI controller 430a and the first data store 440a, to transfer instance data 442 and respective instance identifiers 422 from the first computing device 1510a to the second computing device 1510b so that the second computing device 1510b will then include any instance data 442 of the first computing device 1510a identified by instance identifiers 422 that were not generated by the second computing device 1510b.
Synchronization may involve one-way synchronization, e.g., from the first computing device 1510a to the second computing device 1510b, or from the second computing device 1510b to the first computing device 1510a. Thus, with one-way synchronization, one computing device includes all of the instance data, but not both computing devices 1510a,b. Synchronization may also be two-way synchronization so that the first and second computing devices 1510a,b (or other numbers of computing devices utilized to prepare an electronic tax return) are synchronized with each other and both devices have all of the current runtime or instance data 442. Synchronization may be performed in response to user request or automatically and periodically.
When the electronic tax return is populated and completed by the logic agent 410 or by the direction of the logic agent 410 or using one or more components or services 470 as applicable, the electronic tax return can be printed and/or filed with a tax authority such federal state or local tax authority or other tax collecting entity such as Internal Revenue Service and Franchise Tax Board of the State of California.
Method embodiments or certain steps thereof, some of which may be loaded on certain system components, computers or servers, and others of which may be loaded and executed on other system components, computers or servers, may also be embodied in, or readable from, a non-transitory, tangible medium or computer-readable medium or carrier, e.g., one or more of the fixed and/or removable data storage data devices and/or data communications devices connected to a computer. Carriers may be, for example, magnetic storage medium, optical storage medium and magneto-optical storage medium. Examples of carriers include, but are not limited to, a floppy diskette, a memory stick or a flash drive, CD-R, CD-RW, CD-ROM, DVD-R, DVD-RW, or other carrier now known or later developed capable of storing data. The processor 1720 performs steps or executes program instructions 1712 within memory 1710 and/or embodied on the carrier to implement method embodiments.
Although particular embodiments have been shown and described, it should be understood that the above discussion is not intended to limit the scope of these embodiments. While embodiments and variations of the many aspects of the invention have been disclosed and described herein, such disclosure is provided for purposes of explanation and illustration only. Thus, various changes and modifications may be made without departing from the scope of the claims.
Further, where methods and steps described above indicate certain events occurring in certain order, those of ordinary skill in the art having the benefit of this disclosure would recognize that the ordering of certain steps may be modified and that such modifications are in accordance with the variations of the invention. Additionally, certain of the steps may be performed concurrently in a parallel process as well as performed sequentially. Thus, the methods shown in various flow diagrams are not intended to be limited to a particular sequential order, unless otherwise stated or required.
Accordingly, embodiments are intended to exemplify alternatives, modifications, and equivalents that may fall within the scope of the claims.
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