System and methods for synchronizing two or more datasets

Abstract

Synchronization system and associated methods provide synchronization of an arbitrary number of datasets, including more than two datasets. To achieve this, a reference dataset is used to store a super-set of the latest or most-recent data from all user datasets to provide a repository of information that is available at all times. Therefore, if the user later wishes to synchronize a new user dataset, such as one in a server computer that stores user information, the system already has all the information necessary for synchronizing the new dataset, regardless of whether any of the other datasets are then available. Further, to simplify use, a unified user interface is provided that allows the user to easily determine which of his or her datasets are currently set to be synchronized and allows the user to conveniently alter the current settings to select one, two, or even more than two clients for synchronization. Various "conflict" or "duplicate" resolution strategies are described for intelligently handling complexities resulting from allowing synchronization for an arbitrary number of datasets and allowing synchronization using even data from datasets that are not available. Architectural support for "plug-in" client accessors and type modules is also provided. This allows support to be added for new datasets or new types of data merely by developing and plugging in new, compact client accessors or type modules, without updating or replacing the core synchronization engine.

Claims

What is claimed is:

1. In an information processing system, a method for synchronizing an arbitrary number of multiple datasets residing on different devices, the method comprising:

accepting a designation of an arbitrary number of multiple datasets comprising more than two datasets from different devices to be synchronized, wherein at least one of the designated datasets includes one record to be synchronized with all others of the designated datasets;

in response to said designation, creating a reference dataset that is used to store a super-set of most-recent data from all of the designated datasets, said reference dataset having records that are uniquely identified in a manner that is independent of how records are identified in any given one of the designated datasets, thereby providing a repository of information that is available independent of unavailability of one of said devices at a given point in time; and

in response to the designation and based on the information stored by said reference dataset, synchronizing all of the designated datasets without requiring further designating of datasets to be synchronized, wherein, after the step of synchronizing, each of the designated datasets includes a record that corresponds to, and is in a synchronized state with, the one record.

2. The method of claim 1 wherein the number of designated datasets is N, and the step of synchronizing the N designated datasets comprises performing a sequence of binary reconciliations, each involving at least one of the N designated datasets, to obtain at least one dataset that is globally-synchronized, wherein any globally-synchronized dataset includes propagated changes, if any exist and were not discarded due to conflict resolution, from each of the N designated datasets, and any dataset by definition includes changes, if any, propagated from itself.

3. The method of claim 2 wherein the step of synchronizing the N designated datasets further comprises, after the step of performing the sequence of binary reconciliations, synchronizing each dataset, of the N designated datasets, that is not yet globally-synchronized with another dataset that is already globally-synchronized.

4. The method of claim 3 wherein a reference dataset is involved in each of at least N-1 binary reconciliations in the sequence of binary reconciliations.

5. The method of claim 3 wherein the sequence of binary reconciliations comprises at most N binary reconciliations, wherein at least (N-1) of the at most N binary reconciliations each involves at least one of the N designated datasets.

6. The method of claim 3 wherein:

the sequence of binary reconciliations includes a first binary reconciliation involving a first dataset and a second, later binary reconciliation;

the first dataset includes a record that has a modification time; and

the step of performing the sequence of binary reconciliations comprises causing, during the first binary reconciliation, a recording of the modification time such that the modification time is available for use after start of the second binary reconciliation.

7. The method of claim 6 wherein:

the second binary reconciliation involves a second and a third dataset, each of which is not the first dataset; and

the step of performing the sequence of binary reconciliations further comprises comparing the recorded modification time to another time in resolving a conflict between a record from the second dataset and a record that is already in a synchronized state with regard to the first record.

8. The method of claim 1 wherein the step of synchronizing the more than two designated datasets comprises:

providing a synchronizer dataset that contains records, wherein the synchronizer dataset reflects a result of an earlier synchronization;

comparing each of the more than two designated datasets to the synchronizer dataset to identify an addition, update, or deletion of a record in the each designated dataset;

changing at least two of the designated datasets based on the identified addition, update, or deletion of a record; and

changing the synchronizer dataset based on the identified addition, update, or deletion of a record.

9. An information processing system for synchronizing an arbitrary number of multiple datasets from different devices, the system comprising:

means for accepting a designation of an arbitrary number of datasets comprising more than two datasets from different devices to be synchronized, wherein at least one of the designated datasets includes one record to be synchronized with all others of the designated datasets;

means, responsive to said designation, for creating a reference dataset that is used to store a super-set of most-recent data from all of the designated datasets, said data comprising records uniquely identified within the reference dataset in a manner that is independent of how data is identified within the designated datasets, for providing a repository of information that is available independent of unavailability of one of said devices at a given point in time; and

means for synchronizing, in response to the designation and based on the information stored by said reference dataset, the more than two designated datasets without requiring further designating of datasets to be synchronized, wherein, after the step of synchronizing, each of the more than two designated datasets includes a record that corresponds to, and is in a synchronized state with, the one record.

10. A computer program product for use with a computer system comprising:

a computer-readable storage medium;

computer code on the storage medium for instructing the computer system to accept a designation of an arbitrary number of datasets comprising more than two datasets from different devices to be synchronized, wherein at least one of the designated datasets includes one record to be synchronized with all others of the designated datasets;

computer code on the storage medium, responsive to said designation, for creating a reference dataset that is used to store a super-set of most-recent data from all of the designated datasets, said data comprising records uniquely identified within the reference dataset in a manner that is independent of how data is identified within the designated datasets, for providing a repository of information that is available independent of unavailability of one of said devices at a given point in time; and

computer code on the storage medium for instructing the computer system to synchronize, in response to the designation and based on the information stored by said reference dataset, the more than two designated datasets without requiring further designating of datasets to be synchronized, wherein, after the step of synchronizing, each of the more than two designated datasets includes a record that corresponds to, and is in a synchronized state with, the one record.

11. A method capable of synchronizing more than two designated datasets, the method comprising:

providing a synchronizer dataset that contains records, wherein the synchronizer dataset reflects a result of an earlier synchronization of the designated datasets, and wherein each record in the synchronizer dataset is identified by a globally-unique record identifier that is independent of how any corresponding records from the designated datasets are identified;

creating a table that associates each globally-unique record identifier to any corresponding records residing on the designated datasets;

using said synchronizer dataset and said table, comparing values derived from each of the more than two designated datasets to values derived from the synchronizer dataset to identify a change of a record in the each designated dataset since an earlier synchronization involving the each designated dataset; and

changing at least two of the designated datasets based on the identified change of a record.

12. The method of claim 11 wherein the step of comparing each of the designated datasets to the synchronizer dataset comprises, for each of the designated datasets, comparing values derived from records from the each designated dataset to values derived from the synchronizer dataset to determine whether any records of the each designated dataset are updates or additions, or whether any record of the each designated dataset has been deleted, since a prior synchronization involving the each designated dataset.

13. The method of claim 12 wherein the step of comparing values derived from records comprises determining a particular record in the each designated dataset to be an update, if the particular record possesses a modification time that is later than a particular time.

14. The method of claim 13 wherein the particular time is a priority time associated with the corresponding record in the synchronizer dataset.

15. The method of claim 14 wherein the priority time is indicative of a modification time, herein referred to as the original priority time, of a record in a particular dataset, wherein values derived from the record in the particular dataset were used to change the corresponding record in the synchronizer dataset due to an earlier synchronization.

16. The method of claim 13 wherein the particular time is a time established based on a most recent earlier synchronization that involved the each designated dataset.

17. The method of claim 18 wherein the particular time is indicative of a time no earlier than a latest modification time, from any record of the each designated dataset, that existed prior to and was seen during the most recent earlier synchronization that involved the each designated dataset.

18. The method of claim 12 further comprising resolving conflicts among at least determined updates or deletions corresponding to a single record of the synchronizer dataset.

19. The method of claim 18 wherein:

the step of providing a synchronizer dataset comprises providing status information regarding contents of at least a particular dataset, of the designated datasets, according to an earlier synchronization involving the particular dataset; and

the step of comparing values derived from records further comprises:

determining a particular record in the each designated dataset to be an addition, if the particular record has no corresponding record in the synchronizer dataset; and

determining that the particular dataset includes a deletion, if the particular dataset no longer includes a valid record that corresponds to a particular record in the synchronizer dataset, wherein the particular dataset did have such a valid record at the end of an earlier synchronization, according to the status information.

20. The method of claim 19 wherein the step of comparing values derived from records further comprises:

comparing a CRC-type result derived from the particular record in the each designated dataset with a CRC-type result derived from the particular record during the earlier synchronization involving the each designated dataset; and

determining the particular record in the each designated dataset to be an update, if the CRC-type results differ.

21. The method of claim 19 wherein the step of comparing values derived from records comprises determining the particular record in the each designated dataset to be an update only if the particular record in the each designated dataset possesses a modification time that is later than a particular time.

22. The method of claim 19 further comprising:

comparing at least one value derived from a determined addition of a record with values derived from at least one other record to determine whether the determined addition represents a duplication of records.

23. The method of claim 22 further comprising:

comparing at least one value derived from a determined update of a record with values derived from at least one other record to determine whether the determined update represents a duplication of records; and

resolving any determined duplication of records.

24. The method of claim 19 further comprising, for at least one of the designated datasets:

identifying a change of a record in the synchronizer dataset since an earlier synchronization involving the at least one designated dataset; and

changing the at least one designated dataset based on the identified change in the synchronizer dataset.

25. The method of claim 24 wherein the step of resolving conflicts comprises resolving conflicts among a plurality of determined updates or deletions corresponding to the single record of the synchronizer dataset, wherein the plurality of determined updates or deletions includes an update or deletion identified in the synchronizer dataset and an update or deletion identified in one of the designated datasets.

26. The method of claim 24 wherein the step of resolving conflicts comprises resolving conflicts among more than two updates or deletions that correspond to the single record of the synchronizer dataset by giving precedence to one of the more than two updates or deletions over others of the more than two updates or deletions.

27. The method of claim 11 wherein at least one of the designated datasets is a non-participant in the earlier synchronization the result of which is reflected in the provided synchronizer dataset.

28. The method of claim 11 wherein all of the designated datasets are non-participants in the earlier synchronization the result of which is reflected in the provided synchronizer dataset.

29. The method of claim 28 further comprising, in the earlier synchronization, changing a first record in the synchronizer dataset; and after the earlier synchronization, in synchronizing the designated datasets:

identifying the changed first record in the synchronizer dataset to be an addition, update, or deletion; and

changing the designated datasets based on the first record in the synchronizer dataset.

30. A system for synchronizing more than two designated datasets, the system comprising:

means for providing a synchronizer dataset that contains records, wherein the synchronizer dataset reflects a result of an earlier synchronization and wherein each record in the synchronizer dataset is identified by a globally-unique record indentifier that is independent of how any corresponding records form the designated datasets are identified;

means for creating a table that associates each globally-unique record identifier to any corresponding records residing on the designated datasets;

using said synchronizer dataset and said table, comparing values derived from means, responsive to said synchronizer dataset and said table, for comparing each of the more than two designated datasets to the synchronizer dataset to idenifty an addition, update, or deletion of a record in the each designated dataset since an earlier synchronization involving the each designated dataset;

means for updating at least two of the designated datasets based on the identified addition, update, or deletion of a record; and

means for updating the synchronizer dataset based on the identified addition, update, or deletion of a record.

Description

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.

BACKGROUND OF THE INVENTION

The present invention relates generally to management of information or datasets stored on electronic devices and, more particularly, to a system implementing methods for maintaining synchronization of datasets among one, two, or more such devices.

With each passing day, there is ever increasing interest in providing synchronization solutions for connected information appliances. Here, the general environment includes "appliances" in the form of electronic devices including, but not limited to, cellular phones, pagers, other hand-held devices (e.g., REX.TM., PalmPilot.TM. and Windows.TM. CE devices), personal computers (PCs) of all types and sizes, and Internet or intranet access devices (e.g., PCs or embedded computers running, for example, Java virtual machines or browsers or Internet Protocol (IP) handlers).

A problem facing such an environment today is that these devices, and the software applications running on these devices, do not communicate well with one another and are typically not designed with data synchronization in mind. In particular, a problem exists as to how one integrates information--such as calendaring, scheduling, and contact information--among disparate devices and software applications. Consider, for instance, a user who has his or her appointments on a desktop PC at work, but also has a notebook computer at home and a battery-powered, hand-held device for use in the field. What the user really wants is for the information (e.g., appointments), in each device to remain synchronized with corresponding information in all devices in a convenient, transparent manner. Still further, some devices (e.g., PCs) are typically connected at least occasionally to a server computer, e.g., an Internet server, which stores information for the user. The user would of course like the information on the server computer to participate in the synchronization, so that the server also remains synchronized.

There have been attempts to solve the problem of synchronizing datasets across different devices or software applications. An early approach to maintaining consistency between datasets was to import or copy one dataset on top of another. This simple "one-way" approach, one which overwrites a target dataset without any attempt at reconciling any differences, is inadequate for all but the simplest of applications. Expectedly, more sophisticated synchronization techniques were developed. In particular, techniques were developed for synchronization of exactly two datasets by attempting to reproduce in each dataset the changes found in the other dataset since a previous synchronization.

The conventional synchronization techniques, which are limited to such pair-wise, or binary, synchronization, may satisfy an information appliance user who wishes to synchronize exactly two datasets. However, these conventional techniques do not adequately satisfy the modem information appliance user, who is accumulating ever more information appliances and software applications and frequently wants to synchronize information from more than just two datasets. To synchronize more than two datasets, such a user is forced by the conventional synchronization techniques to try to achieve the correct synchronization result using successive binary synchronizations. This approach is not only inefficient and generally inconvenient and confusing for the user, but is also fraught with potential for human error, and, further, may produce incorrect results in certain situations.

As an example, consider a user who needs to synchronize information, e.g., scheduling information, from three sources: a PalmPilot organizer device ("Pilot"), a Windows CE device ("CE Device"), and a Microsoft Outlook PIM (Personal Information Manager) software application ("Outlook") on a PC. The user may first perform a Pilot-and-Outlook synchronization, typically using a first synchronization software program that is designed and sold specifically for the Pilot. Next, the user may perform an Outlook-and-CE-Device synchronization, typically using a second synchronization program that is designed and sold specifically for the CE Device. At this point, the user may think he or she is finished. However, he or she in reality must still perform another Pilot-and-Outlook synchronization to ensure that the Pilot correctly includes the latest information from the CE Device. Unfortunately, conventional synchronization programs do not tell the user of the need for this additional synchronization.

In general, the conventional synchronization programs do not adequately help the user in keeping more than two datasets synchronized. For example, the conventional programs do not provide a single user interface (UI) that allows the user to select more than two datasets to be synchronized with every other selected dataset. The conventional programs also do not automatically perform the synchronization of data in more than two datasets for the user without further user input. At most, a conventional synchronization program may permit the user to select a pair of datasets having data of one type (e.g., contacts data) for synchronization and a possibly different pair of datasets having data of a different type (e.g., calendar data) for synchronization. Although the user selects more than two datasets in total, any actual synchronization involves only two datasets. More particularly, synchronization of similar data involves only two datasets. Put another way, no single data record on a particular dataset will effect changes in more than one other dataset in response to a user's selection of datasets using the conventional program. In short, the conventional synchronization scheme is inconvenient and susceptible to human error, especially by less technically-savvy users, and especially as the number of datasets above two increases for a user.

The conventional synchronization scheme suffers from a further problem in that when more than two datasets are synchronized using multiple binary synchronizations, dataset status information (e.g., data modification times) that may be available during earlier-performed synchronizations may not be available during later-performed synchronizations. The failure to retain these status information may be intentional and also reasonable under an assumption that only two datasets need ever be synchronized. The failure to retain these status information may also be caused in part by the design limitations of particular information devices or software applications. Whatever the cause, the unavailability of status information during later-performed synchronizations can lead to erroneous results when, for example, conflicts are resolved during later synchronizations, as will be described in a later section.

Another characteristic of the modem environment for connected information appliances is that new appliances are introduced with ever increasing frequency. Conventionally, an entirely new synchronization software application is released with each new appliance. Such a synchronization application is dedicated to synchronizing data in a single particular information appliance with data in one or several popular PIM applications on a PC. Consequently, the user must buy and install a separate synchronization application, which typically is multi-megabytes long, for each new information appliance. This approach is undesirable for a variety of reasons, including the reason that such large software applications typically cannot be quickly downloaded from the Internet by telephone modem or low-bandwidth channels. Furthermore, should it become desirable for the synchronization programs to synchronize additional types of data, e.g., electronic mail data or expense logging data, or for the synchronization programs to handle additional PC or other software applications, the synchronization software provider typically must upgrade and re-release every affected software application, and the user typically must obtain and install every affected and updated software application.

What is needed is a system and methods for synchronizing data among two or more datasets that is efficient, correct, and resistant to human error, even when more than two datasets need to be synchronized. What is also needed is such a system and method that can easily be expanded to handle new datasets and new data types. At the same time, the approach should be automated so that the user is provided with "one-click" convenience. The present invention fulfills these and other needs.

SUMMARY OF THE INVENTION

The present invention provides a versatile synchronization system and associated methods that provide user-configurable, easily-extensible synchronization among one, two, or more than two user datasets. One aspect of the present invention is that it presents a unified user interface to the user for synchronizing an arbitrary number of the user's datasets (or, "synchronization clients"). Preferably, this user interface includes a client map that allows a user to quickly determine which of his or her clients are currently set to be synchronized and allows the user to conveniently alter the current settings to select one, two, or more than two clients for synchronization.

Another aspect of the present invention is that it preferably controls a reference dataset, sometimes called the Grand Unification Database or GUD, to store a super-set of data from his or her user datasets. In this way, the system of the present invention provides a repository of information that is available at all times and does not require that any other user dataset be connected. Suppose, for instance, that a user has two datasets: a first that resides on a desktop computer and a second that resides on a hand-held device. If the user later wishes to synchronize a third user dataset, such as one in a server computer that stores user information, the system of the present invention has, in the GUD, all the information necessary for synchronizing the new dataset, regardless of whether any of the other datasets are then available. The system of the present invention can, therefore, correctly propagate information to any appropriate user dataset without having to "go back" to (i.e., connect to) the original user dataset from which that data originated. The system of the present invention includes various "conflict" or "duplicate" resolution strategies that handle the increased complexities of allowing synchronization for an arbitrary number of datasets and including in the synchronization even data from datasets that are not available.

Another aspect of the present invention is that, internally, it employs "type plug-in" modules, each one for supporting a particular data type. Since the core synchronization engine treats data generically (e.g., as undifferentiated data), type-specific support is provided by the corresponding plug-in module. Each plug-in module is a type-specific module having an embedded interface (e.g., an API--application programming interface) that each synchronization client may link to, for providing type-specific interpretation of undifferentiated data. For instance, the system may include one type-specific record API for contact information, another for calendar information, and yet another for memo information. In this manner, each client may employ a type-specific API for correctly interpreting and processing particular data. The engine, on the other hand, is concerned with correct propagation of data, not interpretation of that data. It therefore treats the data itself generically. In this fashion, the present invention provides a generic framework supporting synchronization of an arbitrary number of synchronization clients or devices.

An exemplary method for providing synchronization of more than two datasets includes, in an information processing system, accepting a designation of more than two datasets to be synchronized. At least one of the designated datasets includes one record to be synchronized with all others of the designated datasets. The method further includes, in response to the designation, synchronizing the more than two designated datasets without requiring further designating of datasets to be synchronized. After the step of synchronizing, each of the more than two designated datasets includes a record that corresponds to, and is in a synchronized state with, the one record.

Another exemplary method capable of synchronizing more than two designated datasets includes providing a synchronizer dataset that contains records. The synchronizer dataset reflects a result of an earlier synchronization. The method further includes comparing values derived from each of the more than two designated datasets to values derived from the synchronizer dataset to identify a change of a record in the each designated dataset since an earlier synchronization involving the each designated dataset. The method further includes changing at least two of the designated datasets based on the identified change of a record.

An exemplary method is provided for interacting with a user prior to a synchronization of datasets selected from a plurality of more than two datasets, in which the synchronization will leave each of the selected datasets with a record that is synchronized with respect to a corresponding record in each other one of the selected datasets. The method includes presenting an indicator of each of at least the selected datasets; presenting indicators to indicate possible flow of changes among the selected datasets; and accepting a change to the selection of datasets such that, after the step of accepting, the selected datasets to be synchronized include more than two of the plurality of more than two datasets.

Another exemplary method is provided for interacting with a user prior to a synchronization of at least one dataset from a plurality of datasets. The method includes presenting a indicator, referred to as the dataset indicator, of each of at least the at least one dataset to be synchronized; presenting a nexus indicator in addition to the dataset indicators; and presenting path indicators that schematically link the nexus indicator to the dataset indicators of at least the at least one dataset to be synchronized.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that shows the conventional approach to synchronization of datasets.

FIG. 2 is a block diagram that shows a synchronization system according to an embodiment of the present invention in an example environment.

FIG. 3A is a block diagram of a computer system in which the present invention may be embodied.

FIG. 3B is a block diagram of a software system of the present invention for controlling operation of the system of FIG. 3A.

FIG. 4A is a screen-shot that shows a graphical user interface provided by the Synchronizer, according to a preferred embodiment of the invention.

FIG. 4B is a screen-shot that shows the graphical user interface of FIG. 4A at a different moment.

FIG. 5A is a screen-shot of an options dialog box for changing synchronization and other settings for an example client, the REX.TM. organizer.

FIG. 5B is a screen-shot that shows a dialog box for changing options related to the Contacts data type.

FIG. 5C is a screen-shot that shows a data-field-mapping table displayed by the Synchronizer for changing data-field mappings for a particular mapping of record files from different clients.

FIG. 6 is a flowchart that summarizes a method used by the Synchronizer for interacting with a user.

FIG. 7A is a flowchart that illustrates a method used by a "binary-based" embodiment of the Synchronizer for synchronizing two or more than two datasets using multiple binary synchronizations.

FIG. 7B is a flowchart that illustrates a particular implementation of the method of FIG. 7A.

FIG. 7C is a table that shows a faulty result produced by the basic binary-based embodiment of the Synchronizer that can be remedied in an improved system.

FIG. 9A is a block diagram that shows the architecture of a Synchronizer according to the preferred embodiment of the invention.

FIG. 9B is a block diagram that schematically shows the mechanism by which the engine, the client accessors, and the type modules of the Synchronizer communicate with one another.

FIG. 10A is a block diagram that shows components of a Synchronizer dataset.

FIG. 10B is a table that shows records of the Synchronizer dataset, including their data and some of their status information.

FIG. 10C is a table that shows portions of the mapping table (of FIG. 10A) that describes a particular client's records.

FIG. 11A is a flow chart that illustrates the Synchronizer's methodology for performing a synchronization.

FIG. 11B is a flowchart that shows an expansion of the step (of FIG. 11A) that determines fresh changes and proposes actions in response.

FIG. 11C is a flowchart that shows an expansion of the step (of FIG. 11B) that determines all fresh updates and adds from a particular client and proposes GUD.sub.13 Updates and GUD_Adds, respectively, in response.

FIG. 11D is a flowchart that shows an expansion of the step (of FIG. 11B) that determines all fresh deletions from a particular client and proposes a GUD_Delete in response.

FIG. 11E is a flowchart that shows an expansion of the step (of FIG. 11B) that determines all fresh changes in the GUD with respect to the client and proposes to propagate the changes in response.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

The detailed description is separated into the following chapters:

I. Introduction

II. System Hardware

III. System Software

IV. An External View: The User Interface

V. "Binary-Based" System For Automatic Synchronization of Two Or More Datasets

VI. Comparison of Timestamps From Different Datasets

VII. A Plug-In Architecture For the Synchronizer

VIII. Core of The Synchronizer

IX. Synchronization Methods

X. Additional Embodiment(s)

I. Introduction

A. Datasets, Records, and Synchronization

Datasets are collections of data. According to the present invention, the purpose of synchronizing two, or more than two, datasets is to update them as necessary with data from one another so that they contain the same or equivalent data (generally, the latest data), at least in the portions of the datasets that the user has designated for synchronization. Each dataset may be organized into individual data records. For example, a dataset having contact information may be organized into records, including a record listing a "Bill Smith's" phone numbers and addresses and another record listing a "Ted Brown's" phone numbers and addresses. In general, if records have been added to any dataset before a synchronization, then equivalent records are added to the other datasets as a result of the synchronization. Also, generally, if modifications or deletions of records have been made to one dataset before the synchronization, then equivalent modifications and deletions of corresponding records are made to the other datasets as a result of the synchronization. (The preceding discussion of synchronization according to the present invention becomes more complicated if conflicts or duplicates are present. Conflicts and duplicates are further described in later sections.)

B. Record Files, Data Types, Data Fields, etc.

In synchronizing two, or more than two, datasets, a correspondence is generally established between particular records across the datasets. For example, a contact record for "Bob Smith, of Acme Widgets" may exist in every dataset (perhaps as a result of synchronization), and these records in different datasets may correspond to one another. The records in a dataset may be of various data types, for example, a time-zone type, a contact type, a calendar-entry type, a task (or "to do"-list-entry) type, a memo type, an electronic-mail type, or other types. In general, each record may include data organized into one or more data fields. For example, a contact-type record may include data for a "last name" field, a "first name" field, a "company" field, and many other fields. For many typical data types, it is not necessary for each record of the data type to have data for every possible field. For synchronization, a correspondence is typically established between particular data fields across datasets. For example, a "title" field for contact records in one dataset may correspond to a "Job Title" field for contact records in another dataset. In general, the systems and methodologies of the present invention can be adapted to work with any one type of data, or with any multiple types of data, and with arbitrarily defined or named data fields.

Within a dataset, the records of a particular data type may further be organized into one or more groups that are here referred to as record files. Examples of record files include "Cardfiles" in Starfish's Sidekick.RTM. PIM or "folders" in Microsoft's Outlook PIM. A preferred embodiment of the invention allows the user to specify an arbitrary correspondence, or mapping, of particular record files of the same data type in different datasets to each other. For example, the user may specify that a record file named "Business Contacts" in a first dataset, a record file named "Contacts" in a second dataset, and a record file named "Customer List" in a third dataset be mapped to one another. Separately, the user may specify that only a record file named "Calendar" in the first dataset and a record file also named "Calendar" in the third dataset be mapped to each other. As demonstrated by the preceding example, a user-specified synchronization of multiple datasets by the preferred embodiment may include a number of separate synchronizations, each of which synchronizes a set of mutually-mapped, or corresponding, record files. Each synchronization of corresponding record files does not necessarily involve all of the multiple datasets. Each synchronization of corresponding record files also need not necessarily involve the same datasets as other synchronizations of other record files. For simplicity only, unless otherwise stated or unless context demands otherwise, discussion of synchronizing datasets may use language as if to assume that all datasets involved in the synchronization each contains exactly one record file that is mapped to the one record file of all other datasets involved. It is to be understood that this simplification, and other simplifications made for ease of description, are not meant to limit the scope of the invention.

C. Record Transformations

When performing synchronization, a synchronization system transforms records from one dataset's representation into another dataset's representation. For example, the system may transform from an Internet Sidekick.RTM. cardfile for business contacts into a synchronization-system-internal representation. Typically, there is a one-to-one relationship between records in the source and target datasets. If this is not the case, however, the component of the system that interacts with a non-conforming dataset (e.g., a dataset accessor, which will be further described) includes logic to handle this non-conformity.

D. Field Mapping Types and Field Conversion Types

Record transformations are a combination of field mappings and conversions from a source record to a target record. It is often the case that there are significant differences in the number, size, type and usage of fields between two datasets in a synchronization relationship. The specification of transformations generally depends on the particular datasets involved., and may be user configurable, with the synchronization system providing defaults.

In a specific embodiment, the following types of field mappings are supported.

    1. Null           Source field has no equivalent field in the target
                      dataset and is ignored during synchronization.
    2. One-to-One     Map exactly one field in the target to one field in
                      the source.
    3. One-to-Many    Map one field in the target to many fields in the
                      source, such as parse a single address line to
                      fields for number, direction, street,
                      suite/apartment, or the like.
    4. Many-to-One    Map several fields in the target to one fleld in the
                      source, such as reverse the address line mapping
                      above.

    1. Size            Source field may be larger or smaller in size than
                       the target field.
    2. Type            Data types may be different, such as float/integer,
                       character vs. numeric dates, or the like.
    3. Discrete Values A fleld's values may be limited to a known set.
                       These sets may be different from target to source
                       and may be user defined.