Method and system for offline indexing of content and classifying stored data

Information

  • Patent Grant
  • 9158835
  • Patent Number
    9,158,835
  • Date Filed
    Tuesday, May 1, 2012
    12 years ago
  • Date Issued
    Tuesday, October 13, 2015
    9 years ago
Abstract
A method and system for creating an index of content without interfering with the source of the content includes an offline content indexing system that creates an index of content from an offline copy of data. The system may associate additional properties or tags with data that are not part of traditional indexing of content, such as the time the content was last available or user attributes associated with the content. Users can search the created index to locate content that is no longer available or based on the associate attributes.
Description
BACKGROUND

Computer systems contain large amounts of data. This data includes personal data, such as financial data, customer/client/patient contact data, audio/visual data, and much more. Corporate computer systems often contain word processing documents, engineering diagrams, spreadsheets, business strategy presentations, and so on. With the proliferation of computer systems and the ease of creating content, the amount of content in an organization has expanded rapidly. Even small offices often have more information stored than any single employee can know about or locate.


Many organizations have installed content management software that actively searches for files within the organization and creates an index of the information available in each file that can be used to search for and retrieve documents based on a topic. Such content management software generally maintains on index of keywords found within the content, such as words in a document.


Creating a content index generally requires access to all of the computer systems within an organization and can put an unexpected load on already burdened systems. Some organizations defer content indexing until off hours, such as early in the morning to reduce the impact to the availability of systems. However, other operations may compete for system resources during off hours. For example, system backups are also generally scheduled for off hours. Systems may be placed in an unavailable state during times when backups are being performed, called the backup window, to prevent data from changing. For organizations with large amounts of data, any interruption, such as that from content indexing, jeopardizes the ability to complete the backup during the backup window.


Furthermore, traditional content indexing only identifies information that is currently available within the organization, and may be insufficient to find all of the data required by an organization. For example, an organization may be asked to produce files that existed during a past time period in response to a legal discovery request. Emails from five years ago or files that have been deleted or are no longer available except in offsite backup tapes may be required to answer such a request. An organization may be obligated to go through the time consuming task of retrieving all of this content and conducting a manual search for content related to the request.


There is a need for a system that overcomes the above problems, as well as providing additional benefits.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram that illustrates components of a system, in one embodiment of the invention.



FIG. 2 is a block diagram that illustrates flow of data through the system, in one embodiment.



FIG. 3 is a flow diagram that illustrates processing of a content indexing component of the system, in one embodiment.



FIG. 4 is a flow diagram that illustrates processing of an index searching component of the system, in one embodiment.



FIG. 5 illustrates a data structure containing entries of a content index, in one embodiment.





In the drawings, the same reference numbers and acronyms identify elements or acts with the same or similar functionality for ease of understanding and convenience. To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the Figure number in which that element is first introduced (e.g., element 1104 is first introduced and discussed with respect to FIG. 11).


The headings provided herein are for convenience only and do not necessarily affect the scope or meaning of the claimed invention.


Detailed Description


Overview


A method and system for creating an index of content without interfering with the source of the content including an offline content indexing system that creates an index of content from an offline copy of data is provided. In general, organizations may have a primary or production copy of source data and one or more offline or secondary copies of data. Secondary copies can be created using various storage operations such as snapshots, backups, replication, migration, and other operations. The offline content indexing system can create an index of an organization's content by examining secondary copies of the organization's data (e.g., backup files generated from routine backups performed by the organization). The offline content indexing system can index content from current secondary copies of the system as well as older offline copies that contain data that may no longer be available on the organization's network. For example, the organization may have secondary copies dating back several years that contain older data that is no longer readily available, but may still be relevant to the organization. The offline content indexing system may associate additional properties with data that are not part of traditional indexing of content, called metadata, such as the time the content was last available or user attributes associated with the content. For example, user attributes such as a project name with which a data file is associated may be stored.


Members of the organization can search the created index to locate content that is no longer readily available or based on the associated attributes. For example, a user can search for content related to a project that was cancelled a year ago. Thus, users can find additional organization data that is not available in traditional content indexing systems. Moreover, by using secondary copies, content indexing does not impact the availability of the system that is the original source of the content.


In some embodiments, members of the organization can search for content within the organization through a single, unified user interface. For example, members may search for content that originated on a variety of computer systems within the organization. Thus, users can access information from many systems within the organization and can search for content independent of the content's original source. Members may also search through multiple copies of the content, such as the original copy, a first secondary backup copy, and other secondary or auxiliary copies of the content.


Various attributes, characteristics, and identifiers (sometimes referred to as tags or data classifications) can be associated with content. The system may define certain built-in tags, such as a document title, author, last modified date, and so on. Users of the system may also define custom tags, or the system may automatically define custom tags. For example, an administrator may add tags related to groups within an enterprise, such as a tag identifying the department (e.g., finance, engineering, or legal) that created a particular content item. Individual users may also add tags relevant to that user. For example, a user might add a descriptive field, such as a programmer adding a check-in description to identify a change made to a version of a source code document. For content that is inherently unstructured or appears random outside of its intended purpose, tags are an especially effective way of ensuring that a user can later find the content. For example, United States Geological Survey (USGS) data is composed of many numbers in a file that have little significance outside of the context of a map or other associated viewer for the data. Tags allow descriptive attributes or other meaningful information to be associated with the data, for example, so that a searching user can know at a glance that particular USGS data refers to a topological map of a nearby lake. Tags may be associated with offline and online data through a metabase or other suitable data structure that stores metadata and references to the content to which the metadata applies. FIG. 5, discussed below, describes one exemplary data structure used to store user tags associated with content.


The invention will now be described with respect to various embodiments. The following description provides specific details for a thorough understanding of, and enabling description for, these embodiments of the invention. However, one skilled in the art will understand that the invention may be practiced without these details. In other instances, well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments of the invention.


The terminology used in the description presented below is intended to be interpreted in its broadest reasonable manner, even though it is being used in conjunction with a detailed description of certain specific embodiments of the invention. Certain terms may even be emphasized below; however, any terminology intended to be interpreted in any restricted manner will be overtly and specifically defined as such in this Detailed Description section.


Creation of an Offline Copy


As discussed above, the offline content indexing system may create a secondary copy, such as an offline copy, as part of an existing backup schedule performed by an organization. For example, an organization may perform weekly backups that contain a complete copy of the organization's data. It is generally not necessary for the offline content indexing system to consume any further resources of the computer systems within the organization that contain source content, since all of the needed data is typically available in the backup data files. The offline content indexing system may restore the backed up data to an intermediate computer system that is not critical to the operation of the organization, or may operate on the backup data files directly to identify and index content. The offline content indexing system may also create the offline copy using copies of data other than a traditional backup, such as a snapshot, primary copy, secondary copy, auxiliary copy, and so on.


In some embodiments, the offline content indexing system uses a change journal to create an offline copy of content. Modern operating systems often contain built in change journaling functionality that stores a journal entry whenever data is changed within a computer system. The change journal generally contains a step-by-step, sequential, or ordered log of what data changed and how the data changed that can be processed at a later time to recreate the current state of the data. The change journal may be used in conjunction with a full data backup or other data protection mechanisms. The full backup can be used to establish the state of the data at a prior point-in-time, and then the change journal entries can be used to update the state with subsequent changes.


In some embodiments, the offline content indexing system or other system uses a data snapshot to create an offline copy of content. Newer operating systems and several data storage companies offer snapshot software capable of taking a snapshot of the content currently on a computer system with minimal impact to the availability of the system. For example, the snapshot may simply note the current entry in a change journal, and keep track of subsequent change journal entries for updating the snapshot. These snapshots can be transferred from the host system and read on another, less critical system or can be used to replicate the data to a different. The offline content indexing system can then access this intermediate system to identify content and perform content indexing. Other technologies that will be recognized by those skilled in the art, such as disk imaging, mirroring, incremental backups, and so on, may be used in a manner similar to create an offline copy of data for content indexing.


In some embodiments, the offline content indexing system selects an offline copy of data for indexing among several available offline copies. For example, an organization may have several copies of data available on different types of media. The same data may be available on a tape, on a backup server, through network attached storage, or on fast mounted disk media. The offline content indexing system may take into consideration factors such as the access time of a particular media and the scheduled load on a particular offline copy when selecting a copy to use for indexing. For example, an offline copy stored on a hard drive may be preferred over a copy stored on tape due to the faster access time of the hard drive copy and the ability to randomly seek among the data rather than accessing the data sequentially. Alternatively or additionally, a backup server storing or responsible for otherwise desirable data to index scheduled to perform an intensive operation such as encrypting content may be skipped in favor of using a different server responsible for an offline copy that is not expected to be needed by other systems during the time expected to index the content. Similarly, the offline content indexing system may prefer an unencrypted offline copy over an encrypted one due to the extra effort required to decrypt the content to index it.


Indexing of Content


In some embodiments, the offline content indexing system may wait to index content until a request related to the content is received. Searches for offline content may not be as time sensitive as searches for currently available content such that the effort of indexing the content can be postponed until the content is required. For example, in a legal discovery request there may be several days or even weeks available to find content responsive to the request, such that indexing before a request is received would unnecessarily burden an organization's systems.


In some embodiments, the offline content indexing system may postpone content indexing until other storage operations have been performed. For example, one storage operation, called single instancing, may reduce or eliminate redundant files contained in backup data caused by many systems containing the same operating system or application files. By postponing content indexing until after single instancing has occurred, the offline content indexing system does not have to search as much data and may complete the indexing process sooner and with less burden to the organization's systems. A storage policy or other system parameter setting or preference may define how and when content indexing is done, and what other operations are performed before and after content indexing (e.g., indexing content after single instancing). A storage policy is a data structure that stores information about the parameters of a storage operation. For example, the storage policy may define that only some content is to be indexed, or that content indexing should occur late at night when system resources are more readily available.


In some embodiments, the offline content indexing system may update a content index according to an indexing policy. An indexing policy is a data structure that stores information about the parameters of an indexing operation. For example, an organization may create a full backup once a week, and may create an indexing policy that specifies that the index should be updated following each weekly full backup. Indexing the full backup creates a reference copy that the organization can store according to legal requirements (e.g., ten years) to respond to any compliance requests. The indexing policy may also specify that incremental updates are performed on the index based on incremental backups or other incremental data protection operations such as updates from a change journal or snapshot application. For example, incremental backups may be created that only specify the data that has changed since the last full backup, and content changes identified within the incremental backup may be used by the offline content indexing system to update the index to reflect the new state of the content. If the backup data indicates that content has been deleted, the indexed content may be retained, but may be flagged or otherwise identified as having been deleted.


Content Tags


In some embodiments, the offline content indexing system tags or otherwise identifies indexed content with additional information that may help identify the information, for example, in a search for content. For example, indexed content may be tagged with the location of the offline copy in which the information was found, such as a particular backup tape or other offline media. The system may also tag online content, such as tagging a new file with the name of its author. If the content is later deleted, the indexed content may be tagged with the date the content was deleted, the user or process that deleted the content, or the date the content was last available. Deleted content may later be restored, and the indexed content may be identified by a version number to indicate versions of the content that have been available on computing systems throughout the content's history. Other information about the content's availability may also be stored, such as whether the content is stored onsite or is archived offsite, and an estimate of the time required to retrieve the content. For example, if the content is stored offsite with an external archival company, the company may require one week's notice to retrieve the content, whereas if the content is stored on a tape within the organization, the content may be available within an hour. Other factors may also be used to provide a more accurate estimate, such as the size of the content, the offset of the content if it is on tape, and so on. During a search, the search results may indicate whether the time required to retrieve certain content would exceed a retrieval threshold. The system may also prohibit transferring content beyond a given retrieval time to ensure compliance with a policy of the organization.


In some embodiments, the offline content indexing system tags content with classifications. For example, the offline content indexing system may classify content based on the type of application typically used to process the content, such as a word processor for documents or an email client for email. Alternatively or additionally, content may be classified based on the department within the organization that generated the content, such as marketing or engineering, or based on a project that the content is associated with such as a particular case within a law firm. Content may also be classified based on access rules associated with the content. For example, some files may be classified as confidential or as only being accessible to a certain group of people within the organization. The system may identify keywords within the content and classify the content automatically based on identified keywords or other aspects of the content.


Searching


In some embodiments, the offline content indexing system searches for content based on temporal information related to the content. For example, a user may search for content available during a specified time period, such as email received during a particular month. A user may also search specifically for content that is no longer available, such as searching for files deleted from the user's primary computer system. The user may perform a search based on the attributes described above, such as a search based on the time an item was deleted, or based on a project that the item was associated with. A user may also search based on keywords associated with user attributes, such as searching for files that only an executive of the organization would have access to, searching for files accessed by a particular user, or searching for files tagged as confidential.


In some embodiments, the offline content indexing system provides search results that predict the availability of content. For example, content stored offsite may need to be located, shipped, and then loaded back into the organization's systems before it is accessible. The offline content indexing system may provide a time estimate of how soon the content could be available for searching as well as providing limited information about the content immediately based on data stored in the index. For example, the content indexing system may maintain a database of hardware and libraries of media available with the organization, as well as the current location of each of these items such that an estimate can be generated for retrieving the hardware or libraries of media. For example, certain tape libraries may be stored offsite after a specified period of time, and content stored within the tape library may take longer to retrieve than content in a tape library stored onsite in the organization. Similarly, the offline content index system may estimate that data stored on tape will take slightly longer to retrieve than data that is available through magnetic storage over the network.


Figures


Unless described otherwise below, aspects of the invention may be practiced with conventional systems. Thus, the construction and operation of the various blocks shown in FIG. 1 may be of conventional design, and need not be described in further detail herein to make and use the invention, because such blocks will be understood by those skilled in the relevant art. One skilled in the relevant art can readily make any modifications necessary to the blocks in FIG. 1 (or other embodiments or Figures) based on the detailed description provided herein.



FIG. 1 is a block diagram that illustrates components of the system, in one embodiment. The offline content indexing system 100 contains an offline copy component 110, a content indexing component 120, an index searching component 130, an index policy component 140, a data classification component 150, a single instancing component 160, an encryption component 170, and an archive retrieval component 180. The offline copy component 110 creates and identifies offline or other secondary copies of data, such as backup data, snapshots, and change journal entries. The content indexing component 120 creates and updates a content index based on offline copies of data. The index searching component 130 searches the index based on user requests to identify target content. The index policy component 140 specifies a schedule for updating the content index incrementally or refreshing the content index, such as from a full weekly backup. The data classification component 150 adds data classifications to the content index based on various classifications of the data, such as the department that created the data, and access information associated with the data. The single instancing component 160 eliminates redundant instances of information from offline copies of data to reduce the work involved in creating an index of the offline copy of the data. The encryption component 170 encrypts and decrypts data as required to permit access to the data for content indexing. The archive retrieval component 180 retrieves archived content from offsite storage, tape libraries, and other archival locations based on requests to access the content and may also provide estimates of the time required to access a particular content item.



FIG. 1 and the following discussion provide a brief, general description of a suitable computing environment in which the invention can be implemented. Although not required, aspects of the invention are described in the general context of computer-executable instructions, such as routines executed by a general-purpose computer, e.g., a server computer, wireless device or personal computer. Those skilled in the relevant art will appreciate that the invention can be practiced with other communications, data processing, or computer system configurations, including: Internet appliances, hand-held devices (including personal digital assistants (PDAs)), wearable computers, all manner of cellular or mobile phones, multi-processor systems, microprocessor-based or programmable consumer electronics, set-top boxes, network PCs, mini-computers, mainframe computers, and the like. Indeed, the terms “computer,” “host,” and “host computer” are generally used interchangeably herein, and refer to any of the above devices and systems, as well as any data processor.


Aspects of the invention can be embodied in a special purpose computer or data processor that is specifically programmed, configured, or constructed to perform one or more of the computer-executable instructions explained in detail herein. Aspects of the invention can also be practiced in distributed computing environments where tasks or modules are performed by remote processing devices, which are linked through a communications network, such as a Local Area Network (LAN), Wide Area Network (WAN), Storage Area Network (SAN), Fibre Channel, or the Internet. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.


Aspects of the invention may be stored or distributed on computer-readable media, including magnetically or optically readable computer discs, hard-wired or preprogrammed chips (e.g., EEPROM semiconductor chips), nanotechnology memory, biological memory, or other data storage media. Indeed, computer implemented instructions, data structures, screen displays, and other data under aspects of the invention may be distributed over the Internet or over other networks (including wireless networks), on a propagated signal on a propagation medium (e.g., an electromagnetic wave(s), a sound wave, etc.) over a period of time, or they may be provided on any analog or digital network (packet switched, circuit switched, or other scheme). Those skilled in the relevant art will recognize that portions of the invention reside on a server computer, while corresponding portions reside on a client computer such as a mobile or portable device, and thus, while certain hardware platforms are described herein, aspects of the invention are equally applicable to nodes on a network.



FIG. 2 is a block diagram that illustrates the flow of data through the system 100, in one embodiment. Content is initially stored on a data server 210 that may be a user computer, data warehouse server, or other information store accessible via a network. The data is accessed by a backup manager 220 to perform a regular backup of the data. The backup manager 220 may be contained within the data server 210 or may be a separate component as shown. For example, the backup manager 220 may be part of a server dedicated to managing backup or other storage operations. Backup data is stored in a backup data store 230 such as a network attached storage device, backup server, tape library, or data silo. The content indexing system 240 accesses data from the backup data store 230 to perform the functions described above. As illustrated in the diagram, because the content indexing system 240 works with an offline copy of the data, the original data server 210 is not negatively impacted by the operations of the content indexing system 240.



FIGS. 3-4 are representative flow diagrams that depict processes used in some embodiments. These flow diagrams do not show all functions or exchanges of data, but instead they provide an understanding of commands and data exchanged under the system. Those skilled in the relevant art will recognize that some functions or exchange of commands and data may be repeated, varied, omitted, or supplemented, and other (less important) aspects not shown may be readily implemented.



FIG. 3 is a flow diagram that illustrates the processing of the content indexing component 120 of the system 100, in one embodiment. The component is invoked when new content is available or additional content is ready to be added to the content index. In step 310, the component selects an offline copy of the data to be indexed. For example, the offline copy may be a backup of the data or a data snapshot. In step 320, the component identifies content within the offline copy of the data. For example, the component may identify data files such as word processing documents, spreadsheets, and presentation slides within a backup data file. In step 330, the component updates an index of content to make the content available for searching. The component may parse, process, and store the information. For example, the component may add information such as the location of the content, keywords found within the content, and other supplemental information about the content that may be helpful for locating the content during a search. After step 330, these steps conclude.



FIG. 4 is a flow diagram that illustrates the processing of the index searching component 130 of the system 100, in one embodiment. In step 410, the component receives a search request specifying criteria for finding matching target content. For example, the search request may specify one or more keywords that will be found in matching documents. The search request may also specify boolean operators, regular expressions, and other common search specifications to identify relationships and precedence between terms within the search query. In step 420, the component searches the content index to identify matching content items that are added to a set of search results. For example, the component may identify documents containing specified keywords or other criteria and add these to a list of search results. In step 425, the component generates search results based on the content identified in the content index. In step 430, the component selects the first search result. In decision step 440, if the search result indicates that the identified content is offline, then the component continues at step 450, else the component continues at step 455. For example, the content may be offline because it is on a tape that has been sent to an offsite storage location. In step 450, the component retrieves the archived content. Additionally or alternatively, the component may provide an estimate of the time required to retrieve the archived content and add this information to the selected search result. In decision step 455, if there are more search results, then the component loops to step 430 to get the next search results, else the component continues at step 460. In step 460, the component provides the search results in response to the search query. For example, the user may receive the search results through a web page that lists the search results or the search results may be provided to another component for additional processing through an application programming interface (API). The component may also perform additional processing of the search results before presenting the search results to the user. For example, the component may order the search results, rank them by retrieval time, and so forth. After step 460, these steps conclude.



FIGS. 5 illustrates some of the data structures used by the system. While the term “field” and “record” are used herein, any type of data structure can be employed. For example, relevant data can have preceding headers, or other overhead data preceding (or following) the relevant data. Alternatively, relevant data can avoid the use of any overhead data, such as headers, and simply be recognized by a certain byte or series of bytes within a serial data stream. Any number of data structures and types can be employed herein.



FIG. 5 illustrates a data structure containing entries of the content index, in one embodiment. The offline content indexing system uses this and similar data structures to provide more intelligent content indexing. For example, the offline content indexing system may index multiple copies of data and data available from the multiple copies using a secondary copy of data stored on media with a higher availability based on the location or other attributes indicated by the data structure described below. As another example, the offline content indexing system may prefer an unencrypted copy of the data to an encrypted copy to avoid wasting time unnecessarily decrypting the data. The table 500 contains a location column 510, a keywords column 520, a user tags column 530, an application column 540, and an available column 550. The table 500 contains three sample entries. The first entry 560 specifies a location to a file on the corporate intranet using a web universal resource locator (URL). The entry 560 contains keywords “finance,” “profit,” and “loss” that identify content within the file. The entry 560 contains tags added by a user that specify that the content comes from the accounting department and is confidential. The entry 560 indicates that a spreadsheet program typically consumes the content, and that the entry is immediately available. Another entry 570 specifies data stored on a local tape that is a personal email, and can be available in about an hour. Another entry 580 specifies an offsite tape that is a presentation related to a cancelled project. The entry 580 refers to offsite data that is available within one week due to the delay of retrieving the archived data from the offsite location.


Conclusion


From the foregoing, it will be appreciated that specific embodiments of the offline content indexing system have been described herein for purposes of illustration, but that various modifications may be made without deviating from the spirit and scope of the invention. For example, web pages are often unavailable and their content may change such that the offline content indexing system could be used to retrieve point in time copies of the content useful for conducting historical analysis. As another example, although files have been described, other types of content such as user settings, application data, emails, and other data objects can all be indexed by the system. Accordingly, the invention is not limited except as by the appended claims.


Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to.” The word “coupled”, as generally used herein, refers to two or more elements that may be either directly connected, or connected by way of one or more intermediate elements. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word “or” in reference to a list of two or more items, that word covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list.


The above detailed description of embodiments of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed above. While specific embodiments of, and examples for, the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. For example, while processes or blocks are presented in a given order, alternative embodiments may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified. Each of these processes or blocks may be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed in parallel, or may be performed at different times.


The teachings of the invention provided herein can be applied to other systems, not necessarily the system described above. The elements and acts of the various embodiments described above can be combined to provide further embodiments.


These and other changes can be made to the invention in light of the above Detailed Description. While the above description details certain embodiments of the invention and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the system may vary considerably in implementation details, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific embodiments disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed embodiments, but also all equivalent ways of practicing or implementing the invention under the claims.


While certain aspects of the invention are presented below in certain claim forms, the inventors contemplate the various aspects of the invention in any number of claim forms. For example, while only one aspect of the invention is recited as embodied in a computer-readable medium, other aspects may likewise be embodied in a computer-readable medium. Accordingly, the inventors reserve the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the invention.

Claims
  • 1. In a data management system residing within a private computer network, a method for indexing content, comprising: identifying a production copy having one or more production data files each having keywords and metadata, wherein the production copy is available from a production data server within the private computer network;identifying an offline copy from the private computer network, wherein the offline copy includes one or more offline data files each having keywords and metadata, andwherein the offline data files are copies of the one or more production data files, andwherein the offline copy of the one or more offline data files is stored in one or more secondary storage devices;restoring the identified offline copy to an intermediate server, wherein the intermediate server is different from the production data server andwherein the intermediate server has a higher availability than the secondary storage devices;identifying keywords from the restored offline copy on the intermediate server, wherein the identifying of the keywords is performed without use of the production data server and without accessing the production copy;creating a content index of the identified keywords on the intermediate server after the identifying of the keywords, wherein the content index classifies the identified keywords based on at least one or more user-defined classifications,wherein the user-defined classifications include administratively defined groups within an organization or organization departments,wherein the content index is in an unencrypted form even when the offline copy is encrypted, andwherein the creating of the content index is performed without affecting the production data server; andupdating the content index by associating the offline data files with the production data files.
  • 2. The method of claim 1 wherein creating or updating the content index comprises determining a state of data protection of the identified keywords.
  • 3. The method of claim 1 wherein creating or updating the content index comprises determining whether the identified keywords are encrypted.
  • 4. The method of claim 1 wherein creating or updating the content index comprises determining whether the identified keywords have associated access control information.
  • 5. The method of claim 1 wherein creating or updating the content index comprises determining at least a portion of a topology of a network in which the identified keywords is stored.
  • 6. The method of claim 1 wherein creating or updating the content index comprises determining whether the identified keywords contain one or more specified text strings or words.
  • 7. The method of claim 1 further comprising eliminating duplicate keywords within or among the offline data files.
  • 8. The method of claim 1 wherein the identifying an offline copy includes identifying a copy to use from among multiple offline copies based on a time required to access each of the multiple offline copies.
  • 9. A computer system for indexing and searching content of one or more data files, wherein the data files include keywords and metadata, and wherein the computer system is coupled to one or more secondary storage devices, the computer system comprising: a memory having instructions;a processor coupled to the memory to execute the instructions, wherein the instructions include: a production component configured to manage one or more production data files in the memory wherein each of the production data files includes keywords and metadata;an offline copy component configured to identify an offline copy of the one or more production data files after the offline copy is stored in the one or more secondary storage devices, wherein the offline copy contains one or more offline data files, andwherein the offline copy is distinguishable from a source of the one or more production data files;a restoring component configured to restore the identified offline copy to an intermediate server, wherein the intermediate server is different from the source of the one or more production data files andwherein the intermediate server has a higher availability than the secondary storage devices;an indexing component configured to create an index of keywords from the restored offline copy on the intermediate server after the offline copy component identifies the offline copy, wherein the index contains classifications of the one or more offline data files having the keywords;wherein the classifications include a level of confidentiality for the one or more offline data files having the keywords,wherein the index is in an unencrypted form even when the offline copy is encrypted, andwherein the index of the keywords is created without consuming additional resources of a system that is the source of the one or more production data files; andan index searching component configured to select certain indexed keywords based on a received search query and the classifications contained within the index.
  • 10. The computer system of claim 9 wherein the indexing component decrypts encrypted keywords.
  • 11. The computer system of claim 9 wherein the indexing component selects a copy to use for indexing from among multiple offline copies of the production data files based on a time required to access each of the multiple offline copies.
  • 12. The computer system of claim 9 wherein the indexing component selects a copy to use for indexing from among multiple offline copies of the production data files based on a server load or backup schedules associated with at least some of the multiple offline copies.
  • 13. The method of claim 1, further comprising: associating availability information with index entries, wherein the availability information is based upon a location of an offline data file on one of the secondary storage devices referenced by the index entry;searching the index for keywords;generating search results based on the searching; andranking the search results based on availability information.
  • 14. The computer system of claim 9, wherein the indexing component is further configured to associate availability information with index entries, wherein the availability information is based upon a location of an offline data file on one of the secondary storage devices referenced in the index entry.
  • 15. The method of claim 1, further comprising searching the index for information about an availability of data files, wherein the availability is based upon locations of the offline data files on one or more of the secondary storage devices, and providing search results indicating times required to access the data files based upon respective locations and availabilities of the offline data files.
  • 16. The method of claim 1, wherein the offline copy includes data files not available from mounted disk media or faster media, and wherein the offline copy is stored in an archive or secondary storage location.
  • 17. The computer system of claim 9, wherein the offline copy includes keywords not available from mounted disk media or faster media, and wherein the offline copy is stored in an archive or secondary storage location.
  • 18. The method of claim 1, wherein the identifying the keywords is performed in response to receiving a request for information related to the keywords.
  • 19. The method of claim 1, wherein the indexing the keywords is delayed until single instancing is performed on the offline copy to reduce redundant indexing of the keywords.
  • 20. A non-transitory computer-readable medium storing instructions, which when executed by at least one data processor, indexes and searches content of one or more data files, wherein the data files include keywords and metadata, comprising: identifying an offline copy of one or more production data files after the offline copy is stored in one or more secondary storage devices, wherein the offline copy contains one or more offline data files,wherein the offline copy is distinguishable from a source of the one or more production data files, andwherein each of the offline data files has keywords and metadata;restoring the identified offline copy to an intermediate server, wherein the intermediate server is different from the source of the one or more production data files andwherein the intermediate server has a higher availability than the secondary storage devices;creating an index of keywords from the restored offline copy on the intermediate server after the offline copy is identified, wherein the index contains classifications of the one or more offline data files having the keywords,wherein the classifications include a level of confidentiality for the one or more offline data files having the keywords,wherein the index is in an unencrypted form even when the offline copy is encrypted, andwherein the index of the keywords is created without consuming additional resources of a system that is the source of the one or more production data files; andselecting certain indexed keywords based on a received search query and the classifications contained within the index.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent application Ser. No. 12/058,487 now U.S. Pat. No. 8,170,995, entitled “METHOD AND SYSTEM FOR OFFLINE INDEXING OF CONTENT AND CLASSIFYING STORED DATA,” and filed on Mar. 28, 2008, which is a continuation of U.S. patent application Ser. No. 11/694,869 now U.S. Pat No. 7,882,077, entitled “METHOD AND SYSTEM FOR OFFLINE INDEXING OF CONTENT AND CLASSIFYING STORED DATA,” and filed on Mar. 30, 2007, which claims priority to U.S. Provisional Application No. 60/852,584 entitled “METHOD AND SYSTEM FOR COLLABORATIVE SEARCHING,” and filed on Oct. 17, 2006, each of which is hereby incorporated by reference.

US Referenced Citations (299)
Number Name Date Kind
4686620 Ng Aug 1987 A
4995035 Cole et al. Feb 1991 A
5005122 Griffin et al. Apr 1991 A
5093912 Dong et al. Mar 1992 A
5133065 Cheffetz et al. Jul 1992 A
5193154 Kitajima et al. Mar 1993 A
5212772 Masters May 1993 A
5226157 Nakano et al. Jul 1993 A
5239647 Anglin et al. Aug 1993 A
5241668 Eastridge et al. Aug 1993 A
5241670 Eastridge et al. Aug 1993 A
5276860 Fortier et al. Jan 1994 A
5276867 Kenley et al. Jan 1994 A
5287500 Stoppani, Jr. Feb 1994 A
5321816 Rogan et al. Jun 1994 A
5333315 Saether et al. Jul 1994 A
5347653 Flynn et al. Sep 1994 A
5410700 Fecteau et al. Apr 1995 A
5448724 Hayashi Sep 1995 A
5491810 Allen Feb 1996 A
5495607 Pisello et al. Feb 1996 A
5504873 Martin et al. Apr 1996 A
5519865 Kondo et al. May 1996 A
5544345 Carpenter et al. Aug 1996 A
5544347 Yanai et al. Aug 1996 A
5559957 Balk Sep 1996 A
5590318 Zbikowski et al. Dec 1996 A
5619644 Crockett et al. Apr 1997 A
5623679 Rivette et al. Apr 1997 A
5638509 Dunphy et al. Jun 1997 A
5673381 Huai et al. Sep 1997 A
5699361 Ding et al. Dec 1997 A
5729743 Squibb Mar 1998 A
5737747 Vishlitzky et al. Apr 1998 A
5751997 Kullick et al. May 1998 A
5758359 Saxon May 1998 A
5761677 Senator et al. Jun 1998 A
5764972 Crouse et al. Jun 1998 A
5778395 Whiting et al. Jul 1998 A
5812398 Nielsen Sep 1998 A
5813009 Johnson et al. Sep 1998 A
5813017 Morris Sep 1998 A
5829046 Tzelnic et al. Oct 1998 A
5832510 Ito et al. Nov 1998 A
5875478 Blumenau Feb 1999 A
5887134 Ebrahim Mar 1999 A
5892917 Myerson Apr 1999 A
5901327 Ofek May 1999 A
5907621 Bachman et al. May 1999 A
5918232 Pouschine et al. Jun 1999 A
5924102 Perks Jul 1999 A
5950205 Aviani, Jr. Sep 1999 A
5953721 Doi et al. Sep 1999 A
5974563 Beeler, Jr. Oct 1999 A
6006225 Bowman et al. Dec 1999 A
6021415 Cannon et al. Feb 2000 A
6023710 Steiner et al. Feb 2000 A
6026414 Anglin Feb 2000 A
6052735 Ulrich et al. Apr 2000 A
6061692 Thomas et al. May 2000 A
6076148 Kedem Jun 2000 A
6088697 Crockett et al. Jul 2000 A
6092062 Lohman et al. Jul 2000 A
6094416 Ying Jul 2000 A
6131095 Low et al. Oct 2000 A
6131190 Sidwell Oct 2000 A
6148412 Cannon et al. Nov 2000 A
6154787 Urevig et al. Nov 2000 A
6154852 Amundson et al. Nov 2000 A
6161111 Mutalik et al. Dec 2000 A
6167402 Yeager Dec 2000 A
6175829 Li et al. Jan 2001 B1
6212512 Barney et al. Apr 2001 B1
6260069 Anglin Jul 2001 B1
6269431 Dunham Jul 2001 B1
6275953 Vahalia et al. Aug 2001 B1
6301592 Aoyama et al. Oct 2001 B1
6324581 Xu et al. Nov 2001 B1
6328766 Long Dec 2001 B1
6330570 Crighton Dec 2001 B1
6330642 Carteau Dec 2001 B1
6343324 Hubis et al. Jan 2002 B1
RE37601 Eastridge et al. Mar 2002 E
6356801 Goodman et al. Mar 2002 B1
6374336 Peters et al. Apr 2002 B1
6389432 Pothapragada et al. May 2002 B1
6418478 Ignatius et al. Jul 2002 B1
6421683 Lamburt Jul 2002 B1
6421711 Blumenau et al. Jul 2002 B1
6421779 Kuroda et al. Jul 2002 B1
6430575 Dourish et al. Aug 2002 B1
6438586 Hass et al. Aug 2002 B1
6487561 Ofek et al. Nov 2002 B1
6487644 Huebsch et al. Nov 2002 B1
6499026 Rivette et al. Dec 2002 B1
6507852 Dempsey et al. Jan 2003 B1
6516314 Birkler et al. Feb 2003 B1
6519679 Devireddy et al. Feb 2003 B2
6538669 Lagueux, Jr. et al. Mar 2003 B1
6542909 Tamer et al. Apr 2003 B1
6542972 Ignatius et al. Apr 2003 B2
6564228 O'Connor May 2003 B1
6581143 Gagne et al. Jun 2003 B2
6625623 Midgley et al. Sep 2003 B1
6647396 Parnell et al. Nov 2003 B2
6658436 Oshinsky et al. Dec 2003 B2
6658526 Nguyen et al. Dec 2003 B2
6732124 Koseki et al. May 2004 B1
6763351 Subramaniam et al. Jul 2004 B1
6772164 Reinhardt Aug 2004 B2
6775790 Reuter et al. Aug 2004 B2
6785864 Te et al. Aug 2004 B1
6834329 Sasaki et al. Dec 2004 B2
6836779 Poulin Dec 2004 B2
6847984 Midgley et al. Jan 2005 B1
6857053 Bolik et al. Feb 2005 B2
6871163 Hiller et al. Mar 2005 B2
6886020 Zahavi et al. Apr 2005 B1
6947935 Horvitz et al. Sep 2005 B1
6983322 Tripp et al. Jan 2006 B1
6996616 Leighton et al. Feb 2006 B1
7003519 Biettron et al. Feb 2006 B1
7035880 Crescenti et al. Apr 2006 B1
7047236 Conroy et al. May 2006 B2
7085787 Beier et al. Aug 2006 B2
7103740 Colgrove et al. Sep 2006 B1
7130860 Pachet et al. Oct 2006 B2
7130970 Devassy et al. Oct 2006 B2
7149750 Chadwick Dec 2006 B2
7165082 DeVos Jan 2007 B1
7167895 Connelly Jan 2007 B1
7171619 Bianco Jan 2007 B1
7181444 Porter et al. Feb 2007 B2
7194454 Hansen et al. Mar 2007 B2
7197502 Feinsmith Mar 2007 B2
7200726 Gole et al. Apr 2007 B1
7240100 Wein et al. Jul 2007 B1
7246207 Kottomtharayil et al. Jul 2007 B2
7246211 Beloussov et al. Jul 2007 B1
7266546 Son Sep 2007 B2
7269612 Devarakonda et al. Sep 2007 B2
7272606 Borthakur et al. Sep 2007 B2
7330997 Odom Feb 2008 B1
7343365 Farnham et al. Mar 2008 B2
7346623 Prahlad et al. Mar 2008 B2
7346676 Swildens et al. Mar 2008 B1
7356657 Mikami Apr 2008 B2
7356660 Matsunami et al. Apr 2008 B2
7359917 Winter et al. Apr 2008 B2
7366859 Per et al. Apr 2008 B2
7386663 Cousins Jun 2008 B2
7395282 Crescenti et al. Jul 2008 B1
7430587 Malone et al. Sep 2008 B2
7433301 Akahane et al. Oct 2008 B2
7440966 Adkins et al. Oct 2008 B2
7440984 Augenstein et al. Oct 2008 B2
7454569 Kavuri et al. Nov 2008 B2
7496589 Jain et al. Feb 2009 B1
7500150 Sharma et al. Mar 2009 B2
7509316 Greenblatt et al. Mar 2009 B2
7512601 Cucerzan et al. Mar 2009 B2
7512814 Chen et al. Mar 2009 B2
7529748 Wen et al. May 2009 B2
7532340 Koppich et al. May 2009 B2
7533103 Brendle et al. May 2009 B2
7533181 Dawson et al. May 2009 B2
7533230 Glover et al. May 2009 B2
7583861 Hanna et al. Sep 2009 B2
7584227 Gokhale et al. Sep 2009 B2
7590997 Diaz Perez Sep 2009 B2
7613728 Png et al. Nov 2009 B2
7613752 Prahlad et al. Nov 2009 B2
7617541 Plotkin et al. Nov 2009 B2
7620710 Kottomtharayil et al. Nov 2009 B2
7624443 Kramer et al. Nov 2009 B2
7627598 Burke Dec 2009 B1
7627617 Kavuri et al. Dec 2009 B2
7631151 Prahlad et al. Dec 2009 B2
7634478 Yang et al. Dec 2009 B2
7657550 Prahlad et al. Feb 2010 B2
7660800 Prahlad et al. Feb 2010 B2
7660807 Prahlad et al. Feb 2010 B2
7668798 Scanlon et al. Feb 2010 B2
7668884 Prahlad et al. Feb 2010 B2
7672962 Arrouye et al. Mar 2010 B2
7693856 Arrouye et al. Apr 2010 B2
7707178 Prahlad et al. Apr 2010 B2
7711700 Prahlad et al. May 2010 B2
7716171 Kryger May 2010 B2
7716191 Blumenau et al. May 2010 B2
7720801 Chen May 2010 B2
7725605 Palmeri et al. May 2010 B2
7725671 Prahlad et al. May 2010 B2
7734593 Prahlad et al. Jun 2010 B2
7734669 Kottomtharayil et al. Jun 2010 B2
7734715 Hyakutake et al. Jun 2010 B2
7747579 Prahlad et al. Jun 2010 B2
7756837 Williams et al. Jul 2010 B2
7801864 Prahlad et al. Sep 2010 B2
7818215 King et al. Oct 2010 B2
7822749 Prahlad et al. Oct 2010 B2
7831553 Prahlad et al. Nov 2010 B2
7831622 Prahlad et al. Nov 2010 B2
7831795 Prahlad et al. Nov 2010 B2
7840537 Gokhale et al. Nov 2010 B2
7840619 Horn Nov 2010 B2
7841011 Manson et al. Nov 2010 B2
7849059 Prahlad et al. Dec 2010 B2
7882077 Gokhale et al. Feb 2011 B2
7882098 Prahlad et al. Feb 2011 B2
7890467 Watanabe et al. Feb 2011 B2
7890469 Maionchi et al. Feb 2011 B1
7925856 Greene Apr 2011 B1
7933920 Kojima et al. Apr 2011 B2
7937365 Prahlad et al. May 2011 B2
7937393 Prahlad et al. May 2011 B2
7962709 Agrawal Jun 2011 B2
7966495 Ackerman et al. Jun 2011 B2
8010769 Prahlad et al. Aug 2011 B2
8037031 Gokhale et al. Oct 2011 B2
8051045 Vogler Nov 2011 B2
8051095 Prahlad et al. Nov 2011 B2
8055650 Scanlon et al. Nov 2011 B2
8055745 Atluri Nov 2011 B2
8117196 Jones et al. Feb 2012 B2
8229954 Kottomtharayil et al. Jul 2012 B2
20010047365 Yonaitis Nov 2001 A1
20020049626 Mathias et al. Apr 2002 A1
20020069324 Gerasimov et al. Jun 2002 A1
20020087550 Carlyle et al. Jul 2002 A1
20020147734 Shoup et al. Oct 2002 A1
20020161753 Inaba et al. Oct 2002 A1
20030018607 Lennon et al. Jan 2003 A1
20030046313 Leung et al. Mar 2003 A1
20030101183 Kabra et al. May 2003 A1
20030130993 Mendelevitch et al. Jul 2003 A1
20030149739 Adams et al. Aug 2003 A1
20030182583 Turco Sep 2003 A1
20030196052 Bolik et al. Oct 2003 A1
20040015514 Melton et al. Jan 2004 A1
20040254919 Giuseppini Dec 2004 A1
20040260678 Verbowski et al. Dec 2004 A1
20040260973 Michelman Dec 2004 A1
20050010588 Zalewski et al. Jan 2005 A1
20050050075 Okamoto et al. Mar 2005 A1
20050055352 White et al. Mar 2005 A1
20050055386 Tosey Mar 2005 A1
20050086231 Moore Apr 2005 A1
20050114381 Borthakur et al. May 2005 A1
20050154695 Gonzalez et al. Jul 2005 A1
20050187937 Kawabe et al. Aug 2005 A1
20050188248 O'Brien et al. Aug 2005 A1
20050216453 Sasaki et al. Sep 2005 A1
20050228794 Navas et al. Oct 2005 A1
20050262097 Sim-Tang et al. Nov 2005 A1
20060004820 Claudatos et al. Jan 2006 A1
20060015524 Gardiner et al. Jan 2006 A1
20060224846 Amarendran et al. Oct 2006 A1
20060230082 Jasrasaria Oct 2006 A1
20060248055 Haslam et al. Nov 2006 A1
20060259468 Brooks et al. Nov 2006 A1
20060259527 Devarakonda et al. Nov 2006 A1
20060277154 Lunt et al. Dec 2006 A1
20070033191 Hornkvist et al. Feb 2007 A1
20070043956 El Far et al. Feb 2007 A1
20070067304 Ives Mar 2007 A1
20070100867 Celik et al. May 2007 A1
20070100913 Sumner et al. May 2007 A1
20070185926 Prahlad et al. Aug 2007 A1
20070192385 Prahlad et al. Aug 2007 A1
20070203938 Prahlad et al. Aug 2007 A1
20070282680 Davis et al. Dec 2007 A1
20070288536 Sen et al. Dec 2007 A1
20080059495 Kiessig et al. Mar 2008 A1
20080059515 Fulton Mar 2008 A1
20080077594 Ota Mar 2008 A1
20080091747 Prahlad et al. Apr 2008 A1
20080183662 Reed et al. Jul 2008 A1
20080228771 Prahlad et al. Sep 2008 A1
20080229037 Bunte et al. Sep 2008 A1
20080294605 Prahlad et al. Nov 2008 A1
20090172333 Marcu et al. Jul 2009 A1
20090287665 Prahlad et al. Nov 2009 A1
20090319534 Gokhale Dec 2009 A1
20090319585 Gokhale Dec 2009 A1
20100057870 Ahn et al. Mar 2010 A1
20100082672 Kottomtharayil et al. Apr 2010 A1
20100179941 Agrawal et al. Jul 2010 A1
20100205150 Prahlad et al. Aug 2010 A1
20100250549 Muller et al. Sep 2010 A1
20100299490 Attarde et al. Nov 2010 A1
20110161327 Pawar Jun 2011 A1
20110178986 Prahlad et al. Jul 2011 A1
20110179039 Prahlad et al. Jul 2011 A1
20110181383 Lotfi et al. Jul 2011 A1
20110276664 Prahlad et al. Nov 2011 A1
20130110790 Matsumoto et al. May 2013 A1
20130151640 Ahn et al. Jun 2013 A1
20130198221 Roark et al. Aug 2013 A1
Foreign Referenced Citations (21)
Number Date Country
0259912 Mar 1988 EP
0405926 Jan 1991 EP
0467546 Jan 1992 EP
0774715 May 1997 EP
0809184 Nov 1997 EP
0899662 Mar 1999 EP
0981090 Feb 2000 EP
1174795 Jan 2002 EP
WO-9412944 Jun 1994 WO
WO-9513580 May 1995 WO
WO-9912098 Mar 1999 WO
WO-9914692 Mar 1999 WO
WO-0106368 Jan 2001 WO
WO-0193537 Dec 2001 WO
WO-03060774 Jul 2003 WO
WO-2004010375 Jun 2004 WO
WO-2004063863 Mar 2005 WO
WO-2005055093 Jun 2005 WO
WO-2007062254 May 2007 WO
WO-2007062429 May 2007 WO
WO-2008049023 Apr 2008 WO
Non-Patent Literature Citations (36)
Entry
U.S. Appl. No. 13/076,714, filed Mar. 31, 2011, Prahlad et al.
“Text Figures”, retrieved from http://www.microsoft.com/msj/1198.ntfs/ntfstextfigs.htm on Nov. 10, 2005, 7 pages.
Armstead et al., “Implementation of a Campus-wide Distributed Mass Storage Service: The Dream vs. Reality,” IEEE, Sep. 11-14, 1995, pp. 190-199.
Arneson, “Mass Storage Archiving in Network Environments,” Digest of Papers, Ninth IEEE Symposium on Mass Storage Systems, Oct. 31, 1988-Nov. 3, 1988, pp. 45-50, Monterey, CA.
Arneson, David A., “Development of Omniserver,” Control Data Corporation, Tenth IEEE Symposium on Mass Storage Systems, May 1990, ‘Crisis in Mass Storage’ Digest of Papers, pp. 88-93, Monterey, CA.
Bowman et al. “Harvest: A Scalable, Customizable Discovery and Access System,” Department of Computer Science, University of Colorado—Boulder, Revised Mar. 1995, 29 pages.
Brad O'Neill, “New Tools to Classify Data,” Storage Magazine, Aug. 2005, 4 pages.
Cabrera et al., “ADSM: A Multi-Platform, Scalable, Backup and Archive Mass Storage System,” Digest of Papers, Compcon '95, Proceedings of the 40th IEEE Computer Society International Conference, Mar. 5-9, 1995, pp. 420-427, San Francisco, CA.
Eitel, “Backup and Storage Management in Distributed Heterogeneous Environments,” IEEE, Jun. 12-16, 1994, pp. 124-126.
EMC Corporation, “Today's Choices for Business Continuity,” 2004, 12 pages.
Farley, M., “Storage Network Fundamentals Network Backup: The Foundation of Storage Management, Data Management,” Storage Networking Fundamentals: an Introduction to Storage Devices, Subsystems, Applications, Management, and Filing [File] Systems, Cisco Press, Jan. 1, 2005, 9 pages.
International Search Report and Written Opinion for International Application No. PCT/US07/81681, Mail Date Nov. 13, 2009, 8 pages.
Jander, M., “Launching Storage-Area Net,” Data Communications, US, McGraw Hill, NY, vol. 27, No. 4 (Mar. 21, 1998), pp. 64-72.
Jason Gait, “The Optical File Cabinet: A Random-Access File System for Write-Once Optical Disks,” IEEE Computer, vol. 21, No. 6, pp. 11-22 (Jun. 1988).
Jeffrey Cooperstein and Jeffrey Richter, “Keeping an Eye on Your NTFS Drives, Part II: Building a Change Journal Application,” Microsoft Systems Journal, Oct. 1999, 14 pages.
Jeffrey Cooperstein and Jeffrey Richter, “Keeping an Eye on Your NTFS Drives: the Windows 2000 Change Journal Explained,” Microsoft Systems Journal, Sep. 1999, 17 pages.
Jeffrey Richter and Luis Felipe Cabrera, “A File System for the 21st Century: Previewing the Windows NT 5.0 File System,” and attached text figures, Microsoft Systems Journal, Nov. 1998, 24 pages.
Karl Langdon and John Merryman, “Data Classification: Getting Started,” Storage Magazine, Jul. 2005, 3 pages.
Manber et al., “WebGlimpse—Combining Browsing and Searching,” 1997 Usenix Technical Conference, Jan. 1997, 12 pages.
Microsoft Developer Network, “GetFileAttributes,” online library article, [accessed on Nov. 10, 2005], 3 pages.
Microsoft Developer Network, “GetFileAttributesEx,” online library article, [accessed on Nov. 10, 2005], 2 pages.
Microsoft Developer Network, “Win32—File—Attribute—Data,” online library article, [accessed on Nov. 10, 2005], 3 pages.
Partial International Search Results, mailed May 25, 2007, International Application No. PCT/US2006/045556, 2 pages.
PCT International Search Report and Written Opinion for International Application No. PCT/US07/81681, Mail Date Oct. 20, 2008, 11 pages.
Rosenblum et al., “The Design and Implementation of a Log-Structured File System,” Operating Systems Review SIGOPS, vol. 25, No. 5, New York, US, pp. 1-15 (May 1991).
Supplementary European Search Report for European Application No. EP07844364, Mail Date Apr. 19, 2011, 9 pages.
U.S. Appl. No. 13/538,862, filed Jun. 29, 2012, Prahlad et al.
U.S. Appl. No. 13/616,197, filed Sep. 14, 2012, Prahlad et al.
“Titus Labs—Announces Document Classification for Microsoft Word” Nov. 3, 2005, XP55034835, available at http://web.archive.org/web/20051126093136/http://www.titus-labs.com/about/DocClassRelease.html, 1 page.
Titus Labs Document Classification V1.1 for Microsoft Word—Document Policy Enforcement, available at: <http://web.archive.org/web/20060104112621/www.titus-labs.com/includes/PDF/DocClassDataSheet.pdf>, Nov. 3, 2005, 2 pages.
U.S. Appl. No. 13/894,010, filed May 14, 2013, Pawar.
Bhagwan, R. et al. “Total Recall: System Support for Automated Availability Management,” Proceedings of the 1st Conference on Symposium on Networked Systems Design and Implementation, vol. 1, Mar. 3, 2004, XP055057350, Berkeley, CA, 14 pages.
Extended European Search Report for European Application No. EP11003795, Mail Date Nov. 21, 2012, 20 pages.
Harrison, CDIA Training & Test Preparation Guide 2000, Specialized Solutions, 3 pages.
Quick Reference Guide for West and East [date unknown, but verified as of Sep. 13, 2007], Search and Information Resource Administration, 2 pages.
User's Manual for the Examiners Automated Search Tool (East) Jul. 22, 1999, Version 1.0, 179 pages.
Related Publications (1)
Number Date Country
20120215745 A1 Aug 2012 US
Provisional Applications (1)
Number Date Country
60852584 Oct 2006 US
Continuations (2)
Number Date Country
Parent 12058487 Mar 2008 US
Child 13461434 US
Parent 11694869 Mar 2007 US
Child 12058487 US