Abstract:
A method of viewing information associated with data in a spreadsheet, includes providing a document including data and information associated with the data, parsing the document to retrieve the associated information, processing the associated information to break the associated information down into at least one sentence, categorizing the at least one sentence to determine whether the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data, assigning an association strength to the categorized at least one sentence, the association strength indicating a likelihood that the categorized at least one sentence actually corresponds to the at least one category in the taxonomy, filtering the at least one categorized sentence based on the association strength to determine whether to match the categorized at least one sentence with the at least one category in the taxonomy and outputting only the categorized at least one sentence matched with the at least one category in the taxonomy.

Description:
REFERENCE TO RELATED APPLICATION  
       [0001]     The present disclosure is a continuation-in-part of co-pending U.S. patent application Ser. No. 11/397,105 filed Apr. 4, 2006 which is a continuation-in-part of co-pending U.S. patent application Ser. No. 11/214,083 filed Aug. 29, 2005, the entire contents of each of which are herein incorporated by reference. 
     
    
     BACKGROUND  
       [0002]     1. Technical Field  
         [0003]     The present disclosure relates generally to financial data and, more particularly, to a system and method for rendering data.  
         [0004]     2. Description of the Related Art  
         [0005]     The Sarbanes-Oxley Act (the Act) is legislation that affects corporate governance, financial disclosure and the practice of public accounting. The Act was signed into law largely in response to numerous corporate accounting scandals. The Act requires executives, boards of directors and auditors to take precise measures to bring about greater corporate accountability and transparency.  
         [0006]     In the electronic format, a file containing a financial statement is usually not coded to indicate the type of information represented by each line or column of text. In order to have a computer extract the desired information from the file, the content of the file has to be identified. That is, the various tables in the file have to be recognized and the content within each table has to be parsed and broken down to their constituent parts.  
         [0007]     Once the data is recognized and broken down, it can be normalized and manipulated. For example, the normalized data can be placed in a spreadsheet program or a database program. The performance of the company can then be illustrated and analyzed by various mathematical, statistical, or financial models within the functional capabilities of the spreadsheet program. The relationship between various financial statement entries can be compared and hypothetical situations can be generated and tested. Furthermore, industry analysis can be performed as well by gathering and collating data from the financial statements of several companies. Thus, there is great incentive for identifying and parsing the content of a file containing a financial statement.  
         [0008]     A spreadsheet is a programming tool specifically adapted to the manipulation of financial data and provides a rich programming and modeling environment using a number of tools and macros that are familiar to most users of financial data. The cells of a spreadsheet can be used to store both data and formulas for manipulating data. And, as spreadsheet functionality is improved, users familiar with the capabilities of their particular spreadsheet program become dependent on those functions. An example of the improved functionality of spreadsheet programs, U.S. Pat. No. 6,779,151 to Cahill et al., incorporated by reference herein for all purposes, provides for a spreadsheet program that will recognize new object data types, i.e., those in addition to the typical spreadsheet data types such as numbers, texts, date, Boolean and error, and store the new object data types in the cells of the spreadsheet. There have also been inventions developed to parse data and render such data in a spreadsheet, such as U.S. Pat. No. 5,893,131 to Kornfeld for a method and apparatus for parsing data, incorporated by reference herein for all purposes, and U.S. application Ser. No. 086522, U.S. publication Ser. No. 20030037038 to Block et al. for a method for adding metadata to data, incorporated by reference herein for all purposes.  
         [0009]     In the past, in order to obtain the utility provided by a spreadsheet with financial data such as that supplied to the U.S. Securities and Exchange Commission (SEC), a spreadsheet user would “copy and paste” the relevant information from a document from a data provider into the spreadsheet for further use and analysis. Not only was this process cumbersome and time consuming, but it also allows the introduction of data errors into the spreadsheet. In addition, there was no method for reversing the process from the spreadsheet program to the online data provider.  
         [0010]     To facilitate the flow of corporate financial information from public companies to analysts, regulators and investors, Extensible Business Reporting Language (XBRL) was developed. XBRL is a meta-data standard or data that describes data. That is, an XBRL tag associated with a number or text describes the meaning of the data. For example, assume that a company announces that it produced $5.7 Mil. in 2003. With no context, it is difficult to determine what the number in this statement relates to. It could mean, for example, the company&#39;s revenue, gross margin, executive salaries, etc. However, XBRL can be used to place a tag indicating that the 5.7 Mil. represents revenue for the year 2003.  
         [0011]     XBRL is quickly becoming a global standard for the preparation of financial information for facilitating its transfer and ease of usability. XBRL tags financial information so that it can be tracked from interactions with vendors, etc. and so that it can readily be used in reports for operating divisions of a company, consolidated earnings releases, etc. Systems have been developed for converting financial documents into XBRL. For example, Rivet Software has developed a system called “Dragon Tag” that is used for this purpose. There are also other companies that provide XBRL tagged data. For example, Edgar Online provides XBRL-tagged SEC filing data and OneSource provides access to U.K. financial data in XBRL.  
         [0012]     One goal of the push to derive such a standard for financial information is to enable an entire new generation of Web services that will make it easier for financial analysts and regulators to locate problems in financial data, executives to compare their company to competitors, and analysts to identify performing stocks.  
         [0013]     Documents such as financial documents often include information besides that in the main body of the document. This information is referred to herein as “associated information”. This associated information may include, for example, footnotes, head notes, management discussion, etc. Although the associated information may not be included in the main body of the financial document, it may nevertheless contain important information that can be useful when evaluating the financials of a company.  
         [0014]     It would be beneficial to enable users to view the associated information along with the information in the main body of a document so that the associated information can be viewed in context.  
       SUMMARY  
       [0015]     This application describes tools (in the form of methodologies, apparatuses, and systems) for viewing information associated with data in a spreadsheet. The tools may be embodied in one or more computer programs stored on a computer readable medium or program storage device and/or transmitted in the form of a computer data signal in one or more segments via a computer network or other transmission medium.  
         [0016]     A method of viewing information associated with data in a spreadsheet, includes providing a document including data and information associated with the data, parsing the document to retrieve the associated information, processing the associated information to break the associated information down into at least one sentence, categorizing the at least one sentence to determine whether the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data, assigning an association strength to the categorized at least one sentence, the association strength indicating a likelihood that the categorized at least one sentence actually corresponds to the at least one category in the taxonomy, filtering the at least one categorized sentence based on the association strength to determine whether to match the categorized at least one sentence with the at least one category in the taxonomy and outputting only the categorized at least one sentence matched with the at least one category in the taxonomy.  
         [0017]     A system for viewing information associated with data in a spreadsheet, includes a module for providing a document including data and information associated with the data, a module for parsing the document to retrieve the associated information, a module for processing the associated information to break the associated information down into at least one sentence, a module for categorizing the at least one sentence to determine whether the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data, a module for assigning an association strength to the categorized at least one sentence, the association strength indicating a likelihood that the categorized at least one sentence actually corresponds to the at least one category in the taxonomy, a module for filtering the at least one categorized sentence based on the association strength to determine whether to match the categorized at least one sentence with the at least one category in the taxonomy and a module for outputting only the categorized at least one sentence matched with the at least one category in the taxonomy.  
         [0018]     A computer recording medium including computer executable code for viewing information associated with data in a spreadsheet. The computer executable code includes code for providing a document including data and information associated with the data, code for parsing the document to retrieve the associated information, code for processing the associated information to break the associated information down into at least one sentence, code for categorizing the at least one sentence to determine whether the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data, code for assigning an association strength to the categorized at least one sentence, the association strength indicating a likelihood that the categorized at least one sentence actually corresponds to the at least one category in the taxonomy, code for filtering the at least one categorized sentence based on the association strength to determine whether to match the categorized at least one sentence with the at least one category in the taxonomy and code for outputting only the categorized at least one sentence matched with the at least one category in the taxonomy.  
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0019]     A more complete appreciation of the present disclosure and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:  
         [0020]      FIG. 1  is a block diagram of an exemplary computer system capable of implementing the method and system of the present disclosure;  
         [0021]      FIG. 2A  is a block diagram of an overall architecture used for implementing embodiments of the present disclosure;  
         [0022]      FIG. 2B  is a flow chart for describing operation of a financial data system according to embodiments of the present disclosure;  
         [0023]      FIG. 2C  is a Dialog box of the XBRL Properties of a cell in a spreadsheet selected by a user;  
         [0024]      FIG. 3  is a screen shot of a spreadsheet including a main menu according to embodiments of the present disclosure;  
         [0025]      FIGS. 4A-4F ,  5  and  6  are screen shots for describing aspects of a Fundamental Data Wizard according to embodiments of the present disclosure;  
         [0026]      FIGS. 7 and 8 A- 8 D are screen shots for describing aspects of a Market Data Wizard according to embodiments of the present disclosure;  
         [0027]      FIG. 9  is a flow chart for describing a method for entering a function call directly into a cell of a spreadsheet;  
         [0028]      FIG. 10A and 10B  are screen shots for describing aspects of a Fundamental Data Function Builder according to embodiments of the present disclosure;  
         [0029]      FIGS. 11 and 12  are screen shots for describing aspects of a Market Data Function Builder according to embodiments of the present disclosure;  
         [0030]      FIGS. 13A and 13B  are screen shots for describing a link back feature according to embodiments of the present disclosure;  
         [0031]      FIG. 14  is a screen shot for describing how multiple company financials can be displayed in a spreadsheet at the same time;  
         [0032]      FIG. 15  is a view of portion of a footnote section of a financial document;  
         [0033]      FIG. 16  is view of a list of categories;  
         [0034]      FIG. 17  is a block diagram for describing an associated information processing system according to an embodiment of the present disclosure;  
         [0035]      FIGS. 18A and 18B  are flow charts for describing operation of an associated information processing system according to an embodiment of the present disclosure;  
         [0036]      FIG. 19  is a table of sentences with category labels and association strengths for describing aspects of embodiments of the present disclosure;  
         [0037]      FIG. 20  is a screen shot of information displayed to a user according to an embodiment of the present disclosure; and  
         [0038]      FIG. 21  is a screen shot of associated footnote information displayed to a user according to an embodiment of the present disclosure;  
         [0039]      FIG. 22  is a screen shot showing a drop down menu according to an embodiment of the present disclosure;  
         [0040]      FIG. 23  is a screen shot of extracted related notes according to an embodiment of the present disclosure; and  
         [0041]      FIG. 24  is a screen shot of selected related note information displayed in context according to an embodiment of the present disclosure. 
     
    
     DETAILED DESCRIPTION  
       [0042]     The following exemplary embodiments are set forth to aid in an understanding of the subject matter of this disclosure, but are not intended, and may not be construed, to limit in any way the claims which follow thereafter. Therefore, while specific terminology is employed for the sake of clarity in describing some exemplary embodiments, the present disclosure is not intended to be limited to the specific terminology so selected, and it is to be understood that each specific element includes all technical equivalents which operate in a similar manner.  
         [0043]      FIG. 1  shows an example of a computer system  100  which may implement the method and system of the present disclosure. The system and method of the present disclosure may be implemented in the form of a software application running on a computer system, for example, a mainframe, personal computer (PC), handheld computer, server, etc. The software application may be stored on a recording media locally accessible by the computer system, for example, floppy disk, compact disk, hard disk, etc., or may be remote from the computer system and accessible via a hard wired or wireless connection to a network, for example, a local area network, or the Internet.  
         [0044]     The computer system  100  can include a central processing unit (CPU)  102 , program and data storage devices  104 , a printer interface  106 , a display unit  108 , a (LAN) local area network data transmission controller  110 , a LAN interface  112 , a network controller  114 , an internal bus  116 , and one or more input devices  118  (for example, a keyboard, mouse etc.). As shown, the system  100  may be connected to a database  120 , via a link  122 .  
         [0045]     The computer system  100  is merely exemplary. The specific embodiments described herein are illustrative, computer system(s) as referred to herein may include(s) individual computers, servers, computing resources, networks, etc., and many variations can be introduced on these embodiments without departing from the spirit of the disclosure or from the scope of the appended claims.  
         [0046]     According to an embodiment of the present disclosure, financial documents in XBRL are rendered into a spreadsheet, preferably Microsoft® Excel. According to an embodiment of the present disclosure, the present system is delivered through a Dynamic Link Library (DLL) and is registered upon installation as a spreadsheet add-in. Although Microsoft Excel is used herein as an example of a spreadsheet program, other spreadsheet programs may be utilized in its place. In addition, according to another embodiment of the present disclosure, the present system may be compiled as part of the actual spreadsheet program and is not a part of the DLL.  
         [0047]     An overall architecture of a system for rendering financial documents into a spreadsheet is shown in  FIG. 2A . According to this embodiment of the present disclosure, the present system is an add-in to the spreadsheet  26 . The add-in will be referred to herein as financial data system  24  or simply system  24 . Database  20  may consist of one or more databases and/or other types of sources of business and financial information. For example, database  20  may include source financial disclosure documents filed with the Securities and Exchange Commission. Database  20  may also include other types of source documents from which business and financial information can be obtained. An online financial data web service  22  such as, for example, the service offered by Edgar Online, Inc., is accessed by the present system  24  via the Internet  28 . In response to a query generated by system  24  for specific financial data, financial data online web service  22  will access the appropriate data from database  20  and return the data to system  24 . For example, according to an embodiment of the present disclosure, an XML response including an XBRL instance document is returned to system  24 . Utilizing the instance document and taxonomies  25  locally or remotely available to it, system  24  then populates spreadsheet  26  as appropriate. This bi-directional compatibility with standard XML and XBRL taxonomies allows the direct use of the functional capabilities of the spreadsheet program such as custom macros, existing models and work sheet.  
         [0048]     Because not all companies use the same terminology, the taxonomies used by standards organizations also include synonyms and alternative phrases that have the same meaning. For example synonyms for Sales could include “Revenues” or “Fees”. Cost of Goods Sold might be “Cost of Goods” or “Cost of Sales”. Taxonomies and their extensions are used to define the Information Labels. For example in a financial report, the label &lt;Sales&gt; followed by a numerical value indicates that the numerical value relates to company&#39;s Sales. &lt;Cost of Goods Sold&gt; followed by a numerical value indicates that the value represents the company&#39;s Cost of Goods Sold. Since Gross Profit is Sales minus Cost of Goods Sold, computers could access third party reports that show these values and easily calculate the Gross Profit with a simple rule that says &lt;Sales&gt;&lt;minus&gt;&lt;Cost of Goods Sold&gt;=&lt;Gross Profit&gt;.  
         [0049]     Embodiments of the present disclosure thus provide methods and systems for automating entry of XML and XBRL compliant data into non-XML or non-XBRL compliant programs or applications. In addition to rendering the XML and XBRL compliant data into a spreadsheet compatible format, the present system also provides for transmitting data in a format compliant with the Simple Object Access Protocol (SOAP). Briefly, (SOAP) is a way for a program running in one kind of operating system to communicate with a program in the same or a different kind of operating system by using the Internet&#39;s HTTP and XML as the mechanisms for information exchange.  
         [0050]      FIG. 2B  is a flow chart for describing steps involved in invoking processes according to embodiments of the present disclosure. From the spreadsheet  26 , a user may request corporate financial data for one or more companies through an online data provider  22  (Step S 100 ). System  24  converts the user&#39;s request to XML format (Step S 102 ). The now-converted XML request is then sent to the online web service  22  (Step S 104 ). According to an embodiment of the present disclosure, online web service  22  is a SOAP-compliant web service linked to Database  20 . Web service  22  retrieves the appropriate financial information from database  20  and returns an XML response to system  24 . The response includes a XBRL instance document including a dataset. An XBRL instance document is an XML document that contains a list of elements and values. This XBRL instance document is created by the online web service  22  by pulling data for selected companies from the database  20  and creating the XBRL instance document. Additionally the user may request that data from a XBRL instance document created outside of the online data provider be leveraged. For example, a user may open an existing XBRL instance document (Step S 130 ). Regardless of the method used to retrieve the data, the instance document will be stored as a file in the cache  10  (Step S 110 ) so that the user can make use of the instance document offline at a later time if desired. The cache  10  may include one or more storage devices provided on the same computer as system  24  and spreadsheet  26  or remotely accessible by system  24 . The instance document is processed and a taxonomy associated with the instance document (or company being examined) is retrieved from cache, local directory or the Internet (Step S 112 ). A taxonomies presentation linkbase, calculation linkbase, or user defined presentation is then processed to determine a set of presentation rules (Step S 114 ). A representation of the full taxonomy is then created in cache  10  (Step S 116 ). The instance document&#39;s elements are then retrieved and evaluated against full presentation (Step S 118 ). Elements not found in the selected instance documents are suppressed (Step S 120 ). That is, when the data in the spreadsheet is represented, the system only displays those tags and labels which are represented in the one or more selected company&#39;s financials. For example, if a company does not report short term investments in their quarterly or annual reports, then the system will not present the label in the spreadsheet output because it is not relevant for this company. As will be described in more detail later below, the user of the present system writes out data provider function calls for the elements to be included in the spreadsheet. The system then executes the function calls and returns the values found in the instance document(s) (Step S 124 ). The system also marks each cell where data was returned as a XBRL element (Step S 125 ). This allows a user to linkback to and view the source document (e.g., see  FIGS. 13A and 13B ) that provided the data in that cell. This also allows a user to view the XBRL Properties of the data in a cell by right-clicking on the cell and selecting “Properties”.  
         [0051]      FIG. 2C  is an example showing the XBRL Properties dialog box for the data of a selected cell. Label  200  is a label associated with the portion of the document where the data was taken. That is, label  200  is the primary label associated with this element in the label linkbase. Value  202  is the value associated with the element that was taken from the document. Description  204  is a brief description of the element generally providing an accounting text book description of what the data represents. Terse label  206  is a secondary label associated with the element. Type  208  shows the data type associated with the element. Units  210  presents the currency associated with the value and is generally relevant for monetary item types only. Balance  212  enables the user to understand if the element is a credit or a debit. Period  214  explains the duration associated with the data element. “Instant” would mean the data is from the end Date of the period and “Duration” would mean the data is from the beginning of the period to the end of the period. For example, revenue is generated across the whole period so it would be “Duration”, while cash would be the cash on hand at the end of the period so it would be an “Instant” element. Taxonomy  216  shows the web address of a taxonomy associated with the document or data taken. The system formats the returned values as defined in the presentation linkbase (Step S 126 ). The user can then view the requested data in the spreadsheet as, for example, a workbook (Step S 128 ).  
         [0052]     Various aspects of the present system will now be described. It should be noted that although described as an add-in to a spreadsheet, in the alternative, the present system may itself include a fully functional spreadsheet.  
         [0053]      FIG. 3  shows a Microsoft Excel spreadsheet window. The spreadsheet includes an add-in for rendering financial data and according to an embodiment of the present disclosure, is presented to the user as a button labeled FD (Financial Data)  10  in the spreadsheet&#39;s toolbar. When clicking on this button, the user is presented with a main menu  12  providing the user several options. For example, the user can activate a Fundamental Data Wizard  13  or a Market Data Wizard  14 . The Fundamental Data Wizard  13  helps the user to retrieve fundamental data by guiding them through several questions. The user&#39;s answers to these questions will be used by the system to determine which data to return. The Market Data Wizard  14  is similar to the Fundamental Data Wizard  13  but is used to retrieve intraday and historical market data. The user is also given the option of using a Fundamental Data Function Builder  15  or a Market Data Function Builder  16 . The Data Function Builders assist the user in creating custom analytical tools and models by helping them pull in fundamental data (Fundamental Data Function Builder) or market data (Market Data Function Builder). Sheet Properties  17  allows a user to modify the properties of previously requested data or to select new data. The user is also given an option to select Connection Management  19  which provides tools for logging, modifying data sources and general tool administration. Login/Switch User  18  allows a user to log in or switch to a different user.  
         [0054]     The Fundamental Data Wizard  13  (FDW) allows a user to enter and create a query (or load an existing saved query) used to retrieve data from an online data service such as, for example, EDGAR Online. Highlighting and clicking on FDW  13 , a screen such as that shown in  FIG. 4A  is displayed. This window allows a user to create or load a query by selecting one of buttons  32 ,  34  and  36 . Selecting button  34 , the user is prompted to input a file name for a file they want to review. Selecting button  36  and inputting a query name in window  38  allows the user to retrieve from storage a previously saved query. Selecting button  32 , the user is prompted to create a new query. After the user has made a selection and presses the NEXT button  40 , the screen shown in  FIG. 4B  is displayed.  
         [0055]     The screen shown in  FIG. 4B  is the primary interface for requesting data. The user is given an option to select a type of data set they would like to select. For example, using pull down menu  42 , the user is given an option to select Standardized, Summary Fundamentals or As Reported data sets. Standardized is a data set that includes information which has been converted into standard XBRL. Summary Fundamentals is a summary data set or summarized version of the Standardized data set. That is, the format of Summary Fundamentals is XBRL, but the number of data points is standardized at  75 . This data set is particularly useful for users who want to analyze companies on a high end basis. The As Reported data set leverages the naming conventions and structure of a company&#39;s filing. For example, for each company selected, a dataset is provided which includes the actual labels that were used within the company&#39;s filings with the SEC as well as the associated data. The As Reported data set is XBRL created by an online financial data web service such as Edgar Online, from documents filed with the SEC. The As Reported data set can be useful for analysts who cover a particular company and need to understand the labels and values a company is using to represent their financials. It should be noted that since different companies often use different conventions and structure for their company filings, the As Reported data set can generally not be used to compare one company to another company. Although not shown, the present system can also provide an option to select a SEC Filed dataset which enables users to request and retrieve data from XBRL financials that were filed by companies directly as XBRL documents with the SEC  
         [0056]     The system also allows the user to enter one or more company ticker symbols separated by spaces in the Symbol box  50  or the selection text box  52 . Pressing Add to List button  44  adds the entered companies to a list of companies in the system. The user can also enter a list of company symbols separated by spaces in the company symbol input box  50  or in the selection text box  52  and click on the Add to List button  44  which will add each of the companies to the system. The user can also provide a range of cells from the spreadsheet that includes company ticker symbols into box  50 . Pressing Add to List button  44  then adds those companies to the system&#39;s list. If the ticker symbol of a company is not known, pressing Lookup Symbol button  46  will prompt the user to input the name of a company. The system will then perform a lookup to determine the appropriate ticker symbol for the company and present that information to the user. The system can access the ticker symbol information online using an appropriate database search engine or can have the information already loaded locally into the computer the system is running on and perform the search locally. Selecting File button  48  allows the user to select from an existing file of company ticker symbols.  
         [0057]     After a company or companies have been selected, the user can select the period for which they would like to examine data. For example, the user is given an option to select the period by clicking on one of the Annual ( 54 ), Quarterly ( 56 ) and Other ( 58 ) tabs. When the Annual tab  54  has been selected, the user is presented with a window giving the user several options for selecting data as shown in  FIG. 4C . For example, selecting Previous button  60  allows the user to request the last X number of fiscal years of annual data, where X is a number of years input by the user in box  62 . It should be noted that the system will only return data for years for which data exists. For example, if a user requests four years of fiscal data and only two years worth of data was ever filed, only those two years of data will be returned and displayed. In the alternative, the user is given the option to select Fiscal Years button  64  and to enter the years for which they would like data, in boxes  66  and  68 . Checking the Include Quarterly Data button  70  allows the user to retrieve the quarterly data associated with the annual data that has been selected.  
         [0058]     Selecting the Quarterly tab  56 , the user is also given several options for selecting data as shown in  FIG. 4D . For example, the user can select Previous button  70  and enter the number of quarters in box  72  for which data is desired. Selecting the Fiscal Quarters button  74 , the user can request data between any two fiscal quarters input by the user in boxes  76 - 82 . Selecting the Calendar Dates button  84 , the user can request data for quarters that occurred between the two dates input by the user in boxes  86 ,  88 . Checking box  90  will retrieve annual data that may have been filed between the selected quarters.  
         [0059]     Selecting the Other tab  58  allows the user to request data for year to date and trailing twelve month periods using the window shown in  FIG. 4E . For example, selecting the Most Recent Quarter button  92  allows the user to select the most recent quarter of data. Selecting the Fiscal Quarter button  94 , allows the user to select the specific fiscal quarter input by the user in boxes  96 ,  98 . Selecting the Quarter by Date button  100 , allows the user to select a specific quarter by the dates input by the user in boxes  102 ,  104 . The user is also given the option to select data types. For example, checking YTD Data box  106 , the user can request consolidated data for the current fiscal year. Checking TTM Data box  108 , the user can request data for the trailing twelve months (e.g., the sum of the last four quarters). Checking the Include Quarterly Data box  110 , the user can retrieve quarterly data for the selected period.  
         [0060]     Returning to  FIG. 4B , the user can also select what type of data is returned using the Calculation Filter drop down menu  112  which gives the user options None, Enhanced or Preferred. Selecting None, the system only returns values for elements that have been provided by the reporting company. Selecting Enhanced returns values for elements that have been provided by the reporting company or have been rolled up (calculated ) as per U.S. Generally Accepted Accounting Principles (US GAAP) by an online company such as, for example, EDGAR Online. Selecting Preferred returns values for elements based upon US GAAP accounting rules. With the Preferred option, company provided roll-ups will be overwritten. The “Preferred” option presents a US GAAP representation of a company&#39;s financials.  
         [0061]     By default, the system will always return the most recent data available for a company. However, the user can modify this behavior by clicking on the Most Recent Financial Results Edit button  114  which then presents the user with a Result Option menu as shown in  FIG. 4F . This menu allows the user to select the source and types of data to include in the results and can be used to retrieve virtually any type of available data from any type of available document including, for example, non-SEC sources. The following are just examples of the types of data that can be retrieved. Embodiments of the present disclosure are, of course, not limited to the shown examples. The user can select data types by checking the Preliminary Reports box  116  and/or the Annual/Quarterly Results box  118  and/or Estimates box  119 . Selecting Preliminary Reports box  116 , will return preliminary fundamental data derived from 8K earnings releases in the result. Selecting Annual/Quarterly Results box  118  will include fundamental data derived from 10K, 10K/A, 10Q, 10Q/A as well as 20F, 40F and 6K foreign filing data in the result. The retrieved information may also include information derived form S1, S1/A, etc. captured from information provided by new issuers. Selecting Estimates box  119  will include earning estimate information in the data returned. By default, both the Earning Releases and the Annual/Quarterly Results options are selected. Data filters can also be selected by checking Original Results box  120 , Amended Results box  122  and/or Restated Results box  124 . Checking Original Results box  120  will include data from the originally filed 10K or 10Q in the result. Checking Amended Results box  122  will include data filed in a 10K/A or 10Q/A in the result. Checking Restated Results box  124  will include data from a restated 8K, 10K or 10Q in the result. By default, each of these data filters is selected so that original, restated and amended data will be returned unless otherwise specified by the user.  
         [0062]     In addition, by default, the system will return results in a single column of data for each of the selected period(s). The column of data is derived from the most recent data based upon the criteria selected. In the alternative, however, the user can check Return Results Individually box  126  to see each of the options included in the results listed in individual columns for the selected period. This will return all results for the selected time period, and not just the most recent. When all selections have been made, pressing the OK button  128  will save the selections for this and all future queries until changed.  
         [0063]     Returning to  FIG. 4B , Advanced Options button  130  allows the user to personalize the way content is displayed in the spreadsheet. After all selections are made in these windows, clicking Next button  132  brings the user to a window such as that shown in  FIG. 5 , which allows the user to have the results placed in a new worksheet (button  134 ), or an existing worksheet (button  136 ). When selecting an existing worksheet, pull down box  138  will present the user with a list of all available worksheets from which the user can choose. According to an embodiment of the present disclosure, when selecting an existing worksheet, the system will overwrite the contents of the worksheet with the results of the query.  
         [0064]     After completing this window, clicking Next button  140  brings the user to a window such as that shown in  FIG. 6  which allows the user to save the query so that it can be run again in the future. If the user does not desire to save the query, the query can be run by clicking on Pull Query button  148  in which case the query will be run and the information will automatically populate into the spreadsheet. If the user desires to save the query, after checking the Yes box  142  and inputting a query title in box  144 , the query can be saved by clicking on the Save As File button  146 . Clicking on Save &amp; Run button  150  will then save and run the query, with the information automatically populating into the spreadsheet.  
         [0065]     Returning to  FIG. 3 , according to an embodiment of the present disclosure, a user may choose a Market Data Wizard by highlighting and selecting Market Data Wizard  14  from main menu  12 . Upon selecting the Market Data Wizard, the user is presented with a screen such as that shown in  FIG. 7 . This screen allows a user to load and run an existing query or to create a new query and is similar to the Fundamental Data Wizard window shown in  FIG. 4A . After a selection is made and the Next button  152  is pressed, the user is presented with a screen such as that shown in  FIG. 8A  which is the primary interface for requesting market data.  
         [0066]     The user enter a company ticker symbol, search for a company by name, or load a comma separated file of company tickers using the inputs  155  in a manner similar to that described above with respect to  FIG. 4B . The user can then select what data to retrieve.  
         [0067]     The market data type tabs on the screen allow the user to select historical data (Historical tab  154 ) or intraday data (tab  156 ), with historical data being the default selection. Selection of the Historical tab  154  allows the user to identify the field of data (from window  157 ) to retrieve from a service provider such as, for example, EDGAR Online. The user can select from several fields including “Open” which will return the opening stock price, “Close” which will return the closing stock price, “High” which will return the Highest stock price, “Low” which will return the lowest stock price and “Volume” which will return the amount of shares traded. Highlighting a field and clicking on the&gt;button  158  will add that field to the requested data and that field will be displayed in the Selected Fields area  160 . Highlighting a field and clicking the&lt;button  164  will remove a field from the list of requested data. Clicking on&gt;&gt;( 162 ) or&lt;&lt;( 166 ) adds or removes the entire list of available fields. Selecting the Most Recent Data button  168  will request the most recent pricing information. Selecting the Year to Date button  170  will request the highest stock price listed by day for the year to date. Selecting the Dates button  172  will request the stock pricing for the specific time period input by the user into boxes  174 ,  176 . Selecting the Periods button  178  will select from preset time frames. Drop down menu  180  gives the user the option of selecting the following time frames: last week, last month, last 3 months, last 6 months, last year, last 3 years, last 5 years, last 10 years. The Instance field  182  will return data for one day during the period selected. The user can select from the following periods: Daily, Weekly or Monthly. For example, if the user is asking for the closing price for one year period and selects Weekly, the query will return the closing price for one day per week for that period.  
         [0068]     Selecting the Intraday tab  156 , the user is presented with a screen such as that shown in  FIG. 8B  which allows the user to identify the type of data to retrieve from the online service provider. The available fields are displayed in window  185 . The available fields and their descriptions are shown in  FIG. 8C . Highlighting a field and clicking on the&gt;button  158  adds the field to the requested data and displays the field in Selected Fields window  160 . Highlighting a field and clicking the&lt;button  164  removes the field from the list of selected fields. Just clicking on&gt;&gt;button  162  or&lt;&lt;button  166  adds or removes the entire list of available fields. Checking the Intervals box  184  allows the user to retrieve data since market open in specific intervals including every 1, 5, 30 and 60 minutes. These intervals are displayed in pull-down menu  186 . According to an embodiment of the present disclosure, when an interval is selected, the user is only given the option to select from the following fields: Event Time, Last Trade price and Volume. Once the interval is selected, the user can select a start time ( 159 ) and end time ( 161 ) for which they want to retrieve data.  
         [0069]     Once the user has made all of their selections, clicking on a Next button  183  ( FIG. 8A ) will take the user to a screen similar to that shown in  FIG. 5 , allowing the user to specify where the results should be displayed and then to a screen similar to that shown in  FIG. 6  allowing the user to save the query so that it can be run again at a later time.  
         [0070]     Embodiments of the present disclosure provide several methods for the retrieval of data into a spreadsheet such as Microsoft Excel. One method is to add a function call. This allows users to select a specific field of data and place it in a selected cell of the spreadsheet. There are several ways to add a function call to a cell. According to an embodiment of the present disclosure, this can be done directly by writing a function call by typing in the function name and parameters. According to another embodiment, this can be done using a function builder to retrieve data. In either case, the function call can be used to retrieve both fundamental and market data into the spreadsheet.  
         [0071]     Writing a function call to retrieve fundamental data will now be described. Retrieving fundamental data, the function call uses required and optional parameters. This information includes symbol, dataset, field, type, year, quarter, filter, eligible and reports.  
         [0072]     The symbol information refers to the ticker symbol of the company the user would like to retrieve data for. The dataset information refers to the dataset the user would like to retrieve date from. The datasets include, for example, Standardized XBRL Dataset (STD), Summary XBRL Dataset (SUM) and As Reported Dataset (SCPEC), and SEC filed which is XBRL filed by a company with the SEC. The field information refers to the XBRL field the user would like to retrieve from the selected dataset. The type information refers to the type of data the user would like to retrieve. The user has the option of the type (Type) of data to retrieve. For example, the user can specify Annual (A), Quarterly (Q), Trailing Twelve Months (T) and Year to Date (Y) data as desired. The year information refers to the fiscal year the user would like to retrieve data for. The user has the option of specifying a specific year, or selecting from several mnemonics including, for example, the last fiscal year (FY), the last fiscal year—1 (FY1), the last fiscal year—2 (FY2), the last fiscal year—3 (FY3) and the last fiscal year—4 (FY4). The quarter information refers to the fiscal quarter the user would like to retrieve data for. The user has the option of specifying a specific quarter (e.g., fiscal quarter 1, 2, 3 or 4). The user also can also select from several mnemonics including, for example, last fiscal year (FQ), Last Fiscal Year—1 (FQ1), Last Fiscal Year—2 (FQ2), Last Fiscal Year—3 (FQ3), Last Fiscal Year—4 (FQ4) . . . Last Fiscal Year—20 (FQ20). The Fiscal Quarter parameter is required if the user sets the Type=“Q”, “T”, or “Y”. If the user sets Type=“A” they do not have to provide a Quarter parameter. The filter information refers to the calculation view the user would like to apply to the results. Options include, for example, None (A), Enhanced (C) and Preferred (P). If the user does not specify a filter, the system will default to Enhanced. The Eligible Reports information allows the user to specify the type of information to include in the results. By default the system will return the most recent data available for the specified period. However, available options include, for example, RCNT (the default if not otherwise specified), which returns the most recent report for the selected period. PRELIM will include preliminary results (8K earnings releases) in the result. ORIG will include original filed results for the selected period in the result. AMEND will include amendments for the selected period in the result. RESTATE will include restated information for the selected period in the result. AUDIT will only include audited information for the selected period in the result. More than one option can be specified by separating them by commas. Each of the flags has three states: Include, Positive and Negative. The Include state indicates to not use the flag in generating the results. This is the default option and to specify this option the user does not specify the flag. A Positive state will only return results that match the flag. To return results that match the flag, this option is specified in the eligible reports parameter. A Negative state indicates to never return results that match the flag. To return results that do not match the flag, the user can specify this option in the eligible reports parameter prefaced with an exclamation point “!”.  
         [0073]     If, for example, the user wanted to request only audited results, they would set the eligible reports parameter to “AUDIT”. If the user does not want to retrieve preliminary information they would set the parameter to “!PRELIM”. If they would like to retrieve only preliminary information they would set the parameter to “PRELIM”. If they would only like to retrieve restated information they would set the parameter to “!ORIG, !AMEND”. The reason a user would select “!ORIG, AMEND” is when they do not want to ignore the ORIG and AMEND flags but rather only include values where neither are true.  
         [0074]     According to another embodiment of the present disclosure, the user can type the function call directly into the cell, following the procedure shown in  FIG. 9 . The user first highlights the cell where the function call is to be added (Step S 90 ). The user then types in the name of the function call followed by values in parenthesis (Step S 92 ). For example, if the user wanted to retrieve Operating Revenue for Microsoft for the 3 rd  Quarter of 2003, the user would enter the following information into the spreadsheet cell:
 
=FD(“MSFT”, “STD”, “usfr-pt:OperatingRevenue”, “Q”, 2003, 3, “C”)
 
 Once the function call has been entered, pressing the Enter button retrieves the data and populates the cell with the value (Step S 94 ). It should be noted that if no value is returned and the Internet connection is active, the company has not filed a value for the requested field. 
 
         [0075]     According to another embodiment of the present disclosure, a function call can be written to retrieve market data. When retrieving market data, the function call takes the following required and optional parameters: Symbol, Dataset, Field and Date.  
         [0076]     The Symbol parameter refers to the ticker symbol of the company the user would like to retrieve data for. The Dataset parameter refers to the dataset the user would like to retrieve data from. The available datasets include Historical Dataset (HIST) and Intraday Dataset (INTRA). The Field parameter refers to the field the user would like to retrieve. For the Historical Dataset, the fields include Opening Price (OPEN), Closing Price (Close), Daily High (HIGH), Daily Low (LOW) and Daily Volume (VOLUME). For the Intraday Dataset, the fields include ExchangeCode, SecurityCode, LastTrade, Change, PercentChange, Tick, DateTime, Time, Ask, Bid, High, Low, Open, Volume, AnnHigh, AnnLow, Dividend, EPS, Close, PE, Yield, Delay, Halt, Beta, TSO and MarketCap. Date is an optional parameter for specifying the date associated with the data the user would like to retrieve. The format may be entered, for example, as MM/DD/YYYY HH:MM  
         [0077]     The user can type the function call directly into the cell. To do so, highlight the cell where the function call should be added and type the name of the function call followed by values in parenthesis. For example, if the user wanted to retrieve Open price for Microsoft for Apr. 28, 2005, the user could enter the following information into the spreadsheet cell:
 
=FD(“MSFT”, “HIST”, “OPEN”, “Apr. 28, 2005”)
 
 If the user wanted to retrieve today&#39;s open price, the user could enter the following information into the spreadsheet cell:
 
=FD(“MSFT”, “INTRA”, “Open”)
 
         [0078]     Once the user has entered the function call, pressing the Enter button will retrieve the data and populate the cell with the value. Again, it should be noted that if no value is returned and the user&#39;s Internet connection is active, the company has not filed a value for the requested field. In addition to including direct values as the parameters to the function call, the user can reference other cells in the spreadsheet.  
         [0079]     According to another embodiment of the present disclosure, a function builder may be used to retrieve fundamental data. A Fundamental Data Function Builder guides the user through the process of creating function calls and placing them in cells. This enables users to quickly and easily retrieve individual data elements and include them in custom templates and models. To access the Fundamental Data Function Builder, from main menu  12  ( FIG. 3 ), the user selects Fundamental Data Function Builder  15 . This will launch the Fundamental Data Function Builder which consists of one screen as shown in  FIG. 10A .  
         [0080]     The Fundamental Data Function Builder includes several sections which help the user to retrieve the data they are interested in. For example, Select Data Set pull down menu  200  allows the user to select the data set that they would like to retrieve the data from. Available datasets include, for example, Standardized which is the US GAAP Standardized Dataset, Summary Fundamentals which is the summarized version of the Standardized dataset and As Reported which is a dataset leveraging the naming conventions and structure of the company&#39;s filings and SEC Filed which is XBRL filed by a company with the SEC. According to an embodiment of the present disclosure, not all users will be presented with the same options. That is, according to this embodiment, the list shown in pull down menu  200  will only be populated with the datasets to which the user subscribes.  
         [0081]     Taxonomy in essence is a data dictionary. As mentioned above, different companies may use different taxonomies for their data. By entering a company (e.g., company ticker symbol) into box  202 , a user can load the taxonomy or taxonomies associated with the company the user is analyzing. When analyzing multiple companies, the user should select one of the companies to use. Once the company&#39;s ticker symbol or a cell location which contains the company&#39;s ticker symbol is entered into box  202 , clicking on the Load Taxonomies button  203  will load the available taxonomies for that company. A list of taxonomies associated with each company can be stored at the users location (for example, on the user&#39;s computer system or locally accessible by the user&#39;s computer system) or can be stored at an online data provider such as EDGAR Online and later retrieved by the present system. According to an embodiment of the present disclosure, the present system will display the URL(s) to the taxonomies associated with the company in a drop down list  204 . In addition, according to an embodiment, the present system will load a list of elements available in this taxonomy. Data Element area  206  displays all of the elements included in the selected data set. An example of a data set is shown in  FIG. 10B . Selecting elements with + signs next to them will expand the tree and display each elements children.  
         [0082]     In the center of the screen ( FIG. 10A ), information is displayed that is tied to the selected data element. This information includes, for example, the full Label  208  for the data element, the type of Balance  210  (debit or credit) and the financial definition or Description  212  of the data element. The information is displayed next to the appropriate heading.  
         [0083]     Pull down menu  214  is referred to herein as the linkbase selector and allows the user to select the type of information about the element which they would like to retrieve through the function call. The user can select from several options including Instance Document which is the default option. As shown in  FIG. 10A , selecting Instance Document then allows the user to select &lt;value&gt;, Content, Reference, Precision and Unit Reference. The parameter &lt;value&gt;is the default, and will return the value associated with the element. Context Reference will return the context identifier associated with the element. Precision will return the precision that should be applied to the value. Unit Reference will return the units the value is being displayed in (e.g., USD, JPY, . . . ) Other options that can be selected in pull down menu  214  include Taxonomy which allows the user to select attributes associated with the taxonomy, Calculation Linkbase which allows the user to select attributes that define how information has been calculated, Label Linkbase which allows the user to select attributes that describe the field (such as labels as descriptions), Presentation Linkbase which allows the user to select attributes that describe how elements relate to each other (parents, children), Reference Linkbase which allows the user to select attributes that provide reference information about the data and Company Information such as name, address, exchange, etc.  
         [0084]     Once the user has selected the information they are interested in, Macro Settings portion  215  of the display allows the user to select the company, period, etc. for which they would like to retrieve data. Specific options include, for example, Symbol  216  in which the user can input the symbol of the company to retrieve data for and Period  218  in which the user can indicate the specific period they are interested in. In particular, dropdown menu  218  allows the user to choose from Annual to retrieve annual data, Quarterly to retrieve quarterly data, Trailing Twelve Months to retrieve trailing twelve month (TTM) data and Year to Date to retrieve Year To Date (YTD) data.  
         [0085]     The user can also select, using drop down list  220 , the specific fiscal quarter the user would like to retrieve data for. For example, the user can select the last fiscal quarter or any of the previous fiscal quarters from the current fiscal quarter from the drop down list  220 . The user can also select, using drop down list  222 , the fiscal year the user would like to retrieve data for. For example, the user can select a specific year, or select the last fiscal year from the drop down list  222  to retrieve annual data, quarterly data, trailing twelve month (TTM) data or Year To Date (YTD) data. Calculation View drop down list  224  allows the user to select the calculation filter the user would like to apply to the result. The Calculation View drop down list  224  is only available when the attribute=&lt;value&gt;. This drop down list, when available allows the user to select None which only returns values for elements that have been provided by the reporting company, Enhanced which returns values for elements that have been provided by the reporting company or have been rolled up (calculated) as per US GAAP by a data provider such as, for example, EDGAR Online, Preferred which returns values for elements based upon US GAAP accounting rules (company provided roll-ups will be overwritten) which presents a US GAAP representation of a company&#39;s financials.  
         [0086]     After all fields are filled where appropriate, clicking on the Write Function button  226  will write a function call to the currently highlighted cell. If no cell is highlighted the user should select a cell with the mouse and then press the Write Function button  226 . Once pressed, the results will be retrieved and displayed in the selected cell. Users are also given the ability to select an item in the drop down menu  214  and drag the item to a cell on the spreadsheet.  
         [0087]     A function builder may also be used to retrieve market data. Clicking on the Market Data Function Builder button  16  from the main menu ( FIG. 3 ) selects the Market Data Function Builder. The Market Data Function Builder allows the user to create a function call that retrieves the market data for a company and places it in a user defined cell. An example of a Market Data Function Builder is shown in  FIG. 11 .  
         [0088]     The user first highlights or otherwise selects the cell in the spreadsheet where the user would like the data to be placed. The user then inserts the Symbol (or a cell reference that contains the symbol) of the company for which the user would like to retrieve data, into box  300 . The user can also lookup a company symbol using button  302 . The user can then define the Macro Properties in area  304 . Pull down menu  306  allows the user to retrieve data from a chosen dataset. The datasets the user can choose from include a Historical Dataset and an Intraday Dataset. Field  308  allows the user to use a pull down menu to select a field to retrieve from. When Historical Dataset is chosen, the user is given the option of selecting from the following fields: Opening Price, Closing Price, Daily High, Daily Low and Daily Volume. The user can then select the date for which they would like to retrieve data by entering it into box  310 . When Intraday Dataset is chosen, the user can select from the following fields: ExchangeCode, SecurityCode, LastTrade, Change, PercentChange, Tick, DateTime, Time, Ask, Bid, High, Low, Open, Volume, AnnHigh, AnnLow, Dividend, EPS, Close, PE, Yield, Delay, Halt, Beta, TSO and MarketCap. After entering the above-described information, by clicking on the “Write Macro” button  312 , the data will be retrieved and placed into the selected cell in the spreadsheet.  
         [0089]     The wizard creates a function call  31  in the cell to retrieve the data for the stock price, as shown in  FIG. 12 . In the example shown, the function call will retrieve the opening date price for Microsoft on Mar. 29, 2005. As shown in column B, row  2 , the spreadsheet is populated with the opening price on that day of $24.13.  
         [0090]     Another option on main menu  12  ( FIG. 3 ) is Sheet Properties  17 . The Sheet Properties option is used to view the properties of an active worksheet that is currently being displayed and is used to make a new request or to view/update a request that was previously made. For example, Sheet Properties allows a user to modify the properties of previously requested data or to select new data into a worksheet currently being displayed. The Sheet Properties window is similar to the second screen of the Fundamental Data Wizard shown in  FIG. 4B . Using the Sheet Properties window, the user can modify or make selections exactly as described above with respect to the Fundamental Data Wizard screen shown in  FIG. 4B . Accordingly, operation of the Sheet Properties window will not be further described in detail herein. Once the user is satisfied with the selections, pressing the Run Query button will retrieve the results into the active worksheet. Any contents found in the active worksheet will be over-written.  
         [0091]     The Login/Switch User  18  menu option ( FIG. 3 ) allows the user to work offline or another user to access data. The Connect Management Option  19  menu option allows a user to enable application logging, easily remove downloaded files and to modify the location of the online web service being used.  
         [0092]     Once the data has been retrieved, embodiments of the present disclosure allow the user to perform a number of functions. For example, according to an embodiment of the present disclosure, the user can link back to an original document that shows exactly what document and from where in the document a particular value was retrieved. This is referred to herein as a linkback feature. To activate this feature, the user right clicks on a cell containing the value of interest.  FIG. 13A  shows an example of a spreadsheet created by a user utilizing the present disclosure that displays Cash and Cash Equivalents for Microsoft for 2004. Upon right clicking on the value $14,304,000,000, a menu will be displayed as shown. Clicking on “Go to source document” will then launch a window that will display the reported filing from which the value was retrieved, an example of which is shown in  FIG. 13B . As shown, the value was retrieved from a “Cash and Equivalents” column of 10-K Filing dated Aug. 26, 2005. According to an embodiment of the present disclosure, the column containing the value of interest is highlighted for ease of reference.  
         [0093]      FIG. 14  is a screen shot of a spreadsheet according to an embodiment of the present disclosure, showing the financials of several corporations being displayed side by side allowing a user to perform an easy comparison. Column  440  describes the various elements shown in the spreadsheet. Columns  442 - 446  are the company financials for each of the three companies being analyzed.  
         [0094]     According to another embodiment of the present disclosure, a financial data system is capable of displaying various types of information associated with the main financial information being displayed. For example, according to an embodiment of the present disclosure, a system allows users to view footnote information as it relates to different types of tabular data shown in the main body of a report.  
         [0095]     Documents such as financial documents often include information besides that in the main body of the document. This information is referred to herein as “associated information”. This associated information may include, for example, footnotes, head notes, management discussion, etc. Although the associated information may not be included in the main body of the financial document, it may nevertheless contain important information that can be useful when evaluating the financials of a company.  
         [0096]     According to an embodiment of the present disclosure, a text file for each document, which includes the associated information section(s), is broken down into a list of sentences. Each sentence is marked and has an associated category and document identifier applied to it to allow it to be re-inserted later in the document and highlighted. This information allows the user to later view the associated information in its proper context.  
         [0097]      FIG. 15  is an example of a footnote section of a financial document. Although not shown in  FIG. 15 , the footnote section is entitled “Notes To Consolidated Financial Statements” and is annexed to the end of the financial statement for a company called ABC Co. The information contained in the footnote section, although relatively meaningless on its own when taken out of context, is relevant when taken in context with the associated information from the main body of the financial document.  
         [0098]     According to an embodiment of the present disclosure the footnote textual data, can be parsed out of the document, processed and later displayed in relation to information (e.g., XBRL elements) from the main body of the document. The footnote data is connected to one or more XBRL categories, allowing the user to quickly view the footnote data in context with the corresponding XBRL element.  
         [0099]     The information in financial documents can vary depending on the specific type of document. For example, information in a corporate balance sheet can generally be broken down into one of the categories in the list shown in  FIG. 16 . The  23  categories (also referred to as data points) shown in  FIG. 16  correspond to a Commercial and Industrial (C&amp;I) taxonomy and in particular to XBRL labeled data in a Balance Sheet. Of course, the list can be expanded to include other categories such as, for example, Income Statement and Cash Flow Statement data, etc. In addition to data from Commercial and Industrial taxonomy other available XBRL taxonomies such as Oil and Gas, Real Estate, Insurance, etc. can be provided for.  
         [0100]     As shown in  FIG. 16 , the categories include Assets which include Current Assets (e.g., Cash and Cash Equivalents, Short Term Investments, etc.) and Non Current Assets (e.g., Property Plant and Equipment, Long Term Investments, etc.). Liabilities include Current Liabilities (e.g., Accounts Payable and Accrued Expenses, Deferred Revenue, etc.), Non Current Liabilities (e.g., Long Term Debt, Long Term Capital Lease Obligations, etc.) and Retirement Obligations (e.g., Deferred Tax Liability, Minority Interest, etc.) As mentioned above, this list of categories can be expanded to include other categories such as Income Statement, Cash Flow Statement data, etc.  
         [0101]     Data in the main body of the balance sheet is assigned to and XBRL labeled to correspond to one or more of the categories shown in  FIG. 16 . In addition, according to an embodiment of the present disclosure, the associated information (e.g., footnotes) can be parsed from the document, categorized and assigned to one of more of these categories so that the information can later be easily retrieved and put into context by a user of the financial data system.  
         [0102]     A system for categorizing associated information according to an embodiment of the present disclosure will now be described by reference to  FIGS. 17 and 18 . An Associated Information Processing System  200  according to an embodiment of the present disclosure, is shown in  FIG. 17 . Operation of system  200  will be described by reference to the flowchart shown in  FIG. 18A . A parsing module  202  parses the associated information (e.g., footnotes, headnotes, etc) from a document (Step S 2 ). Converting module  204  converts the parsed data into a text file (Step S 4 ) and metadata module  206  adds metadata uniquely identifying the text in the text file (Step S 6 ) The information is then sent to a categorization module  208  (Step S 8 ). Categorization module  208  breaks down the text file into sentences (Step S 10 ) and categorizes each sentence (Step S 12 ). For example, categorization module  208  runs each sentence against each category in the list (see  FIG. 16 ) and determines association strength of each sentence to each category. Categorization module  208  then outputs each sentence, its matching categories and association strengths along with the metadata, to threshold filter module  210  (Step S 14 ). Threshold filter module  210  then performs threshold analysis to determine which category or categories to associate with each sentence (Step S 16 ). Threshold filter module  210  eliminates the sentences that do not match a category and eliminates matches for which the association strength is below a set value. System  200  then outputs each sentence with matching categories (Step S 18 ). Each matching sentence is linked back to its location in the document via document offset numbers. The offsets, referred to above as “document identifie” are what allows the best-matching sentence to be viewed in its context in addition to being viewed independently.  
         [0103]     There are various types of processing systems that can be used to categorize data. An example of a categorization module  208  is made by Alias-I, Inc. The module processes sentences and performs statistical matches against selected elements. For example, according to an embodiment of the present disclosure, the module rates each sentence from the associated notes against each category and outputs the results.  
         [0104]     An example of operation of the categorization module (Step S 12 ) will be explained by reference to  FIG. 18B . The first sentence from the associated notes is retrieved (Step S 40 ) and rated against a first category (e.g., Cash and Cash Equivalents). The result (associated match strength) is saved. If additional categories exist (Yes, Step S 44 ), the process returns to Step S 42  and rates the sentence against the next category. This process repeats until no additional categories exist (No, Step S 44 ). The module then outputs the sentence and the associated category matches as well as the match strengths (Step S 46 ). If additional sentences exist (Yes, Step S 48 ), the process returns to Step S 40  and process repeats. If no additional sentences exist, the process ends (Step S 50 ).  
         [0105]     According to an embodiment of the present disclosure, the categorization module outputs the input string and its associated match strength represented as a number between zero and one. The module outputs the input string and its associated match strength represented as a number between zero and one. An associated match strength closer to one indicates a stronger match. That is, the closer the associated match strength is to one, the more likely it is that the sentence corresponds to the category. An associated match strength closer to zero indicates a weaker match. That is, the closer the associated match strength is to zero, the less likely it is that the sentence corresponds to the category.  
         [0106]     An example of some of the information output by categorization module  208  is shown in  FIG. 19 . Categorization module  208  outputs a Document ID  50  which identifies the sentence. The Sentence Text ID  52  shows at least a portion of the text of the sentence. Label/Category  54  shows the category or categories which the categorization module has associated with the sentence. Association Match Strength  56  shows the relative strength of the match. In the example shown in  FIG. 19 , the first sentence (Document ID 1) matches the “Investment Securities” category with an association strength of 0.983066 (approximately 98%). There are no other matches for this sentence. For the second sentence (Document ID 2), there are three matches. The matches are “Intangible Assets” (0.01603284 or approx. 1.6% association strength), “Inventories” (0.00539003 or approx 0.5% association strength) and “Investment Securities” (0.0034696 or approx. 0.34% association strength), respectively. Accordingly, for the second sentence, the best match is the category “Intangible Assets” although the association strength is weak.  
         [0107]     According to an embodiment of the present disclosure, the categorization module  208  is trained prior to being used. For example, according to an embodiment of the present disclosure, prior to the categorization modules initial use, each sentence in a training corpus is run blind against each category from a list, and category matches are determined. Precision and recall measures are taken based on the “ground truth” of the category. For example, since training data is being run against training data, we know what the actual categories should be. That is, for each sentence in a category “A”, there are exactly that many in the “test set”. Accordingly, if every “A” is correctly called “A”, there is 100% precision and recall (on that category). If the categorization module  208  does not find all the “A”s (e.g., it finds some “B”s or “C”s) the categorization module  208  has a recall problem. Recall is the ratio of the number of relevant records retrieved to the total number of relevant records in the database and is usually expressed as a percentage. If the categorization module  208  finds too many “A”s, it has a precision problem. Precision is the ratio of the number of relevant records retrieved to the total number of irrelevant and relevant records retrieved and is also usually expressed as a percentage. If a recall and/or precision problem exists, parameters of the categorization module  208  can be modified until the results output by the categorization module are acceptable.  
         [0108]     Running Such test runs on training data is known as a “cheating” experiment and although these test runs are an indication of whether the system is working properly and is generally considered a reliable way to judge training data quality, it will be appreciated that results may vary greatly on subsequent test sets of real-world data. Data in the training corpus that is not run during these testing rounds (also referred to as “held out” data) is run when the previous testing rounds are yielding good results. For example, results are considered good when relevant sentence matches to categories are consistently above the level of matches of non-relevant sentences. Various types of categorization techniques can be utilized by categorization module  208  for the matching process. For example, according to an embodiment of the present disclosure, the matching process is a character-based Bayesian statistical model. Of course, other categorization techniques can be utilized as desired.  
         [0109]     Threshold filter module  210  filters the data so that only the match or matches having sufficient association strength are presented to the user. Various types of filtering strategies can be used to determine which match to present to the user if there are multiple matches. For example, the filtering strategy could be “best match” in which case only the match with the highest association strength would be displayed. In the alternative, a filtering strategy could be “matches over n %” in which only matches with association strengths above a predefined value (n) are displayed. A filtering strategy could even be used in which “all matches found” can be displayed. According to an embodiment of the present disclosure, when multiple matches for a single sentence are displayed, they are shown in rank order from highest association strength to lowest association strength. According to an embodiment of the present disclosure, the user is given an option to select which filtering strategy to use, and to define the predefined value (n) as they desire.  
         [0110]      FIG. 20  is an example of a spread sheet populated with data showing a portion of information from a financial document of ABC Company. This information represents the financial data from the “main” portion of the financial document including XBRL data  60 . According to an embodiment of the present disclosure, “Short Term Investments,”  62  is circled or otherwise highlighted to indicate that there is associated information corresponding to this category. When a user then double clicks on “Short Term Investments”, a page  70  as shown in  FIG. 21  will pop up showing all of the associated information for this financial document. In this example, the associated information is “Notes to Consolidated Financial Statements.” According to this embodiment, each sentence from the notes is displayed with the particular sentence ( 72 ) associated with the “Short Term Investments” being highlighted. This allows the user to view the notes in context with the financial data from the main portion of the financials. In addition, since each sentence in the Notes is listed in the same order they are shown in the actual financial document, the user can view the associated information in context with the other associated information. According to another embodiment of the present disclosure, only the associated sentences for that category would be displayed in pop up page  70 . Moving scroll bar  74  down the page, the user can review all of the Notes from that financial statement if desired.  
         [0111]     There are various ways the associated information can be accessed. According to an embodiment of the present disclosure, the user can access associated information using a drop-down menu. For example, a user can right click on an area of interest in the document (e.g., in a table or in the text) and choose to view information associated with the information in the area of interest. As shown in  FIG. 22 , when a user right clicks on an area of interest (e.g., the value $2,865) in the displayed data, the user is presented with a drop-down menu  882  giving the user the option to review the associated information relating to that area of interest by clicking View Related Notes  884 . As shown in  FIG. 23 , after clicking View Related Notes  884 , the user is presented with a related notes window  886  showing the information extracted for each category with the category for the chosen information  883  displayed on top.  
         [0112]     The user can then click on a sentence to view the information in context. For example, by clicking on sentence  885 , the user is presented with a display such as that shown in  FIG. 24  with the sentence highlighted and shown in its proper context.  
         [0113]     According to other embodiments of the present disclosure, the user can access the associated information by clicking a link to the footnotes information, for example, found in a task-bar, a header or right-hand menu column near the area of interest.  
         [0114]     For ease of description, various embodiments of the present disclosure have been described above as using individual “modules” for implementing various features. However, it will be appreciated that two or more (e.g., all) of these modules may be combined into one (or more) module(s) for executing code for rendering components of the present disclosure.  
         [0115]     The present system can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. The system can be implemented as a computer program product, i.e., a computer program tangibly embodied in an information calTier, e.g., in a machine-readable storage device or in a propagated signal, for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor, a computer, or multiple computers. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.  
         [0116]     Method steps associated with the present system can be performed by one or more programmable processors executing a computer program to perform functions of the invention by operating on input data and generating output. Method steps can also be performed by, and apparatus of the disclosure can be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).  
         [0117]     Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. Information carriers suitable for embodying computer program instructions and data include all forms of non-volatile memory, including by way of example, semiconductor memory devices, e.g., EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; CD-ROMs (Compact Disc Read-only Memory) and DVD-ROMs (Digital Versatile Disc Read-only Memory). The processor and the memory can be supplemented by, or incorporated in special purpose logic circuitry.  
         [0118]     To provide for interaction with a user, the present disclosure can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to t he user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.  
         [0119]     The present system can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middle-ware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical interface or a Web browser through which a user can interact with an implementation of the present disclosure, or any combination of such back-end, middleware, or front-end components. The components of the computing system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet.  
         [0120]     The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on respective computers and having a client-server relationship to each other.  
         [0121]     The present system has been described in terms of particular embodiments. Other embodiments are within the scope of the following claims. For example, although the present system has been described as a component in a larger system, it can also be implemented in other systems or as a stand-alone system.  
         [0122]     Numerous additional modifications and variations of the present disclosure are possible in view of the above-teachings. It is therefore to be understood that within the scope of the appended claims, the present disclosure may be practiced other than as specifically described herein. For example, elements and/or features of different illustrative embodiments may be combined with each other and/or substituted for each other within the scope of this disclosure and appended claims.