EP0890154A1

EP0890154A1 - Data-conversion method

Info

Publication number: EP0890154A1
Application number: EP97916371A
Authority: EP
Inventors: Rolf Wadewitz
Original assignee: Individual
Current assignee: Individual
Priority date: 1996-03-25
Filing date: 1997-03-21
Publication date: 1999-01-13
Also published as: WO1997036250A1

Abstract

The invention concerns a method of converting data between two applications or software packages which use different data formats. A fundamental problem in data-processing today is the combination and exchange of source data from different software packages. Intelligent conversion software predominantly uses data structures of data bases and data-processing equipment. Proceeding from a first recognition of a rough structure, the file form is pre-classified in conversion tools. The conversion software provides an algorithm set by means of which the fine structure is automatically recognized and converted. The analysis of model files of applications A and B is continued as far as the substructure level, the source data finally being converted by means of the analysis into the target data which are imported by application B.

Description

description

Data conversion procedures

The invention relates to a method for converting data between two applications or software packages that use different data formats, according to the preamble of claim 1.

The invention is based on the fundamental problem of the incompatibility of data from different applications or software packages. Many programs have their own data format for the internal processing of the data. However, this is rarely readable by other programs for further processing. The user is faced with the problem of transporting any data from application A to application B, although the data formats of applications A and B are generally unknown to him. The data to be transported are mostly databases, but application data can also occur in the broadest sense, such as text files, CAD data, sound formats, calculation programs and others.

In order to be able to implement the data transfer described above, modern and flexible programs offer the possibility of reading in data in the most common formats and further processing them in their own format. In order to enable an exchange between different applications, for example also from other operating systems, some software packages provide an import and export function in ASCII format or another common format. In addition, there are many auxiliary programs that allow data conversions from a format A to a format B. These have implemented a fixed conversion algorithm which corresponds to the respective application. The user can now choose between which data formats A and B the program should perform a conversion. These auxiliary programs can partially recognize the type of file or the type of application A automatically on the basis of simple specific features in the file form, such as the file form and fixed information structures and version identifiers within the file.

A special method for data conversion is already known from DE 4128 940 AI. With the aid of this method, print-prepared digital data of a document created with text and / or graphics software on the screen of a data processing system are converted into facsimile-specific transmission data. This method replaces the cumbersome, time-consuming and error-prone method of printing out a document created on the screen of a data processing system on a printer connected to the data processing system and then scanning the document printed on paper by an optoelectronic unit of a facsimile device. The scanning data of the optoelectronic unit are then coded and transmitted in a facsimile-specific manner.

Both the conversion programs integrated in the applications and the independent auxiliary programs for data conversion both have the disadvantage that only a limited selection of data formats is made available which can be converted using the fixed algorithms of the program. These conversions generally do not take into account the element contents and their links, such as character content and character length, linguistic aspects, rules of existence, element transformations, language space, element pattern and element interpretation. Also, most of the data formats not very well standardized, and many applications bring their own data structures. The data elements are optimized for the source application and can cause processing errors in the target application which have to be laboriously corrected by the user or even make further processing of the data impossible.

It is an object of the invention to provide the user with a method for data conversion which enables flexible data matching of different application programs with relatively simple means.

According to the invention, this object is achieved by the features of patent claim 1.

Inventive developments and refinements of the invention are described in the subclaims.

The conversion software according to the invention is able to transfer data of any format A into data of any format B semi-automatically and also fully automatically, with in principle no restriction with regard to the possible data formats. Since the data formats A and B are analyzed semi-automatically and fully automatically in their fine structure by the conversion software according to the invention, in addition to the rough structure of the data, the possible error rate in the data transfer from application A to application B is significantly lower than in the usual auxiliary programs. In addition, data changes and data adjustments are provided in various levels, for example in the file, record, element level and others, in order to reduce the error rate in the target application.

The structure of the method for data conversion according to the invention is shown in the drawing and explained in the following. In it show: 1 shows the information flow diagram of the method for data transfer;

2 shows a diagram for structural analysis of the method with detailed structure; 3 shows the course of the synthesis of the method for forming data B from data A;

4 shows the information flow diagram according to FIG. 1 in a more detailed representation.

FIG. 1 shows in the form of an information flow diagram the sequence of a data transfer using the method according to the invention or the conversion software (1) according to the invention. A user would like to transport any source data Q (2) generated and exported by application A (3) to application B (4) in order to process them there. Each of the applications A (3) and B (4) can import and export their data in a format that they can understand; this is implemented in applications (3) and (4) in order to exchange data between applications of the same type at different workplaces.

The user can now generate a sample export of, for example, approximately 500 data records from the database of application A (3) and that of application B (4). This creates template file VA (5) from application A (3) and template file VB (6) from application B (4). A prerequisite for the functioning of the data conversion method is that application B (4) can import its own exported template file VB (6), which it has produced and exported, but this should of course work. Now the template files VA (5) and VB (6) can be analyzed (7) using the conversion software (1).

In principle, it would also be possible to exchange data directly from application A (3) to application B (4) without going through the

File (for example OLE, DDE and others) to go. Here will then the detour via the files is saved, while the analysis and linking processes naturally remain effective.

Since the user generally does not know anything about the structure of the data structures and the data structures of applications A (3) and B (4), and does not want to know anything about them either, complex algorithms are required for the analysis in order to provide the user to relieve decisions as far as possible and to automate or at least partially automate the analysis and linking process (8). The implemented algorithms can be easily expanded to be able to analyze new, future data structures. The scope of the analysis (8) of the structures is explained in more detail below with reference to FIG. 2. After the analysis and linking process (8), the conversion software (1) knows the data structure of the template files VA (5) and VB (6) and also the necessary links between the elements of the template files VA (5) and VB (6). This conversion pattern for the transfer of the data from application A (3) to application B (4) is stored as a sample sequence file M.

If the user wants to carry out further data transfers between the same applications A (3) and B (4) as explained above at a later point in time, it is possible to save the conversion pattern that has just been obtained in the form of pattern sequence data M (9) (10 ). This means that the user does not need to generate the template files VA (5) and VB (6) in the next conversion process, and the conversion software (1) can directly access the saved sample sequence data M (9) and the sample sequence data during data transfer without analysis process (8) Read M (9) again (10).

As shown particularly in FIG. 4 in addition to FIG. 1, the analysis phase of both the template file VA (5) and the template file VB (6) is subdivided into a rough analysis, a subsequent fine analysis, a further subsequent sub-analysis and so on. ter in order to finally arrive at the final analysis. The analysis phase is then followed by the linking phase, in which the analyzes of the template files are linked.

In the synthesis phase (11) a conversion of the source data Q (2) into the target data Z (12) is achieved with the aid of the determined analysis and linking result. In the last step, application B (4) can import the target data Z (12), since they are in the data format that can be imported and exported by application B (4), and process them further.

With this method according to the invention for data conversion, it is also possible for the user to make data changes by using special rules defined by the user in the synthesis (11) of the source data Q (2) into the target data Z (12). As examples, and by no means fully listed, here are only the replacement of ä, ö, ü by ae, oe ue and the transformation of the elements [Dear] and [Mr. xyz] into the elements [Dear Mr.] and [ xyz] called. Of course, very complex data changes are also possible, which can best be compared with the term "morphing" from image processing, which describes the change from pattern A to pattern B without loss of information.

As FIG. 1 shows, the source file (28) to be exported from application A (3) is placed in the source analysis (29). After the analysis for automatic rule formation and links in block (8) has been carried out, the target analysis (11) is created. The converted data are then placed in the importable target file (30). In the process of exporting the source file (28) into the target file (11) by means of the pattern flow data M, a source or target analysis is no longer necessary. In this case, the rule formation and the links were already generated with the template files VA (5) and VB (6). During the synthesis, the source file Q (2) is read and with the data filter processed from the pattern flow data M. The data records generated are written to the target file. The data filter can use external files for comparison as well as internal files for searching and sorting.

FIG. 2 shows a diagram which shows the structure of a general data transfer file in a detailed form. The analysis (8) of the template files VA (5) and VB (6) is divided into several phases. On the basis of the first recognition of the rough structure (13), the file form is first pre-classified, as in the case of conversion programs known hitherto. The intelligent conversion software now also provides a set of algorithms that are able to automatically recognize the fine structure (14) of the data at hand. The analysis (8) is continued in order to also recognize the substructures (15) within the data elements (17).

As can also be clearly seen in FIG. 3, the rough structure (13) serves to recognize the file structure, the separators, the element identifier, the character length, etc. in the file space and in the sentence space (16). In the rough structure (13) files are differentiated according to their file form. The differences can be recognized, for example, from file extensions or information structures within the entire file.

The fine structure (14) serves to recognize element existence, element character contents, element character length, etc., such as element dream (19) and drawing space (20). The fine structure (14) relates to the sentence level, which contains the structure of a single data record in the so-called sentence space (16) from the elements (17), as well as the links between the sentence elements (17), the so-called sentence control space (18). When determining the features for the data record structure and the data record structure, for example field names in a data record (16) are analyzed, the use of special separating symbols for elements (17) and data records (16), the use of start and stop symbols for structuring - determined within the elements (17) and the number of elements (17) per data record (16).

The substructure (15) serves to recognize words and sub-elements with sub-separators in the individual elements, such as element dream (19), drawing space, word space. The substructure is thus subdivided into the element level, the element space (19), and the drawing level, the drawing space with number space (20). In the element level (19) the existential characteristics for an element (17) are determined.

For example, the following exist as characteristics: minimum and maximum data element character length, data element existence requirements (must, can, may), permissible and occurring characters in a data element (17), language space used, limited list structures within data elements (17 ), Word analysis, etc. The character level (20) specifies the possible selection spaces for numbers, letters, special characters, OEM characters and others.

For example, the "Working Time" element can be a

1st movement: "Meier / Müller / Graf / Kemper", one

2nd movement: "8h / 7H / 9h / 8h" and one

3rd sentence: "5H / 9h / 11h / 7h included.

As a result, there are obviously structures in the "Working time" element that are separated by the "/" character. Such and similar substructures are recognized and treated in the analysis like additional elements with identifiers, namely Meier, Müller, Graf, Kemper, and corresponding contents.

As already mentioned elsewhere above, the "salutation" element contains several words:

1st sentence: "Dear Sir",

2nd sentence: "Dear Ms", ~ 3rd sentence: "Hello, Mr." and

4th sentence: "Dear Mr. Dipl.-Ing". These substructures are adopted as words in word lists and, if necessary, further analyzed individually according to additional patterns and rules.

Another example serves to illustrate this. The "Street" element contains the patterns

1st sentence "Hofweg 13",

2nd movement "At the long Kant 77" and

3rd sentence "Bremer Strasse 19".

These substructures (15) are analyzed as words and examined for patterns. For example, street names and house numbers can be split.

It is very important that the substructures (15) relate to objects in one level under the sentence elements. Here the element contents are searched for further patterns.

In the case of the pattern structure, the pattern and linkage analyzes are carried out with the aforementioned analysis results

(Sentence space (16), sentence control space, element space (19), word space).

Overarching patterns and rules are established by means of fixed

Algorithms and neural as well as fuzzy algorithms are determined.

In order for the pattern recognition in the linguistic analysis (8) of fine structure (14) and substructure (15) to run as automatically as possible, the algorithms require the use of modern techniques, such as neural networks and fuzzy logic in addition to fixed algorithms . If one omits such approaches, the user may have to make individual links manually.

FIG. 3 shows in diagram form the synthesis process (11) for the formation of the data elements (21) for application B (4) "from the data elements (22) of application A (3). From the analysis (8) described above Template files VA (5) and VB (6) the result is a data filter (23) which contains the previously determined linking rules (24) between the data elements (21) and (22). If one sends the data records (25) from the application A (3) through this data filter (23), one obtains new data records (26) with new data elements (21), which in one of the applications B (4) and exportable data format. The number of data elements (22) of data records (25) from application A (3) is not necessarily the same as the number of data elements (21) of data records (26) for application B (4), the number of data records ( 25) and (26) is generally the same for both applications A (3) and B (4).

In addition to the data filter (23) for the data transfer from application A '(3) to application B (4) resulting from the analysis (8) of the template files VA (5) and VB (6), the data elements (21) must also be compared. and (22) possible with an external database or several external databases (27), for example also the mixture of several databases, such as customer file + invoice file. With such an external comparison, for example, the postal codes of data records (25) and (26) can be checked by comparing the data elements (21) and (22) of country, city, street and postal code with those of the external database (27) compares.

In addition, the creation of one or more internal intermediate databases for searching and sorting at the file level is possible. This is necessary in order to enable quick searching and sorting, for example according to the alphabet or special features.

Reference list

1 conversion software or process

2 source data Q

3 Application A

4 Application B 5 template file VA

6 template file VB

7 Incoming analysis templates

8 Analysis, analysis process

9 Sample sequence data M 10 Save the sample sequence data

11 Synthesis, synthesis phase

12 target dates Z

13 rough structure

14 fine structure 15 substructure

16 data set

17 (data) element

18 sentence control area

19 element level 20 drawing level

21 data elements

22 data elements

23 data filter

24 links, link rules 25 records

26 records

27 external database

28 Source file

29 Source analysis 30 Target file

Claims

claims

l. Method for converting data and non-file-related methods between two applications or software packages that use different data formats from one another, characterized in that the database of the first application A (3) and the database of the second application B ( 4) a sample export of data records of a relatively small amount is generated, from which a template file VA (5) from application A (3) and a template file VB (6) from application B (4) are formed, of which the An¬ Application B (4) can import the template file VB (6) generated by it, that the template files VA (5) and VB (6) for determining their data structures and possibly for determining the links between the elements by means of conversion software (1) are analyzed, and that the source data Q (2) are converted with the aid of the analysis results into the target data Z (12), which are imported by application B (4).

2. The method according to claim 1, characterized in that the analysis result is stored as a conversion pattern for the transmission of the data of the first user A (3) to the second user B (4) in the form of pattern sequence data M (9) .

^* 3. The process according to claim 1, characterized in that that the source data Q- (2) after passing through the analysis (8) and linking are given in a target synthesis (11), from which they are converted into the target data Z (12).

4. The method according to any one of claims 1 to 3, characterized in that the analysis (8) of the template files VA (5) and VB (6) is divided into several, in particular three phases, the after recognizing the rough structure (13) File form is first pre-classified, then a set of algorithms for automatic recognition of the fine structure (14) is made available by the conversion software and finally, in continuation of the analysis, the substructures (15) are recognized within data elements (17) .

5. The method according to claim 4, characterized in that in the rough structure (13) the files are differentiated according to their file form.

6. The method according to claim 4, characterized in that the fine structure (14) relates to the sentence level, which includes the construction of a sentence (16) from elements (17) and the links of the sentence elements (17) with each other.

7. The method according to claim 4, characterized in that the substructure (15) is subdivided into the element level (19) and in the drawing level (20) with drawing space and number space, wherein in the element level (19) the existential characteristics for an element (17) can be determined.

8. The method according to any one of the preceding claims, ^~ characterized in that in the algorithms for pattern recognition of the language Chen and logical analysis (8) the technologies of neural networks and / or fuzzy logic are used.

9. The method according to any one of the preceding claims, characterized in that a data filter (23) is formed from the analysis (8) of the template files VA (5) and VB (6), which filters the rules of association (24) between the data elements (21, 22) on the file level or together with one or more external data sources (comparison), whereby after data records (25) from application A (3) have passed through the data filter (23), new data records (26) with new ones Data elements (21) are obtained which are in a data format that can be imported and exported by application B (4).

10. The method according to any one of the preceding claims, characterized in that the data elements (21,22) with an external database (27) can be compared.

11. The method according to any one of the preceding claims, characterized in that one or more internal intermediate databases for the search and sorting of data records is set up.

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