JP2001344140A - Common information collation system between independent system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a very innovative common information collation system between independent systems capable of reducing labor for checking allowable disagreement due to a difference of work purposes and allowing smooth collation update by a simple structure. SOLUTION: Because some information included in data (a) of one system A may always disagree with that included in data b of the other system B, the other system B stores contents taken in once when data at1 of one system A at a predetermined time point t1 are taken in. In collation at the following predetermined time point t2, the stored data at1 taken in to be stored are compared with data at2 of one system A in this following collation, and only the generated disagreement part is extracted so as to be used as collation data c. The collation data c is collated with the data b of the other system B, and confirmation is carried out about only the disagreement part.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The present invention relates to an information processing system in which, when independent systems have different information update timings and have common information between the systems, one of the data is used to match unmatched data. The section relates to a collation method of common information between independent systems that corrects data by judging that it is true and performs a smooth collation update.

[0002]

2. Description of the Related Art In a case where a plurality of independent systems having predetermined information have different information update timings from each other and have common information among the systems, one of the systems has a different information. A and the other system B have common information and the information of the one system A is new, so that the other system B takes in the data a created by the one system A, and After extracting and confirming information that does not match the data b of B, the data of the other system B is corrected.

For example, the one system A has business data a, the other system B has business data b, and the business of the one system A and the business of the other system B are different. Since the business purpose is different, the data a of one system A is
Cannot be reflected on the data b of the system A, and the data a of the one system A and the data b of the other system B may include information that always becomes inconsistent.

In this case, data correction is performed so that the latest information of one system A is sequentially used to update the information of the other system B. At this time, the data a of one system A is taken in and the other data is acquired. The data b of the other system B is corrected as the data to be updated for the common data between the systems, so that the data b is corrected. For this reason, it is necessary to perform a confirmation / correction process of ignoring the inconsistent portion that is required. At this time, since the system B does not perform data correction for the inconsistency to be corrected, the inconsistency remains in the future. Therefore, the "inconsistent to be corrected" is extracted for each collation. And the amount of work for confirming the update increases.

[0005] The present invention finds such a problem in the collating and updating operation between the systems, and proposes a revolutionary independent information collating method between independent systems which solves this problem with a simple system configuration. It is intended to provide.

[0006]

The gist of the present invention will be described with reference to the accompanying drawings.

When a plurality of independent systems having predetermined information have different information update timings and have common information between the systems, if one system A and the other system B have common information, And the information of the one system A is newer than the information of the other system B, the other system B fetches the data created by the one system A, and the other system B In the collation method of common information between independent systems that performs data correction of the other system B after extracting and confirming information that does not match the data of the one system A, the one system A has business data a, The other system B has business data b, and the business purpose of the one system A is different from the business purpose of the other system B. From the data a of one system A
Cannot be directly reflected in the data b of the other system B, and the data a of the one system A and the data b of the other system B may include information that always does not match. When the data at1 at the predetermined time t1 of the one system A is fetched, the once fetched contents are stored, and at the time of the next verification at the predetermined time t2, the fetched stored data at1 and this next time are compared. Data at2 of one system A in the collation of
The system is configured to extract only the inconsistency that has occurred and to use this as collation data c, collate this collation data c with the data b of the other system B, and confirm only the inconsistency. Thus, the labor of compensating the data of the other system B at the time of collation can be saved, and the data a of the one system A that has not been changed from the time point t1 to the time point t2 can be ignored. The present invention relates to a method for collating common information between independent systems, characterized in that it is sufficient to confirm only the data that has changed in A.

Also, since there is common information between the one system A and the other system B, and the information of the one system A is newer than the information of the other system B, the other system A B takes in the data created by the one system A, extracts and confirms information that does not match the data of the other system B, and then performs data correction of the other system B at a predetermined time t2. When collating one system A with the other system B, first, the data at2 of this one system A
Is compared with the stored data at1 of one system A stored at the time of the previous comparison at the predetermined time t1, and the data of the generated mismatch is referred to as the comparison data c. By comparing the data b of the system B with the data b of the system B for the common data between the systems A and B, the confirmation / correction processing of rewriting and correcting the data b of the system B and disregarding the inconsistent data is performed. The present invention relates to a method for collating common information between independent systems according to claim 1, characterized in that it is possible to reduce the labor required for confirming the inconsistency.

[0009]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the present invention (how to implement the invention) will be briefly described with reference to the drawings, showing the operational effects thereof.

The present invention constitutes a so-called "two-step collation method" with respect to the conventional simple collation method. In a case where an independent system collates common information possessed by another system, a "mismatch is determined." This is an effective method that can ignore the inconsistency in such a case.

[0011] (1) One system A has business data a, and the other system B, which automatically corrects using this data a, has business data b for a different purpose.

(2) The system A frequently updates data, and the data a always holds new information.

(3) In system B, the frequency of data update is lower than in system A (the interval of information update timing is large), and information tends to be outdated.

(4) Since the data a and the data b have common information, if the data a, which is the latest data, can be reflected on the data b, labor for maintaining the data b can be saved.

(5) The business purpose of the system A is different from the business purpose of the system B. Therefore, the data a of the system A cannot be directly reflected on the data b of the system B. Contains information that is always inconsistent (desirable inconsistency).

For example, under the preconditions (1) to (5), the following two-step collation update is performed as shown in FIG.

(1) System B is system A at time t1
When the data “a” is captured, the captured content is saved. This stored content is referred to as data at1.

(2) In the next collation (t2 in the future from the time t1), collation of the data at1 and the data at2 is performed while the data at2 is taken in. At the next collation, at2 taken in this time is used as at1.

(3) As a result of the collation () of the data at 1 and the data at 2, only the inconsistency that occurs is extracted from at 1 and is referred to as collation data c.

(4) The collation data c and data b need to be collated (), and only the unmatched portion needs to be confirmed, so that labor for correction can be saved.

That is, the two-step collation method is adopted, the collation data c is collated with the data b of the other system B, and the common data between the systems A and B is compared with the data of the system B for the unmatched part. By performing a check and correction process of rewriting and correcting b, and disregarding non-coincidence data, data that has not changed in data a of system A between time t1 and time t2 is ignored. It is only necessary to confirm the data that has changed on the system A side, the independence between the systems increases, and the trouble of confirming the "mismatch" that arises due to the difference in business purpose is reduced. Labor savings can be achieved.

[0022]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Specific embodiments of the present invention will be described with reference to the drawings.

In the present embodiment, the two-step verification method of the present invention is applied to the basic resident register verification processing and the land tax ledger verification processing of the functions of the comprehensive information management system for farmland and the like. Method for collating common information between independent systems that can realize smooth collation under the condition that the information (data a of system A) held by the system does not always match the information (data b of system B) held by the agricultural committee And

Hereinafter, this embodiment will be described.

The agriculture committee needs to properly manage the information of the farmland and the farmhouse by using the "Land of Farmland / Farmhouse Basic Ledger". Agricultural land law Articles 3, 4, 5 to 20 and the Law on Strengthening the Agricultural Management Base were allowed to obtain appropriate information on the permission and notification related to the agricultural land law through the Agricultural Committee. There is a problem in that it is difficult to grasp information on transfer of rights such as name change due to the transfer of information on the "person" of a farm household without going through the Agricultural Committee. In order to improve these problems, the matching process reads information that cannot be grasped by the Agriculture Committee from the municipalities' fixed property tax book (land tax book) and computerized information on the basic resident register, and compares the information with the contents of the farmland / farmhouse basic ledger. By performing the collation, a list is created for an inconsistency that is considered to have caused a change, and ledger data correction processing is performed.

For example, "Housekeeping differs between the Basic Resident Register and the Basic Farmer Ledger.""The owner on the farmland registry has died, and another owner is different from the management of the business area on the farmland ledger. Despite being changed to a new owner on the farm land register with the permission of Article 3 of the Agricultural Committee, the old owner remains on the register without being registered. " There is no such thing as an orchard, and ordinary fields and orchards are both 'fields'. This is a major cause of the unmatch that the basic resident register and land tax book do not always match the basic land for land and farmers, and the Agricultural Committee's ledger, tax book and resident register are mutually exclusive. It is an indispensable unmatch, which is made for fulfilling the business purpose of the company, and it cannot be unified into one of the ledgers just because it is unmatched. Extraction and output of such an “indispensable unmatch” (a disagreement to be sure) every time the matching process is executed leads to an increase in the number of unmatches = an increase in confirmation work, which is a great obstacle to the matching process. To cope with this problem, the "farmland information system" employs the "two-stage matching method" of the present invention.

That is, the contents of the previous registration of the resident registry and the tax register are compared with each other, and only the data changed between the resident registry and tax is compared with the register of the farmland information system.

This farmland information system corresponds to the system B of the present invention, and performs a collation process with a residence register and a tax ledger relating to the system A to be used. For example, a birth list, a transference list, and an owner change List, land area change list,
It has a list of changes in grounds, a list of transfers, a list of deaths, a list of new establishments, a list of deletions, and a list of diversions.

In the two-step matching, "the common layout data to be compared this time is compared with the common layout data which has been imported at the time of the previous matching". Data that has not been changed since the previous matching on the basic ledger or land tax ledger side ”can be excluded from the matching target.

After extracting only "data that has really changed in the basic resident register or tax book" from the previous collation, as unmatch candidates, only that data is to be collated with the ledger of the farmland information system.

Therefore, unmatching (mismatch) occurs in large quantities at the time of the first matching because of direct matching, but after the second matching, only the pure change information of the resident registry and the taxing side is compared with the matching data c.
Can be set as a collation target.

It is to be noted that, for example, the conditions for collating the Juki common file with the individual / household information of the “farmland information system” are set, the code for specifying the individual is selected, and whether the collation is performed or ignored is set. It is possible.

In addition, items to be compared and items not to be compared can be selected by the "matching selection item".
It is clear that "items that cannot be maintained by the resident registry or the taxing side" and "items that have distinctly different code systems in the resident registry, taxation and farmland, and the basic register of farmers" will be unmatched. By specifying outside, a meaningless unmatch may be excluded and only necessary items may be collated.

[0034]

According to the present invention, as described above,
A step-by-step collation method is adopted, the collation data c is collated with the data b of the other system B, and the data b of the system B is rewritten and corrected for the common data between the systems A and B with respect to the mismatched part. The non-coincidence data is ignored and the confirmation / correction processing is ignored, so that t2
Until the time point, the data that has not changed in the data a of the system A can be ignored, and only the data that has changed on the system A side needs to be confirmed.
Independence between each other's systems is increased, labor for confirming the "mismatch" that arises due to differences in business objectives can be reduced, and a simple configuration allows for smooth reconciliation and extremely innovative independence. It becomes a collation method of the common information between the systems that have been set.

[Brief description of the drawings]

FIG. 1 is a schematic explanatory diagram of the present embodiment.

Claims (2)

[Claims] When a plurality of independent systems having predetermined information have different information update timings and have common information among the systems, one system A and the other system B are connected to each other. Have the same information and the information of the one system A is newer than the information of the other system B, the other system B takes in the data created by the one system A, and In a collation method of common information between independent systems that performs data correction of the other system B after extracting and confirming information that does not match the data of the system B, the one system A has business data a. The other system B has business data b, and the business purpose of the one system A is different from the business purpose of the other system B. Therefore, the data a of one system A cannot be directly reflected in the data b of the other system B, and the data a of the one system A and the data b of the other system B are always inconsistent. Therefore, when the other system B captures the data at1 at the predetermined time point t1 of the one system A, the system B stores the once captured content, and performs the next verification at the predetermined time point t2. The captured stored data at1 and the data at of the one system A in the next verification are compared.
2 is compared, and only the inconsistency generated is extracted and used as collation data c. This collation data c is collated with the data b of the other system B, and only the inconsistency is confirmed. In order to save the labor of correcting the data of the other system B at the time of collation, the data a of the one system A that has not changed during the time from the time point t1 to the time point t2 is ignored. A method for collating common information between independent systems, characterized in that it is only necessary to confirm data that has changed in system A. 2. The one system A and the other system B have common information, and the information of the one system A is newer than the information of the other system B. B is the one system A
When the data created in step (2) is imported, and information that does not match the data of the other system B is extracted and confirmed, and then the data correction of the other system B is performed, a predetermined time t2
When comparing the one system A with the other system B, first, the data at2 of the one system A and the storage of the one system A that were saved at the time of the previous comparison at the predetermined time t1. The data at1 is collated, and the data of the disagreement generated is referred to as collation data c. The collation data c is collated with the data b of the other system B. , The data b of the system B is rewritten and corrected, and a check / correction process is performed to ignore the mismatch data to be corrected, thereby saving labor for checking the mismatch to be corrected. A method for collating common information between independent systems according to claim 1.