WO2022177268A1

WO2022177268A1 - Fragmented data integration device and method

Info

Publication number: WO2022177268A1
Application number: PCT/KR2022/002227
Authority: WO
Inventors: 문재원; 금승우
Original assignee: 한국전자기술연구원
Priority date: 2021-02-18
Filing date: 2022-02-15
Publication date: 2022-08-25
Also published as: KR102457965B1; KR20220118027A

Abstract

The present invention provides a fragmented data integration device comprising: an information addition unit for adding, to heterogeneous fragmented data, a plurality of retrieval information for retrieving the fragmented data; a selection unit for selecting at least one of the plurality of retrieval information; a configuration unit for configuring reference information for the selected retrieval information; a retrieval unit for, with respect to the configured reference information, retrieving, among the heterogeneous fragmented data, the fragmented data that is relevant; and an integration unit for integrating the fragmented data with respect to a time axis.

Description

Fragmental data aggregation device and method

FIELD OF THE INVENTION The present invention relates to an apparatus and method for consolidating fragmentary data.

The present invention is derived from the research conducted as part of the international joint technology development project of the Korea Institute of Industrial Technology Promotion.

[Project unique number] 1415171252

[task number] P0011948

[Ministry name] Ministry of Trade, Industry and Energy

[Name of task management (specialized) institution] Korea Institute of Industrial Technology Promotion

[Research project name] International joint technology development project

[Research project name] Development of layered cloud-edge platform and embedded intelligent service solution for smart livestock

[Contribution rate] 1/1

[Name of project execution organization] Glusys Co., Ltd.

[Research period] 2019.12.01 ~ 2022.11.30

With the development of Internet of Things (IoT) technology and the spread of devices, the types and amounts of data that can be secured are increasing exponentially. Among them, in the case of time series-based data, there are not many open sources of analysis available compared to other data formats such as video, and the difficulty of data preprocessing of raw data is high, so the additional cost for the private sector to extract meaningful insight information is high.

Here, time series-based open sources include distributed processing (Hadoop), observation/collection (telegraf, prometheus), visualization (Grafana, etc.), storage management (InfouxDB, Machbase, Graphite, etc.), analysis prediction (prophet, etc.) Integration optimization of other heterogeneous fragmentary data is not considered.

In addition, although technical research on single time series analysis has been steadily developed, research on algorithms and platforms for searching and integrated analysis of fragmented heterogeneous time series data has been slow.

In addition, until now, time series data analysis has been mainly researched in the direction of increasing the accuracy of the learning model by using the standardized data collected for a predetermined purpose.

In addition, most of the data collected in reality have distinct individual differences for different physical units, resolutions, sizes and formats, and most of them are collected without an agreed purpose. etc.) were collected and utilized individually.

In addition, heterogeneous fragmented data are not interpreted due to their different characteristics and only occupy data space, causing economic loss.

Therefore, it is necessary to select, integrate, and utilize data in the right place at the right time, even if the needs and purposes change for heterogeneous fragmented data collected from different purposes and places.

In order to solve the problems of the prior art as described above, it is an object of the present invention to provide an apparatus and method for integrating fragmentary data that enables a smooth search for a plurality of fragmented data generated in various places and having different characteristics. do it with

In addition, an object of the present invention is to provide a fragmented data search integration and method that can minimize economic loss by integrating and utilizing local fragmentary data that is difficult to use immediately due to different characteristics.

Another object of the present invention is to provide an apparatus and method for integrating fragmentary data that can be created and utilized for a new purpose according to the range and characteristics of the fragmented data to be collected.

In addition, an object of the present invention is to provide an apparatus and method for integrating fragmentary data that can easily select and select fragmentary data collected based on an unspecified purpose and integrate and utilize the fragmentary data.

Another object of the present invention is to provide an apparatus and method for integrating fragmentary data that can identify additional relationships between heterogeneous fragmented data and integrate and utilize a large number of private data and open big data.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. There will be.

In order to solve the above problems, the present invention provides an information adding unit for adding a plurality of search information for searching fragmentary data to heterogeneous fragmentary data, and a selection unit for selecting at least one of the plurality of search information; , a setting unit that sets reference information for the selected search information, a search unit that searches relevant fragmentary data among heterogeneous fragmentary data based on the set reference information, and a method for integrating fragmentary data based on a time axis A fragmentary data aggregation device including an aggregator is provided.

Here, the fragmentary data may include time series data, semi-time series data, and non-time series data.

In addition, the plurality of search information may include at least one of a type of fragmentary data, an acquisition location, an acquisition time, an error, an access level, an attribute, a generation subject, and a reliability.

In addition, the integrator may integrate the fragmentary data searched by the searcher based on at least one of spatial characteristics of an acquisition location, similarity of acquisition time, relevance of generation subjects, and correlation of time series patterns.

In addition, the integrator may integrate the fragmentary data searched by the searcher based on at least one of a purpose of generating the fragmentary data and an issue related to the fragmentary data.

Also, the aggregator may select and integrate the fragmented data based on at least one of a collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit.

In addition, the non-time series data may include acquisition time information.

In addition, the search unit, when the selection unit selects the type and acquisition time of the fragmentary data as the search information, and the setting unit sets the reference time zone as the reference information, it is possible to search the fragment data acquired in the same time zone as the reference time zone.

In addition, the search unit, when the selection unit selects the location of acquisition of fragmentary data as the search information, and the setting unit sets the reference location as the reference information, the fragments acquired from the same location as the reference location or from a place within a certain range based on the reference location You can search enemy data.

In addition, the search unit, when the selection unit selects a subject for generating fragmented data as the search information and the setting unit sets the reference generating subject as the reference information, the same generating subject as the reference generating subject or a generating subject having a certain relationship with the reference generating subject You can retrieve the fragmented data generated by

In addition, the present invention includes the steps of: adding a plurality of pieces of search information for searching fragmentary data to heterogeneous fragmentary data by the information adding unit; selecting at least one of the plurality of pieces of search information by the selection unit; A step of setting reference information for search information, a step of searching for relevant fragmentary data among heterogeneous fragmentary data based on the reference information set by the search unit, and a step of integrating the fragmentary data based on the time axis by the integration unit It provides a method for integrating fragmentary data comprising the steps.

Here, the fragmentary data may include time-series data, semi-time-series data, and non-time-series data, and the plurality of search information includes types of fragmented data, acquisition locations, acquisition times, errors, access levels, attributes, generation subjects, and reliability may include at least one of

In addition, the step of integrating the fragmentary data includes integrating the fragmentary data based on at least one of spatial characteristics of the location of acquisition, similarity of acquisition time, relevance of generating subjects, and correlation of time series patterns for the fragmented data searched by the search unit. It may be a step to

In addition, the step of integrating the fragmentary data may be a step of integrating the fragmentary data searched by the search unit based on at least one of the purpose of generating the fragmentary data and an issue related to the fragmentary data.

In addition, the step of integrating the fragmentary data may be a step of selecting and integrating the fragmentary data based on at least one of a collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit.

According to the present invention, it is possible to seamlessly search for a large number of fragmented data generated in various places and having different characteristics, and it is possible to interpret and predict integrated and individual situations by integrating and analyzing fragmented data with complex interconnectivity. data processing costs can be reduced by linking to decision-making utilization. In addition, it is possible to minimize economic loss by utilizing local fragmented data that is difficult to use immediately due to different characteristics.

In addition, according to the present invention, according to the scope and characteristics of the fragmented data to be collected, it can be created and utilized for a new purpose, and the fragmentary data collected based on an unspecified purpose can be easily selected and utilized, and different types of fragmentary data can be used. Additional relationships between data can be identified. In addition, a large number of private data and open big data can be integrated and utilized.

The effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art from the following description. will be.

1 is a diagram showing the main configuration of a fragmentary data integration apparatus according to an embodiment of the present invention.

2 is a diagram showing the configuration of a control unit of the fragmentary data integration apparatus according to an embodiment of the present invention.

3 is a view for explaining a method for integrating fragmentary data based on a time axis by the fragmentary data integration apparatus according to an embodiment of the present invention.

4 is a view for explaining a method for analyzing the cause of indoor air quality and predicting a future situation using the fragmentary data integration device according to an embodiment of the present invention.

5 is a view for explaining a method of analyzing the effect of a specific home appliance on a living body using the fragmentary data integration device according to an embodiment of the present invention.

6 is a flowchart of a method for integrating fragmentary data according to an embodiment of the present invention.

In order to fully understand the configuration and effect of the present invention, preferred embodiments of the present invention will be described with reference to the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, and may be embodied in various forms and various modifications may be made. However, the description of the present embodiment is provided so that the disclosure of the present invention is complete, and to fully inform those of ordinary skill in the art to which the present invention pertains the scope of the invention. In the accompanying drawings, components are enlarged in size than actual for convenience of description, and ratios of each component may be exaggerated or reduced.

Terms such as 'first' and 'second' may be used to describe various elements, but the elements should not be limited by the above terms. The above term may be used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a 'first component' may be termed a 'second component', and similarly, a 'second component' may also be termed a 'first component'. can Also, the singular expression includes the plural expression unless the context clearly dictates otherwise. Unless otherwise defined, terms used in the embodiments of the present invention may be interpreted as meanings commonly known to those of ordinary skill in the art.

As shown in FIG. 1 , the fragmentary data integration device 100 according to the present invention includes a communication unit 110 , an input unit 120 , a display unit 130 , a memory 140 and a control unit 150 . can be

The communication unit 110 may communicate with an external device such as a server (not shown) to receive different types of fragmentary data. To this end, the communication unit 110 is ^5th generation communication (5G), long term evolution-advanced (LTE-A), long term evolution (LTE), Bluetooth, bluetooth low energe (BLE), near field communication (NFC), etc. of wireless communication, and wired communication such as cable communication may be performed.

The input unit 120 generates input data in response to a user's input. The input unit 120 includes at least one input means. The input unit 120 includes a keyboard, a keypad, a dome switch, a touch panel, a touch key, a mouse, a menu button, etc. may include.

The display unit 130 displays search information and reference information related to the operation of the fragmentary data aggregation apparatus 100 , and displays the fragmented data searched and integrated by the fragmentary data aggregation apparatus 100 .

As such, the display unit 130 includes a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, and a micro electro mechanical system (MEMS). systems) displays and electronic paper displays. Also, the display unit 130 may be combined with the input unit 120 to be implemented as a touch screen.

The memory 140 stores operation programs of the fragmentary data aggregation apparatus 100 . In addition, the memory 140 may store various algorithms related to fragmentary data search and integration, and the memory 140 may store a plurality of fragmented data received from an external device.

The controller 150 may perform a series of operation processes for searching and integrating fragmentary data using an operation program and an algorithm stored in the memory 140 .

The fragmentary data integration apparatus 100 according to an embodiment of the present invention easily and efficiently searches for relevant fragmentary data at the right time and place according to needs and purposes for fragmentary data collected at different purposes and places, and In other words, it is possible to integrate and utilize relevant fragmentary data.

Referring to FIG. 2 , the control unit 150 of the apparatus 100 for integrating fragmentary data according to an embodiment of the present invention includes an information adding unit 151 , a selection unit 152 , a setting unit 153 , and a search unit ( 154) and the integration unit 155 may be included.

The information adding unit 151 may add a plurality of pieces of search information for searching fragmentary data related to each other to the fragmentary data of different types.

Here, heterogeneous fragmentary data is data having different characteristics generated by various generating entities in various places, and may mean local and incomplete data collected with different rights.

Such fragmentary data may include time series data, semi-time series data, and non-time series data.

Unlike general data, time series data includes time information, and time itself is a very important criterion.

Most of the sensor data of the IoT (Internet of Things) sensor is collected based on a certain time interval. Here, the image data includes time information according to the content flow, but does not include acquisition time information, so it is non-time series data.

In addition, event data for recognizing an event (door opening/closing, etc.) is non-time-series data because it is non-periodic data that is collected according to the occurrence of an event situation, not data acquired at regular intervals.

In addition, text-oriented issue data such as news can utilize time information at the time the issue occurred, but it is mostly non-time series data because it is stored and interpreted based on the issue itself rather than time information.

Biometric data can be defined as time series data, but because it is collected as needed (Cross-Sectional Data), it is stored in the form of fragmented data collected for a short period of time.

The plurality of search information may include at least one of a type of fragmentary data, an acquisition location, an acquisition time, an error, an access level, an attribute, a generation subject, and a reliability.

The selection unit 152 may select at least one of a plurality of pieces of search information. That is, the selection unit 152 may select at least one of a type of fragmentary data, an acquisition location, an acquisition time, an error, an access level, an attribute, a generation subject, and a reliability.

Here, the type of fragmentary data means whether the fragmentary data corresponds to time series data, semi-time series data, and non-time series data, and may be utilized when integrating fragmentary data in the future.

In addition, the location of the fragmented data acquisition means the unique location where the fragmented data was acquired, and it can be utilized when integrating the fragmentary data in the future.

In addition, with respect to the acquisition time of fragmentary data, time series data naturally contains time information, so there is no problem, but non-time series data does not contain time information. have.

In addition, with respect to the error of the fragmentary data, it is possible to estimate the error rate of the integrated data generated by integrating the fragmentary data in the future by adding information about when an abnormality occurred in the data to the fragmentary data.

In addition, by adding the access level of the fragmented data to the fragmented data, it is possible to check the access authority of the data and to check and manage whether it is possible to integrate when the fragmented data is integrated. Here, the access level can also be linked to paying for data usage.

In addition, the properties of fragmentary data may include numeric, character, and categorical types, and if it is necessary to perform operations with other data after fragmentary data is integrated in the future, this should be considered. can

In addition, the subject of generating fragmentary data may include a producer, generating household, generating country, and generating device. If this is added as search information, fragmentary data related to the generating subject can be searched.

In addition, with respect to the reliability of the fragmentary data, the reliability of the integrated data generated by integrating the fragmentary data in the future may be estimated by adding the reliability to the fragmentary data.

The setting unit 153 may set reference information for the search information selected by the selection unit 152 . That is, the setting unit 153 may set a reference location for the location of acquisition of fragmentary data, and set a reference time zone (eg, specific time zone, specific day, specific month, and specific season) for the acquisition time of fragmentary data. and it is possible to set a standard generating entity (eg, a specific device, a specific user, and a specific country) for the subject of generating fragmentary data.

The search unit 154 may search for and collect fragmentary data related to each other among heterogeneous fragmentary data based on the reference information set by the setting unit 153 .

Specifically, the search unit 154, when the selection unit 152 selects the type and acquisition time of fragmentary data as the search information, and the setting unit 153 sets the reference time zone as the reference information, the set reference time zone and Fragmental data acquired in the same time period can be retrieved.

In addition, the search unit 154, when the selection unit 152 selects the location of acquisition of fragmentary data as the search information, and the setting unit 153 sets the reference location as the reference information, the same location as the set reference location or It is possible to search for fragmentary data acquired from a place within a certain range based on the reference place.

In addition, when the selection unit 152 selects the generation subject of fragmentary data as the search information and the setting unit 153 sets the reference generation entity as the reference information, the search unit 154 generates the same generation as the set reference generation entity. Fragmental data generated by a subject or a generating subject that has a certain relationship with the reference generating subject can be retrieved.

Meanwhile, the selection unit 152 may select a plurality of pieces of search information, and the setting unit 153 may set reference information for each search information. Accordingly, the search unit 154 may search for and collect relevant fragmentary data based on a plurality of pieces of reference information. For example, the selection unit 152 may select an acquisition time and place of the fragmentary data as the search information, and the setting unit 153 may set a reference time zone and a reference place for the acquisition time and place. Accordingly, the search unit 154 may search for and collect relevant fragmentary data based on the reference time zone and the reference location.

As such, the fragmentary data searched for by the search unit 154 may be integrated and analyzed in the future, thereby improving the data utilization value of the fragmentary data.

The display unit 130 visualizes and displays the fragmentary data retrieved by the search unit 154 based on the reference information to determine the possibility of integrating the fragmentary data.

The integration unit 155 integrates the fragmentary data searched by the search unit 154 based on the time axis.

Referring to FIG. 3 , the degree of time series is large in the order of issue data, image data, event data, biometric data, and sensor data. Accordingly, the integrator 155 may integrate the fragmentary data based on the time-series characteristics of the fragmented data.

For example, the integrator 155 may integrate different sensor data having a relatively high degree of time series. In addition, it is also possible to integrate sensor data and issue data with a relatively small degree of time series. In this case, since the issue data may include acquisition time information by the information adding unit 151 , the integrator 155 may integrate the sensor data and the issue data only in a time zone in which the acquisition time is the same.

The integrator 155 integrates the fragmented data retrieved by the search unit 154 based on at least one of spatial characteristics of the acquisition location, similarity of acquisition time, relevance of generating subjects, and correlation of time series patterns. can do.

In addition, the integrator 155 may integrate the fragmentary data searched by the searcher 154 based on at least one of a purpose of generating the fragmentary data and an issue related to the fragmentary data.

On the other hand, the fragment data searched by the search unit 154 is not only different in quantity and quality, but also different in collection period and collection period.

Accordingly, the aggregator 155 may select and integrate the fragmented data based on at least one of a collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit 154 . For example, the aggregation unit 155 may integrate fragmentary data having similar collection period, data amount, data quality, and collection period among the fragmentary data searched by the search unit 154 .

The integrator 155 may estimate an error rate of the integrated data by using the error added to the fragmentary data, and may integrate the fragmented data to generate integrated data having the smallest error rate.

In addition, the integrator 155 may estimate the reliability of the integrated data using the reliability added to the fragmented data, and may integrate the fragmented data to generate integrated data with the highest reliability.

The fragmentary data integration apparatus 100 according to the above-described embodiment of the present invention enables a smooth search for a plurality of fragmented data generated in various places and having different characteristics, and is a fragmentary data unit with complex interconnectivity. By integrating data analysis, it is possible to interpret and predict aggregated and disparate situations, and to link to decision-making utilization, thereby reducing the cost of data processing. In addition, it is possible to minimize economic loss by utilizing local fragmented data that is difficult to use immediately due to different characteristics.

4 is a view for explaining a method for analyzing a cause of indoor air quality and predicting a future situation using the fragmentary data integration device according to an embodiment of the present invention.

Referring to FIG. 4 , indoor air quality meters are provided inside a plurality of furniture, respectively, to measure indoor air quality to generate indoor air quality data H1 , H2 , and H3 . Data that can be associated with indoor air quality data (H1, H2, H3) to analyze causes of indoor air quality and predict future situations include outdoor air quality data (A1, A2) and weather data (W) provided by the public. can Here, the outdoor air quality data (A1, A2) and weather data (W) are measured and disclosed by devices sporadically installed in various specific areas nationwide, so anyone can freely use them.

At this time, in order to analyze the causes of indoor air quality (H1, H2, H3) and predict the future situation, search for and generate outdoor air quality data (A1, A2) and weather data (W) measured and generated at the location closest to each household. It must be collected, processed and used.

To this end, the fragmentary data integration apparatus 100 according to an embodiment of the present invention sets the acquisition location and time of the fragmentary data to search for the fragmented data, thereby measuring and generating the outdoor measured and generated at the location closest to individual households. Air quality data (A1, A2) and weather data (W) can be searched easily and efficiently, and by integrating these data into indoor air quality data (H1, H2, H3) on a time axis and analyzing the cause of indoor air quality and future situation can be predicted.

4 is a view for explaining a method of analyzing the effect of a specific home appliance on a living body using a fragmentary data integration device according to an embodiment of the present invention.

Referring to FIG. 4 , a specific piece of furniture may have two separate first and second spaces, and one IoT sensor is provided inside the first space to generate the first environmental data R1 and the second space. Two IoT sensors are provided inside to generate second and third environment data R2 and R3. In addition, the first to third members constituting a specific household carry devices that generate biometric data P1 , P2 , and P3 by measuring individual biometric conditions.

Here, when the first member is inside the first space (R1), and the second and third members are inside the second space (R2), the specific home appliance in the first space (R1) is the first member's In order to analyze the effect on the living body, the data that can be associated with the biometric data P1 is the first environmental data R1, and a specific home appliance in the second space R2 affects the living body of the second and third members. Data that may be associated with the biometric data P2 and P3 in order to analyze the effect is the second and third environmental data R2 and R3.

Here, the fragmentary data integration device 100 according to an embodiment of the present invention sets the acquisition location and time of fragmentary data to search for fragmentary data, so that an IoT sensor located in a space with individual members is measured and generated One environment data can be easily and efficiently searched, and the effect of a specific home appliance on the living body can be efficiently analyzed by integrating the retrieved environmental data with the biometric data on a time axis and analyzing it.

The fragmentary data aggregation apparatus 100 according to an embodiment of the present invention may search for and integrate fragmentary data in consideration of an access level of the fragmentary data.

For example, it is possible to provide a new service by integrating image data (ie, time series data about people who visited a place by time) acquired from a plurality of CCTVs installed in one area and public data on weather and traffic. If the conditions for disclosing the corresponding data (eg, payment and policy authority, etc.) are different depending on the owner of each CCTV, the service provider can selectively search and integrate only fragmented data that meets the conditions.

In addition, the fragmentary data aggregation apparatus 100 according to an embodiment of the present invention can efficiently search and integrate fragmented data related to each other by selecting search information and setting reference information based on various cases.

According to the fragmentary data integration apparatus 100 according to the embodiment of the present invention described above, it can be generated and utilized for a new purpose according to the range and characteristics of the fragmented data to be collected, and the fragmented data collected based on an unspecified purpose can be easily selected and utilized, and additional relationships between heterogeneous fragmentary data can be identified. In addition, a large number of private data and open big data can be integrated and utilized.

Hereinafter, a fragmentary data integration method according to an embodiment of the present invention will be described with reference to FIGS. 1 to 6 , but the same contents as those described above will be omitted.

In the fragmentary data integration method according to an embodiment of the present invention, first, the information adding unit 151 adds a plurality of pieces of search information for searching fragmentary data to heterogeneous fragmentary data (S10). Here, the fragmentary data includes time series data, semi-time series data, and non-time series data. And, the non-time series data includes acquisition time information. In addition, the plurality of search information includes at least one of a type of fragmentary data, an acquisition location, an acquisition time, an error, an access level, an attribute, a generation subject, and reliability.

Next, the selection unit 152 selects at least one of the plurality of search information (S20).

Next, the setting unit 153 sets reference information for the selected search information (S30).

Next, the search unit 154 searches for relevant fragmentary data among heterogeneous fragmentary data based on the set reference information (S40).

Here, the step (S40) of searching for fragmentary data is a step (S30) of selecting the type and acquisition time of the fragmentary data as the search information in the step (S20) of selecting the search information, and setting the reference time period (S30). If the reference time zone is set as information, fragmentary data acquired in the same time zone as the reference time zone is retrieved.

In addition, the step (S40) of retrieving the fragmentary data is, in the step (S20) of selecting the search information, an acquisition location of the fragmentary data as the search information, and as the reference information in the step (S30) of setting the reference information When the reference location is set, the fragmented data acquired from the same location as the reference location or from a location within a certain range based on the reference location is searched.

In addition, the step of searching for fragmentary data (S40) is to select the subject of generation of fragmentary data as the search information in the step (S20) of selecting the search information, and as the reference information in the step (S30) for setting the reference information When the reference generating subject is set, the fragmented data generated by the same generating subject as the reference generating subject or by the generating subject having a certain relationship with the reference generating subject is retrieved.

Next, the integration unit 155 integrates the fragmentary data retrieved by the search unit 154 based on the time axis (S50).

Here, in the step (S50) of integrating the fragmentary data, at least one of the spatial characteristics of the location of acquisition, the similarity of acquisition time, the relation of the generating subject, and the correlation of the time series pattern, of the fragmented data searched by the search unit 154 Integrate fragmentary data as a baseline.

In addition, in the step of integrating the fragmentary data (S50), the fragmentary data searched by the search unit 154 is integrated with the fragmentary data based on at least one of the purpose of generating the fragmentary data and the issues related to the fragmentary data. do.

In addition, the step of integrating the fragmentary data ( S50 ) includes selecting and integrating fragmentary data based on at least one of the collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit 154 . do.

The fragmentary data integration method according to the embodiment of the present invention described above enables a smooth search for a plurality of fragmented data generated in various places and having different characteristics, and integrates the fragmentary data with complex interconnectivity. By analyzing, it is possible to interpret and predict holistic and discrete situations, and link them to decision-making utilization, thereby reducing the cost of data processing. In addition, it is possible to minimize economic loss by utilizing local fragmented data that is difficult to use immediately due to different characteristics.

In addition, the fragmentary data integration method according to an embodiment of the present invention can be created and utilized for a new purpose according to the range and characteristics of the fragmented data to be collected, and the fragmentary data collected based on an unspecified purpose can be easily selected It can be used by doing this, and additional relationships between heterogeneous fragmentary data can be identified. In addition, a large number of private data and open big data can be integrated and utilized.

In the detailed description of the present invention, although specific embodiments have been described, various modifications are possible without departing from the scope of the present invention. Therefore, the scope of the present invention is not limited to the described embodiments, and should be defined by the following claims and their equivalents.

The fragmentary data integration apparatus and method according to the present invention can be used in various industrial fields such as data collection, search and utilization.

Claims

an information adding unit for adding a plurality of pieces of search information for searching the fragmentary data to heterogeneous fragmentary data;

a selection unit for selecting at least one of the plurality of pieces of search information;

a setting unit for setting reference information for the selected search information;

a search unit that searches for the relevant fragmentary data among the different types of fragmentary data based on the set reference information; and

Integration unit that integrates the fragmentary data based on the time axis

A fragmented data aggregation device that includes.
The method of claim 1,

The fragmented data

time series data, semi-time series data, and non-time series data.

Fragmental data aggregation device.
3. The method of claim 2,

The plurality of search information is

including at least one of a type of the fragmented data, a location of acquisition, a time of acquisition, an error, an access level, an attribute, a creation subject, and a reliability

Fragmental data aggregation device.
4. The method of claim 3,

The integrator

Integrating the fragmentary data based on at least one of spatial characteristics of the acquisition location, the similarity of the acquisition time, the relevance of the generating subject, and the correlation of time series patterns for the fragmentary data searched by the search unit

Fragmental data aggregation device.
The method of claim 1,

The integrator

Integrating the fragmentary data searched by the search unit based on at least one of a purpose of generating the fragmentary data and an issue related to the fragmentary data

Fragmental data aggregation device.
The method of claim 1,

The integrator

Selecting and integrating the fragmentary data based on at least one of a collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit

Fragmental data aggregation device.
4. The method of claim 3,

The non-time series data is

Acquisition time information

Fragmental data aggregation device.
8. The method of claim 7,

the search unit

When the selection unit selects the type and acquisition time of the fragmentary data as the search information, and the setting unit sets the reference time period as the reference information,

retrieving the fragmentary data acquired in the same time zone as the reference time zone

Fragmental data aggregation device.
4. The method of claim 3,

the search unit

When the selection unit selects a location for acquiring the fragmentary data with the search information, and the setting unit sets a reference location with the reference information,

retrieving the fragmented data acquired from the same place as the reference place or from a place within a certain range based on the reference place

Fragmental data aggregation device.
4. The method of claim 3,

the search unit

When the selection unit selects the generation subject of the fragmentary data as the search information, and the setting unit sets the reference generation entity as the reference information,

retrieving the fragmented data generated by the same generating subject as the reference generating subject or by the generating subject having a certain relationship with the reference generating subject

Fragmental data aggregation device.
adding, by an information adding unit, a plurality of pieces of search information for searching the fragmentary data to heterogeneous fragmentary data;

selecting, by a selection unit, at least one of the plurality of pieces of search information;

setting, by a setting unit, reference information for the selected search information;

retrieving the relevant fragmentary data from among the heterogeneous fragmentary data based on the reference information set by a search unit; and

Integrating the fragmentary data based on the time axis by the integration unit

A method of integrating fragmentary data, including
12. The method of claim 11,

The fragmented data

time series data, semi-time series data, and non-time series data.

The plurality of search information is

including at least one of a type of the fragmented data, a location of acquisition, a time of acquisition, an error, an access level, an attribute, a creation subject, and a reliability

Fragmental data integration methods.
13. The method of claim 12,

The step of integrating the fragmentary data is

Integrating the fragmentary data based on at least one of the spatial characteristics of the acquisition location, the similarity of the acquisition time, the relation of the generating subject, and the correlation of the time series pattern with the fragmentary data searched by the search unit

Fragmental data integration methods.
12. The method of claim 11,

The step of integrating the fragmentary data is

The step of integrating the fragmentary data retrieved by the search unit based on at least one of a purpose of generating the fragmentary data and an issue related to the fragmentary data

Fragmental data integration methods.
12. The method of claim 11,

The step of integrating the fragmentary data is

Selecting and integrating the fragmented data based on at least one of a collection period, data amount, data quality, and collection period of the fragmented data searched by the search unit

Fragmental data integration methods.