Analysis system, analysis method, and analysis program

Abstract

To provide an analytical system, analytical method, and analytical program that enable experimenters to utilize the knowledge they have gained in their experiments. [Solution] The analysis system 1 described herein comprises an analysis target data acquisition unit 111, a text acquisition unit 112, an extraction unit 113, and an analysis unit 114. The analysis target data acquisition unit 111 acquires analysis target data, which is at least one of measurement data obtained by measuring a sample and numerical data related to the sample. The text acquisition unit 112 acquires text data recording the experimental details of the sample. The extraction unit 113 extracts information related to the experimental details from the text data. The analysis unit 114 performs analysis based on the analysis target data and the extracted information.

Description

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Technical Field

[0001] The present disclosure relates to an analysis system, an analysis method, and an analysis program.

Background Art

[0002] Patent Document 1 describes a data analysis system that analyzes measurement data obtained by analyzing materials. The data analysis system described in Patent Document 1 receives measurement data via a communication device, processes the measurement data using a learned machine learning model, and outputs an analysis result.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, experimenters and developers obtain various findings in experiments. Such findings may contain important information in analysis. However, it is difficult to incorporate such findings into analysis. Therefore, in the analysis system according to the prior art, such findings have not been fully utilized.

[0005] That is, in the analysis system according to the prior art, there is a problem that the findings obtained by the experimenter in the experiment cannot be fully utilized. Patent Document 1 does not disclose a technique capable of solving such a problem.

[0006] The present disclosure has been made to solve such problems, and an object thereof is to provide an analysis system, an analysis method, and an analysis program capable of utilizing the findings obtained by an experimenter in an experiment.

Means for Solving the Problems

[0007] The analysis system described herein comprises an analysis target data acquisition unit, a text acquisition unit, an extraction unit, and an analysis unit. The analysis target data acquisition unit acquires analysis target data, which is at least one of measurement data obtained by measuring a sample and numerical data related to the sample. The text acquisition unit acquires text data recording the experimental details of the sample. The extraction unit extracts information related to the experimental details from the text data. The analysis unit performs analysis based on the analysis target data and the extracted information.

[0008] With this configuration, the analysis system according to this embodiment can acquire the knowledge gained by the experimenter as text data. As a result, the analysis system according to this embodiment can utilize the knowledge gained by the experimenter in the experiment.

[0009] In the analysis system relating to this disclosure, the extracted information may include at least one of the following: information regarding the experimental conditions of the sample and information regarding the physical properties of the sample.

[0010] In the analysis system relating to this disclosure, the extraction unit may extract items relating to at least one of the following: information relating to the experimental conditions of the sample and information relating to the physical properties of the sample.

[0011] In the analysis system relating to this disclosure, if the extraction unit extracts items related to the physical properties of a sample, the degree of said item may be quantified for each sample.

[0012] In the analysis system relating to this disclosure, when the extraction unit extracts items related to the physical properties of a sample, it may quantify the degree of such physical properties by assigning a first predetermined value to samples that exhibit such physical properties and a second predetermined value to samples that do not exhibit such physical properties.

[0013] The analysis system relating to this disclosure may further include a reception unit that receives item specifications from the user. The analysis unit may then evaluate the correlation between the received item specifications and the data to be analyzed.

[0014] The analysis system relating to this disclosure may further include an unknown data acquisition unit that acquires unknown data, which is the data to be analyzed from an unknown sample. The extracted information may also include information about the physical properties of the sample, and the analysis unit may predict the physical properties of the unknown sample based on the unknown data, the data to be analyzed, and the extracted information.

[0015] In the analysis system relating to this disclosure, the text acquisition unit may acquire image data of a paper document recording the experimental content, process the acquired image data to convert the characters written on the paper document into text data, and acquire the converted text data as text data recording the experimental content of the sample.

[0016] The analysis method related to this disclosure performs the following steps. Analytical data is obtained, which consists of at least one of the measurement data obtained by measuring the sample and numerical data related to the sample. Retrieve text data related to the sample. Extract relevant information about the sample from the text data. The analysis is performed based on the data to be analyzed and the extracted information.

[0017] The analysis program described herein causes the computer to perform the following actions: Analytical data is obtained, which consists of at least one of the measurement data obtained by measuring the sample and numerical data related to the sample. Retrieve text data related to the sample. Extract relevant information about the sample from the text data. The analysis is performed based on the data to be analyzed and the extracted information. [Effects of the Invention]

[0018] According to the present disclosure, an analysis system, an analysis method, and an analysis program that can utilize the findings obtained by an experimenter in an experiment can be provided.

Brief Description of the Drawings

[0019] [Figure 1] It is a block diagram showing the configuration of the analysis system according to the first embodiment. [Figure 2] It is a block diagram showing the configuration of the server according to the first embodiment. [Figure 3] It is a block diagram showing the configuration of the server according to the first embodiment. [Figure 4] It is a flowchart showing the operation of the analysis system according to the first embodiment. [Figure 5] It is a block diagram showing the configuration of the server according to the second embodiment. [Figure 6] It is a block diagram showing the configuration of the server according to the third embodiment.

Modes for Carrying Out the Invention

[0020] <The First Embodiment> (Configuration of the Analysis System) Hereinafter, the first embodiment according to the present disclosure will be described in detail with reference to the drawings. First, the configuration of the analysis system according to this embodiment will be described in detail.

[0021] FIG. 1 is a block diagram showing the configuration of the analysis system according to the first embodiment. As shown in FIG. 1, in the analysis system 1 according to this embodiment, a server 100 and a user terminal 200 are connected via a network N such as the Internet.

[0022] The analysis system 1 according to this embodiment is typically provided as part of a data cloud service used in materials development and research and development, and is used as a system to promote so-called materials informatics (MI) and research and development using data science.

[0023] Analysis system 1 stores various data related to the experimental sample. Then, analysis system 1 analyzes the stored data based on instructions from the user. The various data related to the experimental samples mentioned here include the data analyzed and the text data, which will be described later.

[0024] In the analysis system 1, the user terminal 200 transmits various data about the experimental sample to the server 100, and the server 100 analyzes the received data. The server 100 then transmits the analysis results to the user terminal 200, and the user terminal 200 displays the received analysis results.

[0025] The user terminal 200 according to this embodiment is a terminal operated by a user, and is typically a computer device having a display device. The user terminal 200 transmits various data about the experimental sample to the server 100 via the network N. The user terminal 200 then receives the analysis results of the various data about the experimental sample from the server 100 via the network N.

[0026] In this embodiment, the server 100 receives various data related to experimental samples from the user terminal 200 via the network N and analyzes the received data. The server 100 then transmits the analysis results to the user terminal 200 via the network N.

[0027] Figure 2 is a block diagram showing the hardware configuration of the server according to the first embodiment. As shown in Figure 2, the server 100 includes a processor 110, memory 120, storage device 130, input / output interface 140, network interface 150, and internal bus 160.

[0028] The internal bus 160 is a data transmission path for the processor 110, memory 120, storage device 130, input / output interface 140, and network interface 150 to send and receive data to and from each other. However, the method of connecting the processor 110 and the other components to each other is not limited to bus connection.

[0029] Memory 120 is a main memory device implemented using RAM (Random Access Memory), etc. Storage device 130 is an auxiliary storage device implemented using a hard disk, SSD (Solid State Drive), memory card, or ROM (Read Only Memory), etc. The storage device 130 stores a program for implementing the desired function.

[0030] The processor 110 is a variety of processor such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an FPGA (field-programmable gate array). The processor 110 reads the program stored in the storage device 130 into the memory 120 and executes it, thereby performing the functions of each functional block as shown in Figure 3, which will be described later.

[0031] The input / output interface 140 is an interface for connecting the server 100 with input / output devices. For example, input devices such as keyboards and output devices such as display devices may be connected to the input / output interface 140. The network interface 150 is an interface for connecting the server 100 to the network.

[0032] The program, when loaded into a computer, includes a set of instructions (or software code) for causing the computer to perform one or more of the functions described in the embodiments. The program may be stored in a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include RAM, ROM, flash memory, SSD or other memory technologies, CD-ROM, DVD (digital versatile disc), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include, a temporary computer-readable medium or a communication medium that includes electrically, optically, acoustically, or otherwise propagating signals.

[0033] Figure 3 is a block diagram showing the configuration of a server according to the first embodiment. As shown in Figure 3, the server 100 according to this embodiment includes an analysis target data acquisition unit 111, a text acquisition unit 112, an extraction unit 113, and an analysis unit 114 as functional blocks.

[0034] The data acquisition unit 111 acquires data to be analyzed. More specifically, in this embodiment, the data acquisition unit 111 acquires multiple data to be analyzed from the user terminal 200 via the network N. The data acquisition unit 111 outputs the acquired data to be analyzed to the analysis unit 114.

[0035] Furthermore, the data acquisition unit 111 may store the acquired data in the storage device 130 each time it acquires data. Then, when performing the analysis described later, it may read the data from the storage device 130 and output it to the analysis unit 114.

[0036] In this case, the data acquisition unit 111 does not need to read all the data to be analyzed stored in the storage device 130, but may read only the data to be analyzed specified by the user and output it to the analysis unit 114.

[0037] In other words, the data acquisition unit 111 may create a database containing the data to be analyzed. The data acquisition unit 111 according to this embodiment may be configured so that the user can appropriately select the data to be analyzed from the created database.

[0038] Here, the data to be analyzed acquired by the data acquisition unit 111 according to this embodiment is at least one of the following: measurement data obtained by measuring the sample and numerical data relating to the sample. In other words, the data acquisition unit 111 according to this embodiment acquires data to be analyzed, which is at least one of the measurement data obtained by measuring the sample and numerical data related to the sample.

[0039] The measurement data obtained by measuring a sample may be raw data output from the measuring instrument used to measure the sample, or it may be data that has undergone analytical processing. The measurement data obtained by measuring a sample may be any data format that is readable by a computer.

[0040] Examples of measurement data obtained by measuring a sample include spectral data, waveform data, graph data, secondary image data, and three-dimensional image data. Examples of spectral data include those measured using methods such as nuclear magnetic resonance spectroscopy (NMR), infrared spectroscopy (IR), ultraviolet-visible spectroscopy (UV-vis), X-ray absorption spectroscopy (XAS), Raman spectroscopy, X-ray diffraction (XRD), small-angle X-ray scattering (SAXS), and mass spectrometry (MS). Furthermore, examples of two-dimensional image data include image data acquired using optical microscopes, scanning electron microscopes (SEM), transmission electron microscopes (TEM), and computed tomography (CT). Furthermore, examples of 3D image data include imaging data created by stacking tomographic images taken by computed tomography (CT), and model data created using CAD (Computer-Aided Design), etc. Wave-related data can include, for example, time-series data and displacement data. Examples of time-series data include acoustic data and vibration data, but any data in which the numerical value changes with time can be used. Examples of displacement data include the surface height and surface profile of a sample, but any data in which the numerical value changes with changes in coordinates and other parameters is acceptable. Other data include, for example, cyclic voltammograms, gas chromatography (GC) charts, and coordinate data such as CIF (Crystallographic Information) files.

[0041] Numerical data relating to a sample may, for example, be numerical data defining the experimental conditions of the sample, or numerical data indicating the composition of the sample. For example, if the sample is a composition, the numerical data relating to the sample may be the content of each component contained in the composition. If the sample is a product, the numerical data relating to the sample may be numerical values ​​relating to reaction conditions, such as reaction temperature, reaction time, the weight of the substrate used in the reaction, and the reaction scale.

[0042] Furthermore, the data to be analyzed may include both measurement data obtained by measuring the sample and numerical data related to the sample. Examples of data that include both measurement data obtained by measuring the sample and numerical data related to the sample include the physical properties of the sample.

[0043] Examples of sample properties include mechanical properties such as strength, hardness, toughness, and wear resistance; physical properties such as density, conductivity, magnetism, thermal conductivity, and thermal expansion coefficient; and chemical properties such as corrosion resistance.

[0044] Furthermore, the data to be analyzed is not limited to data related only to the sample; for example, it may also include performance values ​​of products and modules created using the sample. Examples of performance values ​​for products and modules created using the sample include the photoelectric conversion efficiency of a solar cell equipped with a photoelectric conversion layer using the sample as a material, and numerical values ​​evaluating the durability of a vehicle manufactured using the sample as a body material.

[0045] In other words, the data to be analyzed acquired by the data acquisition unit 111 may be data that directly or indirectly defines the composition of the sample to be analyzed, or it may be data that directly or indirectly evaluates the performance of the sample to be analyzed. The data analyzed in this embodiment is data in which information about the experimental content is recorded in a format other than text.

[0046] The text acquisition unit 112 acquires text data that records the experimental details of the sample. The text acquisition unit 112 outputs the acquired text data to the extraction unit 113. Furthermore, the text acquisition unit 112 may store the acquired text data in the storage device 130 each time it acquires text data. Then, when performing the analysis described later, the text data may be read from the storage device 130 and output to the extraction unit 113.

[0047] Furthermore, in this case, the text acquisition unit 112 does not need to read all the text data stored in the storage device 130, but may read only the text data specified by the user and output it to the extraction unit 113. In other words, the text acquisition unit 112 may create a database that stores text data. The text acquisition unit 112 according to this embodiment may be configured so that the user can appropriately select the data to be analyzed from the created database.

[0048] Furthermore, in the database referred to here, text data may be stored in association with the aforementioned data to be analyzed. In other words, the server 100 according to this embodiment may store the acquired data to be analyzed and the text data in the same database, associating them with each sample. In this case, the text acquisition unit 112 may acquire text data associated with the data to be analyzed that has been specified by the user as the target of analysis.

[0049] In this embodiment, the text data is data recorded in text format from a document created by the experimenter who performed the experiment on the sample, in order to record the details of the experiment.

[0050] For example, text data may be created when an experimenter uses an input means such as a keyboard to input text recording the experimental details into the user terminal 200. In this case, the text acquisition unit 112 receives the input text data from the user terminal 200 and acquires text data recording the experimental details of the sample. In this case, the text data may be referred to as an electronic laboratory notebook.

[0051] Furthermore, the written record of the experiment may be written on paper by the experimenter using a writing instrument or the like. In this case, the text acquisition unit 112 may acquire image data of the paper on which the user has recorded the experiment from the user terminal 200, and convert the characters written on the paper into text data by image processing the acquired image data. The text acquisition unit 112 may then acquire the converted text data as text data recording the experimental details of the sample. In this case, the written record of the experiment may be a so-called experiment notebook.

[0052] As described above, the text acquisition unit 112 according to this embodiment may acquire text data that has been recorded as electronic data from the beginning, or it may acquire text data that has been generated by converting character information that was initially recorded on paper. In other words, the text acquisition unit 112 may acquire data other than text data, convert the acquired data, or extract text data from the acquired data.

[0053] For example, the text acquisition unit 112 may extract text data from electronic data that includes text data and image data. The image referred to here may be, for example, a photograph of the appearance of a sample, a sketch of experimental equipment, or an image representing spectral data measured from a sample. In other words, the image referred to here may be any image that is recorded in an experimental notebook or electronic experimental notebook.

[0054] As will be described in detail later, the analysis system according to this embodiment performs analysis using information extracted from text data acquired by the text acquisition unit. In other words, the analysis system according to this embodiment performs analysis using information extracted from documents created by the experimenter to record the experimental content. As a result, the analysis system according to this embodiment can utilize the knowledge gained by the experimenter through the experiment.

[0055] The extraction unit 113 acquires text data from the text acquisition unit 112. The extraction unit 113 extracts information related to the experiment from the text data. The extraction unit 113 outputs the extracted information to the analysis unit 114.

[0056] The extracted information according to this embodiment is used to analyze a sample. Therefore, it is preferable that the extracted information according to this embodiment includes, for example, information regarding the experimental conditions of the sample and information regarding the physical properties of the sample.

[0057] The information extracted by the extraction unit 113 is information extracted from the text data regarding the experimental content in a manner that allows for analysis. Therefore, the manner in which the information extracted by the extraction unit 113 is extracted can be freely set according to the method used for analysis.

[0058] For example, if the analysis method used is a multivariate analysis such as principal component analysis, the extraction unit 113 may extract the information as numerical data recording multiple variables. In such cases, the extraction unit 113 may first extract items relating to at least one of the experimental conditions of the sample and the physical properties of the sample. Then, the extraction unit 113 may extract the extracted information as numerical data by quantifying the degree of each extracted item for each sample.

[0059] In the above case, the extraction unit 113 may refer to a database that records, for example, words related to experimental conditions and words related to physical properties. The extraction unit 113 may then extract items by searching the text data for words recorded in the database. Furthermore, the extraction unit 113 may extract items by, for example, using artificial intelligence (AI) trained to output items from text data as input data.

[0060] Alternatively, the extraction unit 113 may quantify the degree of an item by extracting a value representing the degree of the item that is contained in the text data. For example, if the text data states that "the reaction solution was heated at a reaction temperature of 60 degrees Celsius for 1 hour," the extraction unit 113 first extracts "reaction temperature" and "reaction time" as items related to the experimental conditions. Then, for the "reaction temperature" item, it quantifies the degree of the item by extracting the numerical value "60 degrees Celsius." Furthermore, for the "reaction temperature" item, it quantifies the degree of the item by extracting the numerical value "1 hour."

[0061] Furthermore, if the extraction unit 113 extracts items related to the physical properties of a sample, it may quantify the degree of those physical properties by assigning a first predetermined value to samples that exhibit those physical properties and a second predetermined value to samples that do not exhibit those physical properties. For example, if text data is obtained that states "a foamy product was obtained" and text data that states "a product was obtained" without mentioning foaminess, the extraction unit 113 will first extract "foaminess" as an item related to the physical properties of the sample. The extraction unit 113 then assigns a first predetermined value (e.g., "1") to the "effervescence" item of the sample corresponding to the text data that states, "A foamy product was obtained." Furthermore, the extraction unit 113 assigns a second predetermined value (e.g., "0") to the "effervescence" item of the sample corresponding to the text data that states, "A product was obtained," without mentioning effervescence. With this configuration, information that does not contain specific numerical values ​​in the text data can also be treated as numerical data. As a result, the analysis system according to this embodiment can further utilize the knowledge that the experimenter has gained in the experiment.

[0062] Furthermore, the extraction unit 113 may extract words representing the degree of an item from the text data and quantify the degree of the item based on the extracted words. For example, if there is text data stating "a product that foams slightly was obtained," text data stating "a product that foams was obtained," and text data stating "a product that foams violently was obtained," the extraction unit 113 will first extract "foaminess" as an item related to the physical properties of the sample. The extraction unit 113 will also extract "slightly" and "violently" as words that indicate the degree of the item. The extraction unit 113 then assigns a first predetermined value (e.g., "1") to the "effervescence" item of the sample corresponding to the text data that states, "A slightly effervescent product was obtained." The extraction unit 113 also assigns a second predetermined value (e.g., "2"), which is greater than the first predetermined value, to the "effervescence" item of the sample corresponding to the text data that states, "A effervescent product was obtained." Furthermore, the extraction unit 113 assigns a third predetermined value (e.g., "3"), which is greater than the second predetermined value, to the "effervescence" item of the sample corresponding to the text data that states, "A vigorously effervescent product was obtained." This configuration allows for more detailed quantification of information that is not specifically stated in the text data. As a result, the analysis system according to this embodiment can further utilize the knowledge gained by the experimenter during the experiment.

[0063] Furthermore, the extraction unit 113 may also extract identification information related to each extracted item as extracted information. In this case, the extraction unit 113 may, for example, extract "manufacturing lot number of compound" as an item and extract the corresponding "manufacturing lot number" as identification information. Alternatively, the extraction unit 113 may extract, for example, "the date the sample was created" as an item, and extract the corresponding "date" as identification information.

[0064] Furthermore, the extraction unit 113 may extract, for example, "sample preparation method" as an item. In this case, the extraction unit 113 may pre-assign identifiers to the types of "sample preparation methods". Then, based on the information recorded in the text data, it may identify the corresponding sample preparation method and record the identifier corresponding to the identified preparation method as extracted information.

[0065] As described above, the extraction unit 113 according to this embodiment extracts information related to the experimental content from text data, but the extraction method is not particularly limited and can be freely set according to the method used for analysis. In other words, the extraction unit 113 according to this embodiment may use any method to extract the information, as long as it is a method that can extract information about the experiment recorded in a format applicable to the analysis method from the text data.

[0066] In addition, the extraction unit 113 according to this embodiment may, for example, use artificial intelligence (AI) to extract information from text data. In this case, the extraction unit 113 uses text data as input data and extracts information by using artificial intelligence (AI) trained to output extracted data in a format applicable to the analysis method performed by the analysis unit 114, which will be described later.

[0067] The analysis unit 114 acquires the data to be analyzed from the data acquisition unit 111 and extracts information from the extraction unit 113. The analysis unit 114 performs the analysis based on the data to be analyzed and the extracted information.

[0068] For example, the analysis unit 114 may acquire data to be analyzed, including multiple variables, and extracted information, and perform the analysis using multivariate analysis. In multivariate analysis, the information recorded in the extracted information may be used as explanatory variables or as the dependent variable.

[0069] For example, the analysis unit 114 according to this embodiment may extract feature quantities, such as principal components, from the data to be analyzed. The analysis unit 114 may then evaluate the correlation between the extracted feature quantities and the extracted information.

[0070] For example, the analysis unit 114 may evaluate the correlation between the features extracted from the data to be analyzed and the information regarding the physical properties of the sample. In this case, the analysis unit 114 may, for example, perform principal component analysis on the given data to be analyzed and calculate the principal component score for each principal component. The analysis unit 114 may then evaluate the correlation between the obtained principal component scores and information regarding the physical properties of the sample.

[0071] With this configuration, the analysis system according to this embodiment can clearly present the relationship between the features of the data to be analyzed and the physical properties exhibited by the sample. As a result, the analysis system according to this embodiment can assist the user in considering the physical properties of the sample.

[0072] In this case, for example, the analysis unit 114 may perform principal component analysis on the given data to be analyzed and calculate the principal component score for each principal component. The analysis unit 114 may then evaluate the correlation between the obtained principal component scores and information regarding the experimental conditions of the sample. In other words, the analysis unit 114 may evaluate the correlation between the features extracted from the data to be analyzed and the information regarding the experimental conditions of the sample.

[0073] With this configuration, the analysis system according to this embodiment can clearly present the relationship between the features of the data to be analyzed and the experimental conditions of the sample. As a result, the analysis system according to this embodiment can assist the user in considering the influence of the experimental conditions on the sample.

[0074] (Operation of the analysis system) Next, the operation of the analysis system, that is, the analysis method according to the first embodiment, will be described in detail. Figure 4 is a flowchart showing the operation of the analysis system according to the first embodiment. In the following explanation, Figures 1 to 3 will be referred to as appropriate.

[0075] In the processing procedure shown in Figure 4, the processor 110 of the server 100 functions as the data acquisition unit 111, text acquisition unit 112, extraction unit 113, and analysis unit 114 by reading the program stored in the storage device 130 into the memory 120 and executing it.

[0076] In the analysis method according to this embodiment, first, the processor 110 acquires the data to be analyzed (step ST1). More specifically, in step ST1, the processor 110 acquires the data to be analyzed, which is at least one of the measurement data obtained by measuring the sample and numerical data related to the sample. In other words, in step ST1, the processor 110 functions as the data acquisition unit 111 for the data to be analyzed. For example, in step ST1, the processor 110 receives a selection of data to be analyzed from the user terminal 200. Then, the processor 110 retrieves the selected data to be analyzed from the storage device 130.

[0077] Next, the processor 110 acquires text data (step ST2). More specifically, in step ST2, the processor 110 acquires text data related to the sample. In other words, in step ST2, the processor 110 functions as a text acquisition unit 112. For example, in step ST2, the processor 110 accepts the selection of text data from the user terminal 200. The processor 110 may then retrieve the selected text data from the storage device 130. Alternatively, in step ST2, the processor 110 may retrieve from the storage device 130 the text data stored in association with the data to be analyzed acquired in step ST1. Note that the execution order of steps ST1 and ST2 may be reversed. Also, steps ST1 and ST2 may be executed in parallel.

[0078] Next, the processor 110 extracts information from the text data (step ST3). More specifically, in step ST3, the processor 110 extracts information related to the experimental content from the text data. In other words, in step ST3, the processor 110 functions as an extraction unit 113. As mentioned above, the extracted information relating to this embodiment may include, for example, at least one of the following: information regarding the experimental conditions of the sample and information regarding the physical properties of the sample.

[0079] Finally, the processor 110 performs the analysis based on the data to be analyzed and the extracted information (step ST4), and the analysis system 1 completes its series of operations. In other words, in step ST4, the processor 110 functions as the analysis unit 114. Thus, in the analysis method according to this embodiment, the analysis is performed using information extracted from documents created by the experimenter to record the experimental content. As a result, the analysis method according to this embodiment can utilize the knowledge that the experimenter gained through the experiment.

[0080] As described above, the analysis system according to this embodiment extracts information from text data and performs analysis based on the extracted information. With this configuration, the analysis system according to this embodiment can acquire the knowledge gained by the experimenter as text data. As a result, the analysis system according to this embodiment can utilize the knowledge gained by the experimenter in the experiment.

[0081] <Second Embodiment> (Configuration of the analysis system) A second embodiment of this disclosure will be described in detail below with reference to the drawings. The analysis system according to this embodiment is an application example of the analysis system according to the first embodiment.

[0082] Figure 5 is a block diagram showing the configuration of a server according to the second embodiment. The analysis system according to this embodiment differs from the first embodiment in that the server 100 includes a reception unit 115, but the other configurations are the same as those of the analysis system according to the first embodiment.

[0083] In this embodiment, the extraction unit 113 extracts items relating to at least one of the following: information regarding the experimental conditions of the sample and information regarding the physical properties of the sample. The extraction unit 113 in this embodiment then presents the extracted items to the user. For example, the extraction unit 113 presents the extracted items to the user by displaying a list of the extracted items on the user terminal 200.

[0084] The reception unit 115 receives item specifications from the user. The reception unit 115 outputs identification information of the received items to the analysis unit 114.

[0085] In this embodiment, the analysis unit 114 acquires identification information of the item specified by the reception unit 115. The analysis unit 114 then evaluates the correlation between the specified item and the data to be analyzed.

[0086] Specifically, the analysis unit 114 according to this embodiment may perform principal component analysis on the data to be analyzed, and then perform regression analysis between the principal component scores obtained as a result of the principal component analysis and the items included in the extracted information extracted by the extraction unit 113. The analysis unit 114 may then present to the user the principal component scores that it has determined to have a high correlation with the items specified by the user, and the principal components corresponding to those principal component scores.

[0087] For example, if the item specified by the user is related to the physical properties of the sample, the analysis system according to this embodiment can present the user with analysis data that has a high correlation with the physical properties of the sample, as described above. As a result, the analysis system according to this embodiment can assist the user in considering the physical properties they are interested in.

[0088] Furthermore, for example, if the items specified by the user relate to the experimental conditions of the sample, the analysis system according to this embodiment can present the user with analysis data that has a high correlation with the experimental conditions of the sample, as described above. As a result, the analysis system according to this embodiment can assist the user in considering the effects of experimental conditions on a sample. Furthermore, as a result, the analysis system according to this embodiment can assist the user in considering experimental conditions of interest.

[0089] <Third Embodiment> (Configuration of the analysis system) A third embodiment of this disclosure will be described in detail below with reference to the drawings. The analysis system according to this embodiment is an application example of the analysis system according to the first embodiment.

[0090] Figure 6 is a block diagram showing the configuration of the server according to the second embodiment. The analysis system according to this embodiment differs from the first embodiment in that the server 100 described above includes an unknown data acquisition unit 116, but the other configurations are the same as those of the analysis system according to the first embodiment.

[0091] In this embodiment, the extraction unit 113 extracts information regarding the physical properties of the sample. In other words, the extracted information according to this embodiment includes information regarding the physical properties of the sample.

[0092] The unknown data acquisition unit 116 acquires unknown data, which is the data to be analyzed from the unknown sample. The unknown data acquisition unit 116 outputs the unknown data to the analysis unit 114. The data to be analyzed for the unknown sample referred to here may be data obtained by actually measuring the unknown sample, or it may be simulation data created by the user. In other words, the unknown sample in this embodiment may be a real sample, or it may be a non-existent sample simulated by the user. Furthermore, if an unknown sample actually exists, the unknown data may, for example, be part of the data to be analyzed that was acquired. In this case, the unknown sample according to this embodiment may be defined as a sample for which details of some physical properties are unknown.

[0093] In this embodiment, the analysis unit 114 predicts the physical properties of the unknown sample based on the unknown data, the data to be analyzed, and the extracted information. In this case, the analysis unit 114 may first extract features from the data to be analyzed and perform regression analysis between the extracted features and the information on physical properties contained in the extracted information. Then, the analysis unit 114 may predict the physical properties of an unknown sample based on the unknown data and the results of the regression analysis.

[0094] As a specific example of the above case, for instance, the analysis unit 114 may perform principal component analysis on the data to be analyzed and the unknown data to obtain principal components and principal component scores. Next, the analysis unit 114 may create map data with the principal component scores and numerical values ​​representing the degree of the physical properties of the samples as axes, and plot points representing each sample on the map data. Then, the analysis unit 114 may refer to the principal component scores of the unknown data and the map data to predict the degree of the physical properties of the unknown sample.

[0095] With the configuration described above, the analysis system according to this embodiment can predict the physical properties of an unknown sample.

[0096] <Other Embodiments> The analysis systems according to the first and second embodiments are implemented as a server 100, but the configuration of the analysis system according to this disclosure is not limited thereto. For example, the display system according to this disclosure may be implemented by two or more computer devices. Also, for example, part or all of the configuration of the analysis system according to this disclosure may be implemented as a user terminal 200.

[0097] Although the present invention has been described above in reference to the embodiments described above, the present invention is not limited to the configuration of the embodiments described above, and of course includes various modifications, alterations, and combinations that can be made by a person skilled in the art within the scope of the claims of the present patent application. [Explanation of Symbols]

[0098] 1. Analysis System 100 servers 110 processors 120 memory 130 Storage Devices 140 Input / Output Interfaces 150 network interfaces 160 bus 111 Data acquisition unit for analysis 112 Text acquisition unit 113 Extraction part 114 Analysis Department 115 Reception Department 116 Unknown Data Acquisition Unit 200 user terminals

Claims

1. An analysis target data acquisition unit acquires analysis target data that includes at least one of measurement data obtained by measuring a sample and numerical data related to the sample. A text acquisition unit that acquires text data recording the experimental details of the aforementioned sample, An extraction unit that extracts information related to the experimental content from the aforementioned text data, The system comprises an analysis unit that performs analysis based on the data to be analyzed and the extracted information. Analysis system.

2. The extracted information includes at least one of the following: information regarding the experimental conditions of the sample and information regarding the physical properties of the sample. The analysis system according to claim 1.

3. The extraction unit extracts items relating to at least one of the following: information relating to the experimental conditions of the sample and information relating to the physical properties of the sample. The analysis system according to claim 2.

4. When the extraction unit extracts items related to the physical properties of the sample, it quantifies the degree of each item for each sample. The analysis system according to claim 3.

5. When the extraction unit extracts items related to the physical properties of the sample, it assigns a first predetermined value to samples that exhibit the said physical properties and a second predetermined value to samples that do not exhibit the said physical properties, thereby quantifying the degree of said physical properties. The analysis system according to claim 4.

6. The system further includes a reception unit that receives the specified items from the user, The analysis unit evaluates the correlation between the specified item and the data to be analyzed. The analysis system according to any one of claims 3 to 5.

7. The system further includes an unknown data acquisition unit that acquires unknown data, which is the data to be analyzed from the unknown sample. The extracted information includes information regarding the physical properties of the sample, The analysis unit predicts the physical properties of the unknown sample based on the unknown data, the data to be analyzed, and the extracted information. The analysis system according to any one of claims 1 to 5.

8. The text acquisition unit, We obtained image data of the paper document that recorded the details of the experiment, By processing the acquired image data, the characters written on the paper are converted into text data. The converted text data is acquired as text data recording the experimental details of the sample. The analysis system according to any one of claims 1 to 5.

9. Analytical data is obtained which is at least one of the measurement data obtained by measuring the sample and numerical data related to the sample. Obtain text data related to the aforementioned sample, Extract information relating to the sample from the aforementioned text data, Based on the aforementioned data to be analyzed and the extracted information, the analysis is performed. Analysis method.

10. Analytical data is obtained which is at least one of the measurement data obtained by measuring the sample and numerical data related to the sample. Obtain text data related to the aforementioned sample, Extract information relating to the sample from the aforementioned text data, Based on the data to be analyzed and the extracted information, the computer is instructed to perform the analysis. Analysis program.

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