Method of processing structured data and program

Abstract

To conduct an experiment by an automatic experimental apparatus using structured data created by extracting experimental condition data from an external source.SOLUTION: A method of processing structured data related to an experiment includes the steps of: creating structured data by using a computer; and generating a control signal for operating an automatic experimental apparatus based on the structured data. The structured data includes a plurality of sets including items and values for conducting a predetermined experiment with the automatic experimental apparatus. The step of creating the structured data includes the steps of: extracting, from a first information source, a first value to be input to the sets; and filling a second value to a blank field of the sets.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a method and a program for processing structured data, and more particularly to a method and a program for processing structured data related to experiments. [Background technology]

[0002] In recent years, technologies have been developed to extract experimental condition data contained in external sources (papers and / or experimental videos) (Non-Patent Documents 1 to 4). For example, Non-Patent Document 1 discloses a technology for automatically generating an experimental protocol from an experimental video. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Protocol Generation from Experimental Videos Using VideoCLIP, Kouki Yamamoto et al., Proceedings of the 29th Annual Conference of the Association for Natural Language Processing, March 2023, pp.2306-2311 [Non-patent document 2] "Automatic extraction and structuring of physical property data of polymer materials from papers, etc." [online] [Retrieved October 3, 2023], Internet<URL:https: / / www.nature.com / articles / s41598-022-14735-4> [Non-patent document 3] Marta Skreta et al., “Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting”, March 2023, https: / / doi.org / 10.48550 / arXiv.2303.14100 [Non-patent document 4] Lina Liu et al., “L-Tryptophan Production in Escherichia coli Improved by Weakening the Pta-AckA Pathway”, 27 June 2017, doi:10.1371 / journal.pone.0158200 Summary of the Invention [Problem to be solved by the invention]

[0004] However, papers and experimental videos do not necessarily disclose all the parameters (values) of the experimental conditions required to conduct an experiment, and values ​​that are common sense in the field of the experiment are often omitted. On the other hand, when conducting an automated experiment using automated experimental equipment, it is necessary to set the values ​​of all experimental conditions, including those values ​​that are omitted from disclosure. Therefore, even if the values ​​of the experimental conditions are extracted from a specific paper or a specific experimental video, it may not be possible to conduct an automated experiment using the automated experimental equipment using only the extracted values.

[0005] An object of the present invention is to conduct an experiment using an automatic experiment device using structured data created by extracting experimental condition data from an external source. [Means for solving the problem]

[0006] A first aspect of the present invention is a method for processing structured data related to an experiment, comprising the steps of: creating structured data using a computer; and generating a control signal for operating an automated laboratory equipment based on the structured data. The structured data includes a plurality of sets, each including an item and a value, for performing a predetermined experiment on the automated laboratory equipment. The step of creating the structured data includes the steps of extracting a first value to be input into the set from a first information source and filling in blanks in the set with a second value.

[0007] A second aspect of the present invention is a method for processing structured data related to an experiment, comprising the steps of creating structured data using a computer and displaying the structured data. The structured data includes a plurality of sets, each including an item and a value, for conducting a predetermined experiment. The step of creating the structured data includes the steps of extracting, from a first information source, a first value to be input into the set and filling in blanks in the set with a second value. [Effects of the Invention]

[0008] According to the present disclosure, experiments can be performed using automated experiment equipment using structured data created by extracting experiment condition data from an external source. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram schematically illustrating an example of the overall configuration of an experimental system. [Figure 2] FIG. 10 is a diagram for explaining a method for creating experimental conditions according to an embodiment. [Figure 3] 10 is a flowchart illustrating processing of structured data according to an embodiment. [Figure 4] FIG. 2 is a diagram showing an example of first structured data. [Figure 5] FIG. 10 is a diagram showing an example of second structured data. [Figure 6] FIG. 10 is a diagram illustrating an example of embedded data. [Figure 7] FIG. 10 is a diagram showing an example of the priority order of experimental conditions. [Figure 8] 10 is a flowchart showing processing of structured data according to Modification 1. [Figure 9] 10 is a flowchart showing processing of structured data according to Modification 2. [Figure 10] FIG. 10 is a diagram showing an example of a strain information table. [Figure 11] FIG. 10 is a diagram showing an example of an experiment condition table. [Figure 12] FIG. 10 is a diagram showing an example of an experiment result table. [Figure 13]10 is a flowchart showing processing of structured data according to Modification 3. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0011] [1. Experimental system configuration] 1 is a diagram showing an example of the overall configuration of an experimental system 1 according to this embodiment. The experimental system 1 includes a control device 100 and an experimental device 200.

[0012] The experimental device 200 is an automated experimental device that receives a control signal from the control device 100 and automatically performs a scientific experiment based on the control signal. Figure 1 shows an example of an experiment in which the experimental device 200 performs a cell culture experiment.

[0013] The cells cultured in the experimental apparatus 200 are not particularly limited, and may be, for example, cells that have a useful function in medicine or cells that produce substances that have a useful function in various industrial fields. In one embodiment, the cells are bacteria. In other embodiments, the cells may be cells derived from microorganisms other than bacteria and / or cells derived from animals or plants other than microorganisms. Furthermore, experiments performed in the experimental apparatus 200 may be experiments other than cell culture (e.g., synthetic chemistry experiments).

[0014] The experimental device 200 includes a medium preparation device 210 and a culture device 220 . The culture medium preparation device 210 prepares a culture medium under predetermined experimental conditions based on a control signal received from the control device 100. More specifically, the culture medium preparation device 210 places a predetermined culture medium in a predetermined container in accordance with the control signal, and adds a bacterial strain to the predetermined culture medium.

[0015] The incubator 220 performs incubation under predetermined experimental conditions based on the control signal received from the controller 100. More specifically, the incubator 220 performs incubation at a predetermined temperature for a predetermined time in accordance with the control signal.

[0016] The experimental device 200 preferably also includes a measuring device 230. The measuring device 230 measures the results of the cell culture experiment performed by the culture device 220. The measuring device 230 transmits the results of the experiment to the control device 100.

[0017] 1, the control device 100 includes a processor 101, a memory 102, an input / output interface (I / F) 103, and a communication I / F 104.

[0018] The processor 101 executes various programs so that the control device 100 can perform various processes. The memory 102 stores the programs executed by the processor 101 and various data required for executing the programs. The memory 102 stores a program that, when executed by a computer, performs a structured data processing method according to an embodiment. The input / output I / F 103 is an interface that allows the processor 101 to communicate with the experimental device 200. The communication I / F 104 is an interface that allows the processor 101 to communicate with devices outside the experimental system 1 via a network.

[0019] The control device 100 further includes a display 110 and an input device 120. The display 110 displays the results of the arithmetic processing performed by the processor 101. The input device 120 (such as a mouse, keyboard, or touch sensor) accepts data input operations to the processor 101.

[0020] [2. Comparison with previous methods for creating experimental conditions from papers, experimental videos, etc.] Conventionally, technologies have been developed for extracting experimental condition data from papers, experimental videos, etc. Non-Patent Document 1 discloses a technology for estimating the names of objects and the experimenter's actions from experimental videos and automatically generating an experimental protocol. Non-Patent Document 2 discloses a technology for generating an experimental protocol from natural language and correcting any errors by feeding them back to a large-scale language model. Non-Patent Document 3 describes a technology for extracting material property data from papers, etc., and creating structured data.

[0021] However, papers, experimental videos, etc. often do not disclose the parameters (values) of all experimental conditions (also referred to simply as "all experimental conditions" in this specification) required to conduct an experiment. On the other hand, in an automated experimental device, it is necessary to input the values ​​of all experimental conditions. Therefore, even if the values ​​of all experimental conditions disclosed in a given paper or a given experimental video are extracted, there is a risk that the automated experiment cannot be conducted using only the extracted values.

[0022] In view of the above circumstances, the structured data processing method according to this embodiment supplements appropriate values ​​for experimental conditions that are not disclosed in papers, experimental videos, etc. This makes it possible to carry out experiments that are disclosed in papers, experimental videos, etc. but for which the values ​​of all experimental conditions are not disclosed, using automated experiment equipment.

[0023] [3. Method for creating experimental conditions according to the embodiment] FIG. 2 is a diagram for explaining a method for creating experimental conditions according to the embodiment.

[0024] Referring to FIG. 2, the first information source is an information source that discloses values ​​of experimental conditions for one or more predetermined experiments. The first information source is, for example, an information source that discloses experiments that are conducted for a predetermined purpose and / or that obtain predetermined experimental results. The first information source preferably includes papers and / or experimental videos. With this configuration, papers and / or experimental videos related to a predetermined experiment often also disclose the experimental results and / or objectives of the predetermined experiment, allowing a user to decide to conduct the predetermined experiment by referring to the experimental results and / or objectives disclosed in the papers and / or experimental videos (described in detail below).

[0025] The first information source corresponds to an example of an "external source." In one example, the control device 100 accesses an external research paper database and / or a website that collects experimental videos via the communication I / F 104 to collect the first information source. The control device 100 then extracts values ​​of experimental conditions from the first information source. In this specification, the first information source includes at least values ​​of experimental conditions and may also include values ​​of strain information and / or values ​​of experimental results. The experimental conditions correspond to an example of an "item." In other examples, the "item" may correspond to "strain information" and / or "experimental results."

[0026] In this specification, the value of an experimental condition extracted from the first information source for a given experiment is referred to as a "first value." In this specification, the first value of the experimental condition corresponds to an example of a "first value to be input into a set." The experimental condition from which the first value can be extracted is referred to as a "first experimental condition." In other words, the first experimental condition is an experimental condition from which a corresponding value can be extracted for a given experiment. For example, if the value "LB medium" of the experimental condition "culture medium" can be extracted from a given first information source for a given experiment, the control device 100 determines that "culture medium" is the first experimental condition and that "LB medium" is the first value. In this specification, the relationship between a given item (culture medium) and a given value (LB medium) as described above is referred to as the given item and the given value "corresponding." The given value corresponding to the given item is also simply referred to as the "value of the given item." The first experimental condition is basically an experimental condition for which the corresponding value is not disclosed in the first information source, but an experimental condition for which the corresponding value is disclosed in the first information source but could not be extracted from the first information source for some reason is also determined to be the first experimental condition.

[0027] In one embodiment, the control device 100 saves the extracted first value as first structured data (see FIG. 4 below). The first structured data includes a plurality of sets, each including an item and a value, for carrying out a predetermined experiment, similar to the second structured data (see FIG. 5 below), which will be described later. In the tables of FIGS. 4 and 5, each column corresponds to a set including an item (first row from the top) and one or more values ​​(second row and thereafter).

[0028] However, as mentioned above, first information sources such as papers and experimental videos often do not disclose the values ​​of all experimental conditions required to conduct a given experiment. Therefore, even if the first values ​​of the first experimental conditions disclosed in the first information source are extracted, the values ​​may not be enough to cover all the experimental conditions. In this case, blanks will be generated in the first structured data.

[0029] For example, in the first structured data in Figure 4, the value for "culture medium" in Experiment 3 could not be extracted and is left blank. Also, in Experimental Video C, the value for "temperature" in Experiment 4 could not be extracted and is left blank.

[0030] In this specification, among all experimental conditions for conducting a predetermined experiment, experimental conditions that are not included in the first experimental conditions are referred to as “second experimental conditions.” In other words, the second experimental conditions are experimental conditions that are values ​​that could not be extracted from the predetermined first information source, among all experimental condition values ​​for conducting a predetermined experiment that are disclosed in the predetermined first information source.

[0031] As described above, in an automated experimental device, it is necessary to input values ​​of all experimental conditions to carry out a predetermined experiment. Therefore, the control device 100 also fills in appropriate values ​​(second values) for the values ​​of the second experimental conditions for which corresponding values ​​could not be extracted.

[0032] In one embodiment, the control device 100 supplements the second value using a second information source. In this embodiment, the second information source is an information source containing experimental conditions that are common knowledge to those skilled in the art. The second information source may include, for example, a textbook.

[0033] In another embodiment, the control device 100 uses the first structured data to populate the second value.

[0034] In this specification, structured data in which a second value is added to the first structured data is referred to as "second structured data" (see Figure 5 below). In this specification, the second structured data corresponds to an example of "structured data" created using a computer. For example, "LB medium" is added as the second value of "culture medium" in Experiment 3. Also, "30°C" is added as the second value of "temperature" in Experiment 4.

[0035] The control device 100 converts the first and second values ​​for a predetermined experiment into control signals for execution by the automated laboratory equipment, and transmits them to the laboratory equipment 200. The first and second values ​​are the values ​​of all the experimental conditions for executing the predetermined experiment. Thus, the laboratory equipment 200 can execute the predetermined experiment.

[0036] [4. Flow of processing structured data according to the embodiment] FIG. 3 is a flowchart showing processing of structured data according to the embodiment.

[0037] In steps (hereinafter also referred to as "S") 01 to 03 in FIG. 3, the control device 100 creates structured data.

[0038] First, in S01, the control device 100 extracts a first value to be input into the set from a first information source. In one embodiment, the control device 100 extracts first values ​​of first experimental conditions for conducting one or more predetermined experiments. Preferably, the control device 100 attempts to extract all experimental conditions disclosed in the first information source for each of all experiments described in the first information source. This configuration allows the control device 100 to extract as many experimental conditions as possible from the first information source. Preferably, the control device 100 extracts values ​​of strain information and / or values ​​of experimental results in addition to values ​​of experimental conditions as the first value. This configuration allows the user to use the values ​​of strain information and / or values ​​of experimental results when selecting an experiment to conduct in the experimental system 1 (details will be described later).

[0039] It is preferable that the number of first information sources used to extract the first value in S01 is as large as possible, since the first value can be extracted and used for a large number of experiments.

[0040] In one embodiment, the control device 100 collects and uses first information sources, for example, as follows: First, the control device 100 downloads papers in a desired field from a paper database such as PubMed, and / or downloads experimental videos in a desired field from a website that collects experimental videos. The control device 100 then creates a first information source database containing multiple first information sources by collectively saving the downloaded papers and / or experimental videos. The first information source database may be stored in memory 102 or in a storage device with which the control device 100 can communicate via the communication I / F 104. The control device 100 then reads the contents of each first information source from the first information source database and extracts a first value of a specific experiment disclosed in the first information source.

[0041] When the first information source is a paper, the control device 100 automatically (without user operation) extracts the first value using a method such as named entity extraction, rule-based, or large-scale language model.

[0042] Named entity extraction is a technology that mechanically extracts named entities from natural language text, such as proper nouns such as product names, along with dates, times, quantities, etc.

[0043] Rule-based analysis is a technique for extracting data based on whether it conforms to certain rules devised by humans.

[0044] A large-scale language model is a computer language model that consists of an artificial neural network with a large number of parameters.

[0045] The user may manually extract the first value from the paper using the control device 100. For example, the user may cause the control device 100 to extract the first value by displaying the paper on the display 110, selecting the value of the first experimental condition (e.g., a predetermined character string) using the input device 120, and saving the value. However, having the control device 100 automatically extract the first value has the advantage of reducing the time required for extraction and being highly accurate. On the other hand, even if automatic extraction is not possible due to a spelling error in part of the value of the experimental condition, the first value can still be extracted manually.

[0046] When the first information source is an experimental video, the control device 100 automatically (without user operation) extracts the first value using a method such as object detection or motion detection.

[0047] Object detection is a technique for extracting the names of objects contained in experimental videos. Motion detection is a technique for detecting the motions of an experimenter included in an experimental video.

[0048] Alternatively, the control device 100 may extract the first value from the experimental video using a voice recognition technique, a technique for recognizing character strings in the experimental video, or other techniques.

[0049] A user may manually extract the first value from the experimental video using the control device 100. For example, the user may cause the control device 100 to extract the first value by displaying the experimental video on the display 110 and inputting and saving a character string corresponding to the first value recognized from the experimental video using the input device 120. However, having the control device 100 automatically extract the first value has the advantage of reducing the time required for extraction and increasing accuracy. On the other hand, even if the first value cannot be automatically recognized because, for example, an object in the experimental video, the experimenter's actions, etc. are partially hidden, it has the advantage of being able to recognize and extract the first value by visual inspection.

[0050] The control device 100 may use the above-mentioned methods of extracting experimental conditions from a plurality of papers and experimental videos, either alone or in combination.

[0051] Of course, the control device 100 stores each extracted first value in a format that allows the first condition corresponding to each first value to be understood. In one embodiment, in S02, the control device 100 creates first structured data including the first values ​​extracted from the first information source. More specifically, the first structured data is data in which the first values ​​are structured. The first structured data may also include values ​​of strain information and / or values ​​of experimental results in addition to the first values.

[0052] Fig. 4 is a diagram showing an example of the first structured data, which illustrates the first structured data for Experiments 1 to 4 extracted from the first information source.

[0053] In the first structured data, for a given experiment, the value of "information source", the value of "strain name", and the value of "experimental conditions" are associated with each other.

[0054] In the example of Figure 4, each row corresponds to an experiment. Each experiment is specified by an "information source" and a "strain name." In Figure 4, for the sake of explanation, the serial number of each experiment is written on the left side of the table, but in actual first structured data, the serial number of each experiment does not necessarily have to be assigned.

[0055] In the example of FIG. 4, the first structured data includes the items "information source," "strain name," and first experimental conditions. The first experimental conditions include the items "culture medium," "temperature," "container," and "time." For a given experiment, the value of "information source," the value of "strain name," and the values ​​of each experimental condition are arranged in the same row. In the example of FIG. 4, the values ​​of "information source," the value of culture stage, the value of strain name, and the values ​​of experimental conditions for Experiments 1 to 4 are arranged in each column, respectively.

[0056] In FIG. 4, "information source" indicates the paper and / or experimental video in which a given experiment is disclosed. The value of "information source" is, for example, the title, the author's name, the publication date, the DOI (Digital Object Identifier), etc.

[0057] "Strain name" indicates the strain that is the subject of a given experiment. The value of "strain name" is the name of the strain. Specific examples of strain names include the values ​​of "strains" in Table 1 of Non-Patent Document 4, which are incorporated by reference. The strain name may also include genetic modification information, such as the name of a plasmid inserted into the strain. For example, the value of "strain name" may include character strings such as FB-04, B. subtilis ATCC 6051a, E. coli CCTCC M 2016009, BL(DE3), BL21(DE3) / pET24a-pta, BL21(DE3) / pET24a-pta1, FB-04(Δpta), FB-04(ΔackA), and FB-04(pta1).

[0058] "Culture" refers to the medium used to cultivate the strain. "Temperature" indicates the temperature at which the strain was cultured.

[0059] "Container" refers to the container used to culture the strain. "Time" indicates the time the strain was cultured.

[0060] Examples of experimental conditions are not limited to the above, and may include, for example, "medium volume," "dissolved oxygen concentration," "air," and / or "culture stage."

[0061] "Volume of medium" indicates the volume of medium used to culture the strain. "Dissolved oxygen concentration" refers to the concentration of oxygen dissolved in the medium used to culture the strain.

[0062] "Air" indicates whether the culture environment for the strain is aerobic or anaerobic.

[0063] The "culture stage" indicates whether the culture of the strain is a main culture or a preculture, which is a preparatory stage for the main culture.

[0064] In the structured data of Figure 4, the first value of the predetermined first experimental condition of the predetermined experiment extracted from the first information source is placed in a cell at a position corresponding to the predetermined experiment and the predetermined first experimental condition, while the cell at a position corresponding to the predetermined second experimental condition of the predetermined experiment that was not extracted from the first information source is shown blank.

[0065] In other words, in Experiment 3 of the structured data in Figure 4, the "culture stage," "temperature," "container," and "time" for which the first values ​​are indicated are the first experimental condition, and the "culture medium" corresponding to the blank space is the second experimental condition.

[0066] In steps S02 and S03, the control device 100 fills in the blanks in the set with second values. In S02, the control device 100 determines second experimental conditions that are not included in the first experimental conditions among all experimental conditions for conducting a predetermined experiment. In one embodiment, the control device 100 subtracts the first experimental conditions from all experimental conditions, and sets the remaining conditions as second experimental conditions.

[0067] In S03, the control device 100 supplements the second value of the second experimental condition. Below, an example in which the second value is supplemented using the second information source and an example in which the second value is supplemented using the first information source will be described in order.

[0068] In a first embodiment, in S03, the control device 100 supplements the second value using a second information source for a predetermined experiment for which some of the experimental conditions could not be extracted. More specifically, the control device 100 selects an experiment similar to the predetermined experiment from the experiments included in the second information source. Then, the control device 100 extracts values ​​of second experimental conditions for conducting the similar experiment and sets the second value based on the extracted values.

[0069] In one embodiment, the control device 100 extracts experimental conditions from multiple second information sources in advance, stores them together, and creates a second information source database containing the multiple second information sources.The control device 100 then searches the second information source database for the similar experiment.The control device 100 then extracts values ​​of the second experimental conditions for the similar experiment.

[0070] More precisely, a similar experiment to a predetermined experiment is an experiment that is determined by the control device 100 to be similar to the predetermined experiment. An example of a similar experiment is an experiment in which the value of the strain name matches that of the predetermined experiment. Another example of a similar experiment is an experiment in which the values ​​of one or more first experimental conditions match or are similar to those of the predetermined experiment. More specifically, an example of a similar experiment to experiment 3 is an experiment in which the value of the strain name matches that of the predetermined experiment. Another example of a similar experiment to experiment 3 is an experiment in which the value of the strain name matches that of the predetermined experiment and at least one value of the temperature, container, and / or time matches or is similar to that of the predetermined experiment.

[0071] When there is one similar experiment for a given experiment from which some of the values ​​of all the experimental conditions could not be extracted, the control device 100 sets the value of the second experimental condition of the similar experiment as the second value of the given experiment. When there are multiple similar experiments for the given experiment and multiple values ​​of the second experimental condition are obtained, the control device 100 may set a random value from the multiple values ​​as the second value, or may set the most common value (mode) from the multiple values ​​as the second value. As described above, the control device 100 uses the values ​​of the experimental conditions from the similar experiment to fill in the appropriate value for the second value of the second experimental condition that could not be extracted from the given experiment.

[0072] According to the first embodiment described above, values ​​of common-sense experimental conditions that tend to be omitted from papers and / or experimental videos can be easily supplemented using descriptions in textbooks that disclose common-sense experimental conditions. Furthermore, textbooks generally involve more people than individually created papers and experimental videos, and are therefore more likely to contain orthodox and reasonable experimental conditions. Therefore, values ​​supplemented based on textbooks are less likely to be off the mark.

[0073] In the second embodiment, in S03, the control device 100 uses the first information source to fill in the second value for a given experiment for which some of the experimental conditions could not be extracted. More specifically, the control device 100 selects an experiment similar to the given experiment from the experiments included in the first information source. The control device 100 then extracts values ​​of second experimental conditions for conducting the similar experiment and sets the second value based on the extracted values. Here, the method of extracting values ​​of second experimental conditions for conducting the similar experiment and setting the second value based on the extracted values ​​can be applied to the first embodiment described above.

[0074] In one embodiment, the control device 100 uses first information structured data, which is structured data of first values ​​extracted from a first information source, to search for similar experiments and extract values ​​of second experimental conditions of the similar experiments.

[0075] For example, in the examples of Figures 4 and 5, the control device 100 determines that experiments 1, 2, and 4, which use the same strain A as the medium of experiment 3, are similar experiments. Since "LB medium" is the most commonly used medium in similar experiments 1, 2, and 4, the control device 100 replenishes "LB medium" as the second value for the medium of experiment 3. Similarly, the control device 100 replenishes "37°C," which is the most commonly used temperature in similar experiments 1, 2, and 3, as the second value for the temperature of experiment 4.

[0076] According to the second embodiment, the second value can be supplemented using the first information source collected for extracting the first value. This eliminates the need to collect new information sources for supplementing the second value. Note that a similar experiment to a given experiment in a given first information source may be another experiment in the given first information source, or an experiment in another first information source.

[0077] In addition, papers and experimental videos are generally more numerous and easier to collect than textbooks. Therefore, it is considered easier to collect a large number of experiments contained in papers and experimental videos than to collect the same number of experiments from textbooks. Therefore, the second value can be supplemented based on many experiments.

[0078] In filling in the second value, the control device 100 may display multiple candidates for the second value and accept the selection of the second value to be filled from among the candidates, instead of automatically determining one second value to be filled (without user selection). The candidate second value may be, for example, the value of the second condition of the similar experiment described above. As a more specific example, the control device 100 displays the table of FIG. 4 on the display 110 and displays multiple candidates for the second value to be entered in the blank space near the blank space. The user selects one value from the multiple candidates using the input device 120, and the control device 100 enters the selected value in the blank space as the second value. This configuration allows the user to select an appropriate value from the candidate second values. On the other hand, the method of automatically determining one second value has the advantage of not requiring the user to perform any additional work.

[0079] In S04, the control device 100 generates a control signal for operating the automated laboratory equipment based on the structured data. In one embodiment, the control device 100 generates a control signal for performing a predetermined experiment with the automated laboratory equipment based on the first value and the second value, and then ends the process. In other words, the control device 100 converts the values ​​of all experimental conditions into control signals. This makes it possible to perform the predetermined experiment with the automated laboratory equipment.

[0080] As described above, according to the structured data processing method of the embodiment, among all values ​​of experimental conditions for conducting a predetermined experiment disclosed in a first information source, values ​​that could not be extracted from the first information source can be supplemented without user operation. Therefore, the predetermined experiment disclosed in the first information source can be conducted. As described above, an experiment in which the values ​​of all experimental conditions are not disclosed in a first information source such as a paper or an experimental video can also be conducted using an automated analysis device. In other words, an experiment can be conducted using an automated experiment device using structured data created by extracting experimental condition data from an external source.

[0081] This allows the user to reproduce a given experiment simply by selecting the given experiment and / or the first information source from which the given experiment is disclosed, thereby eliminating the need for the user to read the experimental conditions in the first information source and fill in the second values ​​by themselves.

[0082] As an example of use of the control device 100 according to the embodiment, a case where a user selects an experiment to be performed on an automated laboratory system will be described. First, the user finds a first information source containing a desired experiment (e.g., an experiment conducted for a desired purpose and / or an experiment that can achieve a desired result). If the user is familiar with the first information source, the user inputs information about the first information source (e.g., a title, author name, publication date, DOI (Digital Object Identifier)), etc., using the input device 120. If the user is unfamiliar with the first information source, the user may select the first information source by searching the second structured data ( FIG. 5 ) stored in the memory 102. Then, when the user inputs the information about the first information source containing the desired experiment, the processor 101 uses the second structured data in the memory 102 to retrieve experimental conditions corresponding to the first information source specified by the user. The processor 101 then converts the experimental conditions into control signals and transmits them to the experimental system 200, thereby performing the desired experiment.

[0083] As another example of use of the control device 100 according to the embodiment, a case where a user checks experimental conditions will be described. For example, consider a case where a user wants to know an appropriate incubation time for culturing E. coli in a flask. In this case, the user uses the input device 120 to search the second structured data ( FIG. 5 ) stored in the memory 102 for the incubation time for culturing E. coli in a flask. As a more specific example, the processor 101 displays a user interface for searching the second structured data on the display 110. The user then uses the user interface to instruct the display 110 to display the incubation time values ​​for an experiment using "E. coli" and "flask." The processor 101 then extracts the corresponding incubation time value from the second structured data in the memory 102 and displays it on the display 110. This eliminates the need for the user to search a literature database or the like for a paper describing an incubation experiment in which E. coli is cultured in a flask and then search for the incubation time value within the literature.

[0084] [5. Variation 1] A paper generally includes text data and embedded data embedded in the text data. The embedded data is, for example, a figure or a table. In a paper, the values ​​of the experimental conditions are mainly described in the text data. However, there are cases where at least some of the values ​​of the experimental conditions are only disclosed in the embedded data. In such cases, in order to extract all the values ​​of the experimental conditions disclosed in the paper from the paper, it is necessary to extract the values ​​of the experimental conditions from the embedded data as well. However, when extracting the values ​​of the experimental conditions using a computer, it generally takes more time to extract the values ​​of the experimental conditions from the embedded data than to extract the values ​​of the experimental conditions from the text data.

[0085] FIG. 6 is a diagram showing an example of embedded data. FIG. 6 is a graph showing the relationship between incubation time and incubation result, with the horizontal axis representing incubation time and the vertical axis representing incubation result (concentration). When extracting the value of incubation time from FIG. 6 using a computer, for example, it is necessary to perform processes such as obtaining the item on the horizontal axis, obtaining the position of a data point, and obtaining the value on the horizontal axis corresponding to the position of the data point. This generally takes more time than extracting the value of incubation time from text data using a computer.

[0086] 3, if the control device 100 extracts the values ​​of the experimental conditions from only the text data, it may not be able to extract the necessary values. On the other hand, if the control device 100 extracts the values ​​of the experimental conditions from all the embedded data, it will take a long time to extract the values.

[0087] Therefore, in the data processing method according to the first modification, it is determined whether or not to extract embedded data depending on the importance of the experimental conditions.

[0088] In the control device according to the first modification, a priority is set in advance for each item (each experimental condition). In one embodiment, the control device stores a table as shown in Fig. 7. Fig. 7 is a diagram showing an example of the priority of the experimental conditions.

[0089] Among the experimental conditions, items that are essential for conducting an experiment have a high priority. For example, the "strain" is a strain for the purpose of culturing, so it is essential for conducting an experiment. The optimal composition of the "culture medium" is determined to some extent depending on the strain. Furthermore, the "culture stage" must be selected in line with the purpose of conducting the experiment. Therefore, in the example in Figure 7, the "strain," "culture medium," and "culture stage" are considered essential items and are set to the highest priority of 1.

[0090] Furthermore, among the experimental conditions, there are some items that are not essential but are important. For example, the value of "temperature" can be roughly inferred even without disclosure, but it may vary depending on the experiment. Therefore, in the example in Figure 7, "temperature" is set to priority 2 as an important item.

[0091] On the other hand, some experimental conditions are not important and are merely used as reference. For example, there may be no significant difference between culturing in a flask or a test tube when it comes to the "container." Also, the "container" may be inferred from the experimental purpose and / or the amount of medium, or there may be no choice depending on the experimental environment. Therefore, in the example in Figure 7, the "container" is set to the lowest priority of 3 as a reference item.

[0092] As described above, the priority is set appropriately, reflecting necessary factors such as the magnitude of the impact on the experimental results, ease of supplementing with general knowledge from textbooks, etc. In the example of Fig. 7, the priority threshold for determining whether or not to extract a value from embedded data is set between 2 and 3.

[0093] The priority may be set as a value incremented by one starting from 1 in order of importance as described above. The priority may also be set as a discrete value (for example, 1, 10, 100, etc.). Keywords such as "essential," "important," and "reference" may also be assigned to the order of priority, and a threshold may be set between "important" and "reference."

[0094] As described above, in Variation 1, all experimental conditions for a given experiment include experimental conditions whose priority in the given experiment is higher than a given threshold and experimental conditions whose priority in the given experiment is lower than the threshold. Next, a method for processing structured data related to an experiment using a priority threshold will be described.

[0095] 8 is a flowchart showing processing of structured data according to Modification 1. In Modification 1, S01 in the embodiment (FIG. 3) is replaced with S011 to S013.

[0096] In S011, the control device 100 extracts a first value of a first experimental condition from the text data of the first information source.

[0097] In S012, the control device 100 determines whether or not there is a shortage of values ​​for experimental conditions with priorities higher than a predetermined threshold value even after extracting the first values ​​from the text data.

[0098] If there is no shortage of values ​​for the experimental conditions with a priority higher than the threshold (NO in S012), the control device 100 proceeds to S02.

[0099] If there is a shortage of values ​​for experimental conditions with a higher priority than the threshold (YES in S012), in S013 the control device 100 extracts the shortage values ​​from the embedded data and proceeds to S02.

[0100] According to the structured data processing method of Variation 1, if the values ​​of high-priority experimental conditions are obtained by extracting only the values ​​of the experimental conditions from the text data, the extraction process can be completed without spending time extracting the values ​​of the experimental conditions from the embedded data. On the other hand, if the values ​​of high-priority experimental conditions are insufficient by extracting only the values ​​of the experimental conditions from the text data, the values ​​of the experimental conditions are also extracted from the embedded data. More specifically, extraction of the values ​​of the experimental conditions from the embedded data is performed only for first information sources that include experiments that are lacking values ​​of experimental conditions with a priority higher than the threshold. As described above, according to the structured data processing method of Variation 1, the values ​​of important experimental conditions can be obtained in the minimum amount of time required. More specifically, the process of creating second structured data can be made more efficient.

[0101] [6. Variation 2] 9 is a flowchart showing processing of structured data according to Modification 2. In Modification 2, S04 in the embodiment (FIG. 3) is replaced with S04A.

[0102] Referring to FIG. 9, in S04A, the control device 100 displays the second structured data and terminates the process. In one embodiment, the control device 100 displays the second structured data, including the first and second values, in a table format (see FIG. 5) on the display 110 and terminates the process. In this case, it is preferable that the second values ​​added in S03 be displayed specifically. In other words, it is preferable that the second values ​​be represented in a manner different from the first values. For example, it is preferable that the cell containing the second value be surrounded by a bold frame, that the cell containing the second value be colored, that only the characters of the second value be in a different font, that the second value be underlined, etc. This configuration allows the user to easily recognize the second value and compare it with corresponding values ​​from other experiments. This allows the user to confirm whether the added second value is appropriate.

[0103] As described above, according to the structured data processing method of the second modification, among all values ​​of experimental conditions for conducting a predetermined experiment disclosed in the first information source, values ​​that could not be extracted from the first information source can be supplemented without user operation. Furthermore, the supplemented experimental conditions can be visually confirmed. Therefore, the user can visually confirm the experimental conditions before conducting an experiment using an automated experimental device. In one embodiment, the user checks the values ​​of the row corresponding to the predetermined experiment in the table of FIG. 5 and selects that row to have the automated experimental device conduct the predetermined experiment.

[0104] Displaying the table in Figure 5 also makes it easier for users to check experimental conditions. For example, suppose a user wants to know the appropriate incubation time for culturing E. coli in a flask. The user can determine the appropriate incubation time simply by visually checking the incubation time value in the row in the table in Figure 5 where the strain name is "E. coli" and the container is "flask."

[0105] Furthermore, when the values ​​of the experimental results are displayed together with the first and second values ​​of the experimental conditions, the user can visually check the values ​​of the experimental results and then select an experiment that is expected to produce desirable experimental results.

[0106] The user can also manually conduct a given experiment by referring to the first and second values ​​of the experimental conditions. This also has the advantage that the user does not have to manually read the first information source and fill in the second values. This is particularly useful when the user does not understand the general experimental conditions in the field of the experiment.

[0107] [7. Variation 3] (7-1. Explanation of strain information table, experimental condition table, and experimental result table) In Variation 2, the first structured data and the second structured data are displayed in a single table, but the structured data can include a wide range of values, such as strain information values ​​and experimental result values. In Variation 3, the structured data is displayed in three tables: a strain information table, an experimental conditions table, and an experimental result table, thereby improving convenience.

[0108] For example, many papers on culture experiments are structured as follows: "What kind of strain was used (strain information)?", "Under what conditions was the culture carried out (culture conditions)?", and "What results were obtained (culture results)?" Figures 10 to 12 below show experimental values ​​listed in papers on culture experiments, including values ​​for strain information, culture conditions, and culture results, which are shown in three separate tables.

[0109] FIG. 10 is a diagram showing an example of a strain information table. The strain information table is a table showing data on the strains used in the experiment, and includes the following items: "Information source," "Strain name," "Microorganism name," "Genetic modification information," and "Source of acquisition."

[0110] "Microorganism name" indicates the name of the microorganism of the strain. "Microorganism name" includes, as values, names that are easy to understand for those skilled in the art, such as E. coli and yeast. "Microorganism name" may also include, as values, scientific names and / or taxonomic ranks larger than the strain.

[0111] "Genetic modification information" refers to information about the genetic modification of a strain. For example, if a gene has been modified to produce a specific substance, the "genetic modification information" includes, as values, information such as the name of the specific substance, the name of the modified gene, the modified region in the gene, and the gene sequence before and after modification.

[0112] "Source" indicates the source of the strain. For example, "source" includes the name of a research institution such as a university, research institute, or laboratory as a value.

[0113] 11 is a diagram showing an example of an experimental condition table. The experimental condition table includes information necessary for culturing a predetermined strain in an environment similar to that of the first information source. Each item in the experimental condition table has been explained above.

[0114] Fig. 12 shows an example of an experiment results table. The experiment results table contains the results of an experiment on a specific strain in a specific environment. The experiment results table includes the following items: "information source," "strain name," "culture stage," "production substance," "variation," and "variation factor."

[0115] "Production product" refers to a substance produced by a strain. "Fluctuation" indicates the fluctuating amount of product in the medium.

[0116] "Factors of variation" indicates factors that caused variations in the produced substances in the medium. In some papers, experimental conditions are changed in small increments to compare the results. For example, in a paper on a culture experiment, the culture time and results may be disclosed in stages, such as when the production amount was Xg / L after 10 hours of culture and Yg / L after 20 hours of culture. As mentioned above, when the impact of small differences in experimental conditions on the experimental results is disclosed, an item called "additional culture experimental conditions" may be added for experiments with small differences between the experimental conditions and other experiments. This can further improve the visibility of the experimental condition table.

[0117] As described above, the strain information table, the experimental conditions table, and the experimental results table all contain the "strain name." This allows the strain information, experimental conditions, and experimental results for a given strain to be associated with each other.

[0118] The strain information table, experimental condition table, and experimental result table all contain an "information source," which associates values ​​of strain information, experimental conditions, and experimental results for experiments on specific strains disclosed in a specific information source.

[0119] As described above, in the strain information table, experimental condition table, and experimental result table, each experiment is defined by an "information source" and a "strain name." Therefore, by referring to the "information source" and "strain name," the user can understand the data for a given experiment in relation to each other.

[0120] (7-2. Flowchart) 13 is a flowchart showing processing of structured data according to Modification 3. In Modification 3, S01A in Modification 2 (FIG. 9) is replaced with S01B, and S04A is replaced with S041 to S043.

[0121] Referring to FIG. 13, in S01B, control device 100 extracts values ​​of experimental conditions, values ​​of strain names, values ​​of strain information, and values ​​of experimental results for a predetermined experiment.

[0122] In S02, the control device 100 determines, from among all the experimental conditions for carrying out a predetermined experiment, second experimental conditions that are not included in the first experimental conditions.

[0123] In S03, the control device 100 supplements the second value of the second experimental condition. In S041, the control device 100 displays an experimental condition table that displays the strain name value and the experimental condition value in association with each other for each predetermined experiment. In one embodiment, the control device 100 displays an experimental condition table that displays the strain name value and the experimental condition value (the first value and the second value obtained in S01B to S03) in the same row for the predetermined experiment.

[0124] In S042, the control device 100 displays a strain information table including a correspondence between the value of the strain name and the value of the strain information for each predetermined experiment. In one embodiment, the control device 100 displays a strain information table in which the value of the strain name and the value of the strain information are displayed in the same row for the predetermined experiment.

[0125] In S043, the control device 100 displays an experiment result table including a correspondence between the strain name value and the experiment result value for each predetermined experiment, and then ends the process. In one embodiment, the control device 100 displays an experiment result table in which the strain name value and the experiment result value are displayed in the same row for a predetermined experiment.

[0126] According to the structured data processing method of Modification 3, in addition to filling in blanks in the first structured data with second values, for each given experiment, the strain information values, experimental condition values, and experimental result values ​​are displayed in independent tables in association with the strain name. Therefore, in addition to the effect of Modification 1, the user can easily grasp the strain information values, experimental condition values, and experimental result values ​​corresponding to a given strain.

[0127] More specifically, by displaying the strain information values, the experimental condition values, and the experimental result values ​​in separate tables, the visibility of each of the strain information values, the experimental condition values, and the experimental result values ​​can be improved, making it easier for users to understand each of the strain information values, the experimental condition values, and the experimental result values.

[0128] Specifically, for example, when a user wants to refer to the value of an experimental result, the user does not have to go through the trouble of searching for the position of the experimental result value in the table, compared to when the strain information value, the experimental condition value, and the experimental result value are all contained in a single table. Also, simply because the amount of information contained in the table (e.g., the number of items and values) is small, it is easier to understand the experimental result value. Therefore, it becomes easier for the user to refer to the experimental result value and select the desired experiment. Similarly, it becomes easier for the user to refer to the strain information value or the experimental condition value and select the desired experiment.

[0129] As a specific example, referring to Figures 10 to 12, paper Y includes 10 experiments, Experiment 13 to Experiment 22, in which multiple experimental conditions were tested using the same bacterial strain C. Therefore, the experimental conditions table and experimental results table show 10 rows of information for each experiment using bacterial strain C in paper Y. However, the strain information table can show the experiment using bacterial strain C in paper Y in a single row. This allows a user to use the strain information to understand the values ​​corresponding to the strains used in paper Y by simply checking the single row corresponding to experiments 13 to 22, rather than having to go through the trouble of checking 10 rows corresponding to each of experiments 13 to 22. Furthermore, when a user refers to the strain information table to check the values ​​corresponding to the bacterial strains in paper X, unnecessary information is less likely to be distracting.

[0130] As described above, in Modification 3, strain information, experimental conditions, and experimental results are each displayed in independent tables with only the minimum necessary items and values. This improves the visibility of each table and reduces the amount of data displayed on display 110. Furthermore, if a value in each table is incorrect, it is easy to correct it. For example, if it turns out that the value of the strain name used in Paper Y was actually "Strain B," the user only needs to change the value of one corresponding cell in the strain information table, and the strain name in the other two linked tables will automatically be changed. This eliminates the need for the user to change the strain name a total of 10 times for Experiments 13 to 22.

[0131] (7-3. Carrying out automated experiments using strain information tables, experimental condition tables, or experimental result tables) Next, a method for performing an automatic experiment using each table will be explained.

[0132] In one embodiment, a user issues a command to perform an automated experiment using the strain information table. For example, the user uses the strain information table to find a row corresponding to an "experiment on E. coli with a specific genetic modification" and designates that row. The control device 100 then converts the experimental condition values ​​contained in the row of the experimental condition table corresponding to the designated row of the strain information table into control signals for the experimental device 200.

[0133] A user may issue instructions for performing an automated experiment using the experimental condition table. For example, the user may use the experimental condition table to find a row corresponding to an "experiment for culturing yeast in a flask" and specify that row. The control device 100 then converts the values ​​of the experimental conditions corresponding to that row into control signals for the experimental device 200.

[0134] The user may use the experiment result table to issue instructions for conducting an automated experiment. For example, the user may use the experiment result table to find a row corresponding to "an experiment to increase ethanol production using E. coli" and specify that row. The control device 100 then converts the values ​​of the experimental conditions contained in the row of the experiment condition table corresponding to that row of the experiment result table into control signals for the experimental device 200.

[0135] (7-4. Linking strain information tables, experimental condition tables, or experimental result tables) As described above, the strain information table, experimental condition table, and experimental result table each associate information about a given experiment using the "information source" and "strain name" as keys. This allows the user to easily understand the relationship between strain information, experimental conditions, and experimental results for a given experiment.

[0136] For example, a user can easily check the strain information values ​​and / or experimental condition values ​​for a specific experiment that produces favorable results found in the experimental results table. For example, a user can check the strain information table for a specific experiment that produces favorable results found in the experimental results table. This allows the user to confirm whether the strain used in the specific experiment is E. coli or yeast, whether it has been genetically modified, what kind of genetic modification has been made, where the strain can be obtained, etc. This allows the user to easily confirm whether the specific experiment can be performed using automated laboratory equipment, whether it is appropriate to perform the experiment using automated laboratory equipment, and whether it is in line with the objectives of the experiment.

[0137] Furthermore, for example, a user may check the experimental condition table for a specific experiment that produces favorable results found in the experimental result table. This allows the user to confirm the experimental conditions under which favorable results were obtained. This allows the user to easily confirm whether the specific experiment can be performed using automated experimental equipment, whether it is appropriate to perform the experiment using automated experimental equipment, and whether the experiment is in line with the objectives of the experiment.

[0138] As described above, by using tables that independently contain values ​​of strain information, experimental conditions, and experimental results according to Modification 3, it becomes easier to gradually understand the experimental results, strain information, and experimental conditions for a given experiment, compared to when values ​​of strain information, experimental conditions, and experimental results are all contained in a single table. Therefore, the three tables according to Modification 3 are useful for presenting values ​​of experimental conditions according to the user's wishes or for adopting them as values ​​for automated experiments.

[0139] The strain information table, the experimental condition table, and the experimental result table may be displayed simultaneously or at different times.

[0140] Preferably, when a specific row is specified in one of the strain information table, the experimental conditions table, and the experimental results table, the corresponding row in the other two tables is specifically displayed. This configuration makes it easier to understand the relationship between the strain information values, the experimental conditions values, and the experimental results values ​​for a specific experiment.

[0141] [Aspect] It will be understood by those skilled in the art that the above-described embodiments and their modifications are specific examples of the following aspects.

[0142] (Item 1) A method for processing structured data according to one embodiment includes the steps of creating structured data using a computer and generating a control signal for operating an automated laboratory device based on the structured data. The structured data includes a plurality of sets, each including an item and a value, for performing a predetermined experiment with the automated laboratory device. The step of creating the structured data includes the steps of extracting a first value to be input into the set from a first information source and filling in blanks in the set with a second value.

[0143] According to the structured data processing method described in paragraph 1, among all values ​​of experimental conditions for conducting a predetermined experiment disclosed in a first information source, values ​​that could not be extracted from the first information source can be supplemented without user operation. Therefore, the predetermined experiment disclosed in the first information source can be conducted. As described above, an experiment in which all values ​​of experimental conditions are not disclosed in a first information source such as a paper or an experimental video can also be conducted using an automated analysis device. In other words, an experiment can be conducted using an automated experiment device using structured data created by extracting experimental condition data from an external source.

[0144] (Section 2) A method for processing structured data according to another aspect includes the steps of creating structured data using a computer and displaying the structured data. The structured data includes a plurality of sets, each including an item and a value, for conducting a predetermined experiment. The step of creating the structured data includes the steps of extracting, from a first information source, a first value to be input into the set, and filling in blanks in the set with a second value.

[0145] According to the structured data processing method described in paragraph 2, among all the values ​​of the experimental conditions for conducting a predetermined experiment disclosed in the first information source, values ​​that could not be extracted from the first information source can be supplemented without user operation. In addition, the supplemented experimental conditions can be visually confirmed.

[0146] (Item 3) In the method for processing structured data described in items 1 or 2, the first information source includes a paper and / or an experimental video.

[0147] In many cases, papers and / or videotapes disclosing a specific experiment also disclose the results and / or purpose of the experiment. Therefore, according to the structured data processing method described in Section 3, a user can refer to the results and / or purpose of the experiment disclosed in the first information source and decide to conduct the specific experiment.

[0148] (Clause 4) In the method for processing structured data described in any one of clauses 1 to 3, the step of supplementing the second value includes a step of determining a second item, among all items for conducting a specified experiment, that is not included in the first item corresponding to the first value, a step of selecting an experiment similar to the specified experiment from the experiments included in the first information source, and a step of extracting a value of the second item for conducting the similar experiment and setting the second value based on that value.

[0149] According to the structured data processing method described in paragraph 4, the second value can be supplemented using the first information source collected to extract the first value, which eliminates the need to collect a new information source to supplement the second value.

[0150] (5) In the method for processing structured data according to any one of paragraphs 1 to 3, the step of supplementing the second value includes the steps of: determining, from among all items for conducting a predetermined experiment, a second item that is not included in the first item corresponding to the first value; selecting an experiment similar to the predetermined experiment from experiments included in a second information source; and extracting values ​​of the second items for conducting the similar experiment and setting the second value based on the values. The second information source includes textbooks.

[0151] According to the structured data processing method described in Section 5, values ​​of common-sense experimental conditions that tend to be omitted from papers and / or experimental videos can be easily supplemented by using descriptions in textbooks that disclose common-sense experimental conditions.

[0152] (Clause 6) In the method for processing structured data described in any one of clauses 1 to 5, the step of supplementing the second value includes the step of displaying multiple candidates for the second value and the step of accepting the selection of the second value to be supplemented from the candidates for the second value.

[0153] According to the structured data processing method described in paragraph 6, the user can select an appropriate value from among the second value candidates.

[0154] (Item 7) In the method for processing structured data described in any one of Items 1 to 6, the first information source includes text data and embedded data embedded in the text data. The embedded data includes a figure or a table. All items for conducting a predetermined experiment include items whose priority in the predetermined experiment is higher than a predetermined threshold and items whose priority in the predetermined experiment is lower than the threshold. The step of extracting first values ​​includes a step of extracting the first values ​​from the text data, and, if there are insufficient values ​​for items whose priority is higher than the threshold even after extracting the first values ​​from the text data, a step of extracting the missing values ​​from the embedded data.

[0155] According to the method for processing structured data described in Section 7, it is possible to obtain the values ​​of important experimental conditions in the minimum amount of time required.

[0156] (Item 8) In the structured data processing method described in Item 2, the step of extracting first values ​​includes a step of extracting values ​​of experimental conditions, values ​​of strain name, values ​​of strain information, and values ​​of experimental results for a predetermined experiment from a first information source. The step of displaying the structured data includes a step of displaying an experimental conditions table that displays, for each predetermined experiment, values ​​of strain name and values ​​of experimental conditions in association with each other, a step of displaying a strain information table that displays, for each predetermined experiment, values ​​of strain name and values ​​of strain information in association with each other, and a step of displaying an experimental results table that displays, for each predetermined experiment, values ​​of strain name and values ​​of experimental results in association with each other.

[0157] According to the structured data processing method described in paragraph 8, the user can easily grasp the strain information values, experimental condition values, and experimental result values ​​for a given strain.

[0158] (Item 9) A program that, when executed by a computer, causes the computer to implement the structured data processing method according to any one of items 1 to 8.

[0159] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0160] 1 Experimental system, 100 control device, 101 processor, 102 memory, 110 display, 120 input device, 200 experimental equipment, 210 medium preparation device, 220 culture device, 230 measurement device, 103 input / output interface, 104 communication interface.

Claims

1. 1. A method for processing structured data relating to an experiment, comprising: creating the structured data using a computer; generating a control signal for operating an automated laboratory device based on the structured data; the structured data includes a plurality of sets, each set including an item and a value, for carrying out a predetermined experiment on the automated laboratory equipment; The step of creating structured data includes: extracting from a first information source a first value to populate said set; and filling blanks in the set with second values.

2. 1. A method for processing structured data relating to an experiment, comprising: creating the structured data using a computer; and displaying the structured data; the structured data includes a plurality of sets each including an item and a value for carrying out a predetermined experiment; The step of creating structured data includes: extracting from a first information source a first value to populate said set; and filling blanks in the set with second values.

3. The method for processing structured data according to claim 1 or 2, wherein the first information source includes a paper and / or an experimental video.

4. The step of replenishing the second value comprises: A step of determining a second item that is not included in the first item corresponding to the first value among all items for carrying out the predetermined experiment; selecting an experiment similar to the predetermined experiment from experiments included in the first information source; The method for processing structured data according to claim 1 or 2, further comprising the step of extracting a value of the second item for carrying out the similar experiment and setting the second value based on the extracted value.

5. The step of replenishing the second value comprises: A step of determining a second item that is not included in the first item corresponding to the first value among all items for carrying out the predetermined experiment; selecting an experiment similar to the given experiment from experiments included in a second information source; extracting a value of the second item for carrying out the similar experiment and setting the second value based on the extracted value; The method of claim 1 or 2, wherein the second information source includes a textbook.

6. The step of replenishing the second value comprises: displaying a plurality of candidates for the second value; The method for processing structured data according to claim 1 , further comprising: receiving a selection of the second value to be filled from among the candidates for the second value.

7. the first information source includes text data and embedded data embedded in the text data; the embedded data includes a figure or a table; all items for carrying out the predetermined experiment include items whose priority in the predetermined experiment is higher than a predetermined threshold and items whose priority in the predetermined experiment is lower than the threshold, The step of extracting the first value comprises: extracting the first value from the text data; The method for processing structured data according to claim 1, further comprising a step of extracting the missing value from the embedded data if there are still missing values ​​for items with a priority higher than the threshold value even after extracting the first value from the text data.

8. The step of extracting the first value comprises: extracting values ​​of experimental conditions, strain names, strain information, and experimental results for the predetermined experiment from the first information source; The step of displaying the structured data includes: displaying an experimental condition table that displays the values ​​of the strain names and the values ​​of the experimental conditions in association with each other for each predetermined experiment; displaying a strain information table that displays the value of the strain name and the value of the strain information in association with each other for each predetermined experiment; 3. The method for processing structured data according to claim 2, further comprising the step of displaying an experiment result table that displays, for each of the predetermined experiments, the value of the strain name and the value of the experiment result in association with each other.

9. A program that, when executed by a computer, causes the computer to carry out the method for processing structured data according to claim 1 or 2.

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