CN113140259A - Biomedical data classification management control method and system based on cloud storage - Google Patents
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Abstract
The invention relates to a biomedical data classification management control method based on cloud storage, which comprises the following steps: s1, acquiring newly submitted biomedical data; s2, judging whether the same attribute information types exist or not according to the attribute information and the sample name information, if so, storing the attribute information types under the corresponding attribute information types, and if not, adding new attribute information types; s3, judging whether the new attribute information type has the synonymous attribute information type, if so, turning to S4, and if not, turning to S5; s4, sending prompt information for reselecting the attribute information category; s5, acquiring audit information of an administrator, judging whether the audit is passed, if so, expanding and classifying and storing the new type of data, and if not, sending prompt information for modifying the new attribute information type and resubmitting; s6, assigning a data ID to the newly submitted biomedical data. Compared with the prior art, the method has the advantages of realizing the classified storage of the multivariate biomedical big data, disambiguating the category of the synonymous attribute information and the like.
Description
Technical Field
The invention relates to the technical field of data management, in particular to a biomedical data classification management control method and system based on cloud storage.
Background
In the 21 st century, with the rapid development and application of technologies such as high-throughput sequencing, single-cell sequencing and mass spectrometry, various biological and medical data are continuously accumulated. According to statistics, general medical institutions generate data of 1-20 TB every year, and the annual data volume of individual large hospitals even reaches 300 TB-1 PB. How to effectively store and manage biomedical data of PB-EB magnitude generated in the precise medical era and further effectively serve for clinical data analysis and research is a main research topic at present. Currently, some systems (database systems) for storing biomedical big data can store data submitted by a user through a web-side system, and can also realize quick update of the data and support the user to perform basic data management operations such as access, release and download of the data. For example,
1) the GEO database is the largest and most comprehensive public gene data platform in the world at present, and provides storage and release of free chip data and second-generation sequencing data;
2) linkedOmics is both a database and a Web-based analysis platform. The database contained multiple sets of scientific and clinical data from 32 cancers and 11158 patients from a cancer genomic map (TCGA) project. The platform is also the first multigenomic database integrating Mass Spectrometry (MS) based proteomics data;
3) UCSC Xena is also a large cancer database and a Web-based analysis platform. UCSC Xena includes a front Xena Browser and a background Xena Hubs. The platform has included data for over 50 cancer types and over 1500 datasets, including data in cancer genomic map (TCGA), international association of cancer genomes (ICGC), shared regions of Genomic Data (GDC) and UCSC RNA-seq.
Besides the 3 examples described above, there are many platform systems for biomedical big data storage. However, these platforms still have many disadvantages, namely that sensitive data of colleges, research institutions and hospitals cannot be uploaded to the public data storage platforms; and secondly, the stored biomedical data is single in type and cannot be called and analyzed on line by a standard analysis workflow. This causes inconvenience to researchers and clinical studies. Therefore, a public, safe, efficient and biomedical data cloud storage platform which stores multiple data types and can be linked with an online analysis operating system is urgently needed in the prior art.
Disclosure of Invention
The invention aims to provide a biomedical data classification management control method and system based on cloud storage, aiming at overcoming the defects of poor privacy, single type of stored biomedical data, and incapability of being called and analyzed by a standard analysis workflow on line in the prior art.
The purpose of the invention can be realized by the following technical scheme:
a biomedical data classification management control method based on cloud storage specifically comprises the following steps:
s1, obtaining biomedical data newly submitted by a user;
s2, judging whether the same attribute information categories exist or not according to the attribute information and the sample name information of the biomedical data, if so, storing the same attribute information categories in the corresponding attribute information categories, and if not, adding the corresponding new attribute information categories;
s3, judging whether the new attribute information type has the synonymy attribute information type, if so, turning to the step S4, otherwise, turning to the step S5;
s4, sending prompt information for reselecting the attribute information category;
s5, acquiring audit information of an administrator, judging whether the new attribute information type passes the audit or not according to the audit information, if so, expanding and storing the new type data corresponding to the new attribute information type in a classified mode, and if not, sending prompt information for modifying the new attribute information type and resubmitting;
and S6, assigning a data ID to the newly submitted biomedical data completing the classification of the attribute information categories, and completing the storage of the categories.
The data ID has uniqueness.
The attribute information of the biomedical data comprises classification, experiment platform, data format, sample organization source and sample type.
The process of adding the corresponding new attribute information category in step S2 further includes uploading a compressed file of the biomedical data, and setting a privacy authority of the biomedical data.
Further, the types of privacy rights include public, semi-public, and personal.
Further, the public type of privacy permissions specifically corresponds to biomedical data that all users can retrieve, view, and download; the semi-public type privacy authority specifically corresponds to the biomedical data which can be retrieved by all users but can be downloaded by the users only uploading the data; the privacy permissions of the individual type specifically correspond to biomedical data that can be retrieved, viewed and downloaded by users who only upload this data.
The management system comprises a data warehousing subsystem, a data classification subsystem and a cloud storage subsystem, the management system is connected with a data analysis system, and an analysis workflow of the data analysis system calls corresponding biomedical data from the data warehousing subsystem through a data ID.
The cloud storage subsystem stores data files submitted by users through the allocated data IDs.
The management system also comprises a personal central control module which is respectively connected with the data warehousing subsystem and the data analysis system.
The personal central control module performs management operations on the biomedical data stored therein through the data warehousing subsystem.
Further, the management operation executed by the personal central control module in the data warehousing subsystem comprises deletion, downloading and privacy authority setting.
The data analysis system calls biomedical data through an analysis workflow to perform data analysis or data visualization and generates an analysis result, wherein the type of the analysis result comprises an image and a form.
Further, the principle of data analysis or data visualization performed by the data analysis system is specifically that a data interface established between the data analysis system and the data warehousing communication system provides a relevant computing and operating environment for data analysis requirements.
Further, a result display sub-module is arranged in the personal central control module, and the result display sub-module acquires and displays an analysis result of the data analysis system.
Compared with the prior art, the invention has the following beneficial effects:
1. in the invention, a user can expand the self-defined attribute information category by adding the attribute information, and a new attribute information category is added in an original storage system, compared with the defects that the user cannot support the self-defined expansion of the categories of the attribute information such as the classification of a newly submitted data type, a data format and the like and the data storage type is single or limited in the prior art, the data storage type supported by the invention is more diversified, more friendly and more efficient, the classified storage of the multivariate biomedical big data is realized, and the experience of the user in the aspect of managing the biomedical big data is improved.
2. The invention disambiguates the stored data by judging whether the new attribute information category has the synonymous attribute information category or not, wherein the new attribute information category with the repeated or similar semantics needs to modify the new attribute information category and re-upload the data, thereby effectively avoiding the repeated setting of the attribute information category with the semantic type in the storage system and occupying the storage space, and simultaneously, the similar attribute information category is easy to generate errors when specifically calling the data.
Drawings
FIG. 1 is a schematic flow chart of a control method according to the present invention;
FIG. 2 is a schematic overall flow chart of the present invention;
FIG. 3 is a schematic structural diagram of a management system according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
As shown in fig. 1, a biomedical data classification management control method based on cloud storage specifically includes the following steps:
s1, obtaining biomedical data newly submitted by a user;
s2, judging whether the same attribute information types exist or not according to the attribute information and the sample name information of the biomedical data, if so, storing the attribute information types under the corresponding attribute information types, and if not, adding the corresponding new attribute information types;
s3, judging whether the new attribute information type has the same attribute information type, if yes, turning to the step S4, otherwise, turning to the step S5;
s4, sending prompt information for reselecting the attribute information category;
s5, acquiring audit information of an administrator, judging whether the new attribute information type passes the audit according to the audit information, if so, expanding and classifying and storing new type data corresponding to the new attribute information type, and if not, sending prompt information for modifying the new attribute information type and resubmitting;
and S6, distributing data ID to the newly submitted biomedical data which completes the classification of the attribute information category, and completing the classified storage.
The data ID has uniqueness.
In this embodiment, the types of multivariate biomedical data include second and third generation omic sequencing data, methylation data, mass spectrometry data, medical image data, and clinical medical information data.
The attribute information of the biomedical data includes classification, experimental platform, data format, sample organization source and sample type.
The process of adding the corresponding new attribute information category in step S2 further includes uploading a compressed file of the biomedical data and setting privacy rights of the biomedical data.
Types of privacy authorities include public, semi-public, and personal.
The public privacy authority is specifically corresponding to biomedical data which can be retrieved, checked and downloaded by all users, and is suitable for the published data types;
the semi-public privacy authority specifically corresponds to the biomedical data which can be retrieved by all users but can be downloaded by the user who only uploads the data, and is suitable for the data types which are published but can not be disclosed;
the privacy permissions of the individual types specifically correspond to biomedical data that can be retrieved, viewed and downloaded by users who only upload this data, and are applicable to the data types of privacy.
As shown in fig. 3, a management system using a cloud storage-based biomedical data classification management control method includes a data warehousing subsystem, a data classification subsystem and a cloud storage subsystem, the management system is connected with a data analysis system, and an analysis workflow of the data analysis system calls corresponding biomedical data from the data warehousing subsystem through a data ID.
In this embodiment, the data warehousing subsystem is built at a Web end, and performs operations such as retrieval, access, upload, classification of self-expansion storage data types, attribute information such as data formats, downloading, deletion, privacy authority management and the like on data in the cloud storage subsystem and the classification management subsystem.
The cloud storage subsystem stores the data files submitted by the users through the allocated data IDs.
The management system also comprises a personal central control module which is respectively connected with the data warehousing subsystem and the data analysis system.
The personal central control module performs management operations on the biomedical data stored therein through the data warehousing subsystem.
The management operation executed by the personal central control module in the data warehousing subsystem comprises deletion, downloading and privacy authority setting.
The data analysis system calls the biomedical data through the analysis workflow to perform data analysis or data visualization and generates an analysis result, wherein the type of the analysis result comprises an image and a form.
The principle of data analysis or data visualization performed by the data analysis system is specifically that a data interface established between the data analysis system and the data warehousing communication system provides a relevant computing and operating environment for data analysis requirements.
And a result display submodule is arranged in the personal central control module and used for acquiring and displaying an analysis result of the data analysis system.
As shown in fig. 2, in this embodiment, the workflow of the management system is specifically as follows:
401. a user logs in a personal center module and clicks data storage;
402. if the data is to be newly submitted and stored, go to step 403, otherwise go to step 405;
403. selecting attribute information such as classification of submitted and stored data, an experimental platform, a data format, a sample organization source and a sample type, and filling in information such as a sample name. If the attribute information type corresponding to the user data does not exist in the options of the attribute information such as the data classification, the experiment platform, the data format, the sample organization source, the sample type and the like, the user can expand the self-defined attribute information type by adding the attribute information, then upload the compressed file of the data, and finally click and submit the data after selecting the privacy authority of the data;
404. and the classification management subsystem judges whether the attribute information of the data submitted by the user is of a new class. If the newly added attribute type has the synonymous attribute information type in the system, the system prompts a user to reselect the attribute information of the data through a web interface, so that disambiguation of the attribute information such as classification and the like is realized;
405. if the newly added attribute type does not have the synonymous attribute information type in the system, the system informs an administrator to perform auditing, and the expansion and classified storage of the new type data can be performed after the auditing is passed; if the verification is not passed, the user is informed to modify the newly added attribute information category and to resubmit the data;
406. the data warehousing subsystem distributes a unique data ID to the data newly submitted by the user;
407. if the data is not newly submitted and stored, the uploaded data can be checked or retrieved through a classification management system of data warehousing;
408. in the personal center module, through the data warehousing subsystem, a user can perform management operations such as deletion, downloading, privacy authority setting and the like on stored data;
409. a user can call biomedical data stored in the data warehouse for analysis or data visualization through an analysis workflow in the data analysis system, and feeds back an analysis result to a display page of a result display submodule of a Web end;
410. the user can view and download the analysis results of the data analysis system in the result display submodule of the personal center module.
In addition, it should be noted that the specific embodiments described in the present specification may have different names, and the above descriptions in the present specification are only illustrations of the structures of the present invention. All equivalent or simple changes in the structure, characteristics and principles of the invention are included in the protection scope of the invention. Various modifications or additions may be made to the described embodiments or methods may be similarly employed by those skilled in the art without departing from the scope of the invention as defined in the appending claims.
Claims (10)
1. A biomedical data classification management control method based on cloud storage is characterized by comprising the following steps:
s1, obtaining biomedical data newly submitted by a user;
s2, judging whether the same attribute information categories exist or not according to the attribute information and the sample name information of the biomedical data, if so, storing the same attribute information categories in the corresponding attribute information categories, and if not, adding the corresponding new attribute information categories;
s3, judging whether the new attribute information type has the synonymy attribute information type, if so, turning to the step S4, otherwise, turning to the step S5;
s4, sending prompt information for reselecting the attribute information category;
s5, acquiring audit information of an administrator, judging whether the new attribute information type passes the audit or not according to the audit information, if so, expanding and storing the new type data corresponding to the new attribute information type in a classified mode, and if not, sending prompt information for modifying the new attribute information type and resubmitting;
s6, assigning a data ID to the newly submitted biomedical data that completes the classification of the attribute information category.
2. The biomedical data classification management and control method based on cloud storage as claimed in claim 1, wherein the attribute information of the biomedical data comprises classification, experiment platform, data format, sample organization source and sample type.
3. The method for classified management and control of biomedical data based on cloud storage according to claim 1, wherein the step S2 of adding the corresponding new attribute information category further comprises uploading a compressed file of biomedical data and setting privacy authority of the biomedical data.
4. The biomedical data classification management control method based on cloud storage as claimed in claim 3, wherein the types of privacy authority include public, semi-public and personal.
5. The management system using the biomedical data classification management and control method based on the cloud storage as claimed in claim 1 is characterized by comprising a data warehousing subsystem, a data classification subsystem and a cloud storage subsystem, wherein the management system is connected with a data analysis system, and an analysis workflow of the data analysis system calls corresponding biomedical data from the data warehousing subsystem through the data ID.
6. The management system using the cloud storage based biomedical data classification management control method is characterized by further comprising a personal central control module, wherein the personal central control module is respectively connected with the data warehousing subsystem and the data analysis system.
7. The management system using the biomedical data classification management control method based on cloud storage as claimed in claim 6, wherein the personal central control module performs management operation on the biomedical data stored therein through a data warehousing subsystem.
8. The management system using the biomedical data classification management control method based on the cloud storage is characterized in that the management operations performed by the personal center control module in the data warehousing subsystem comprise deletion, downloading and privacy authority setting.
9. The management system using the cloud storage based biomedical data classification management control method according to claim 6, wherein the data analysis system calls biomedical data through an analysis workflow to perform data analysis or data visualization and generate an analysis result.
10. The management system using the cloud storage-based biomedical data classification management control method according to claim 9, wherein a result display sub-module is arranged in the personal central control module, and the result display sub-module obtains and displays an analysis result of the data analysis system.
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