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  2. Data management plan - Wikipedia

    en.wikipedia.org/wiki/Data_management_plan

    A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; [2] this may lead to data being well-managed in the present ...

  3. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    Data management comprises all disciplines related to handling data as a valuable resource, it is the practice of managing an organization's data so it can be analyzed for decision making. [ 1 ] Concept

  4. Good clinical data management practice - Wikipedia

    en.wikipedia.org/wiki/Good_Clinical_Data...

    Good clinical data management practice (GCDMP) is the current industry standards for clinical data management that consist of best business practice and acceptable regulatory standards. In all phases of clinical trials , clinical and laboratory information must be collected and converted to digital form for analysis and reporting purposes.

  5. ISO 8000 - Wikipedia

    en.wikipedia.org/wiki/ISO_8000

    ISO 8000 is the international standard for Data Quality and Enterprise Master Data.Widely adopted internationally [1] [2] [3] it describes the features and defines the requirements for standard exchange of Master Data among business partners.

  6. Clinical data management - Wikipedia

    en.wikipedia.org/wiki/Clinical_data_management

    The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure

  7. FAIR data - Wikipedia

    en.wikipedia.org/wiki/FAIR_data

    The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (Meta)data use vocabularies that follow FAIR principles I3.