Stage 3: Collecting and analyzing data

You can collect and process primary data in the electronic lab journal, the eRIC Workbench. Furthermore, the eRIC team will develop customised tools, such as interfaces for automated data import or methods for extracting technical metadata to the lab journal, on request. 

 

 

   

 

    

 

Data collection and storage

Primary data may be entered in various ways. This can be done manually or automatically via standardised interfaces.

  • Manual data collection
    • Ability to automate the creation and management of survey projects.
    • Manual data collection: development of a tool for flexible creation of questionnaires.
    • Data collection: conducting and managing surveys based on generated samples. 
  • Automated data collection
    • Development of interfaces and method for connecting to external systems via SOAP.
    • Design of communication with file systems and tracking changes in the data storage of measuring equipment.
    • Implementation of an interface for automated import of data from measuring equipment. 
  • Collecting data using mobile devices
    • Develop a mobile application (app) for Android for access and data transfer to mediaTUM.
    • Extension of an existing iOS app for data collection and management.

Organisation, evaluation and documentation of data

Almost every research data type contains descriptive information (metadata). The project objective is the analysis of research data and the subsequent extraction and storage of associated metadata for further use within the research project.

  • Analysis of primary and secondary data: metadata creation
    • Development of methods for extracting technical metadata and parameter values of primary and secondary data.
    • Extension of interfaces for automated research data import for the transmission of technical parameters and device settings in experiments.
    • Development of standards for the formatting of the metadata collected.
    • Implementation of user interface to manage metadata. 
  • Organisation and documentation of primary and secondary data
    • Development of a tool for the storage and organisation of primary and secondary data including associated metadata.
    • Integration of data into the "Lab Notebook" and project documentation.
    • Expansion of existing mechanisms for long-term preservation of research data.

Filtering, analysis and visualisation of primary and secondary data

For researchers, the evaluation of the stored data is an important milestone in the research project. The aim is therefore to create mechanisms for filtering data and connecting the system to external evaluation tools. This permits both qualitative and quantitative evaluation. Analysis will be facilitated through visualisation of research data at various stages of processing.

  • Filtering of data
    • Implementation of a user interface for filtering research data based on configurable parameters by the researchers. 
  • Analysis of data
    • Integration of required functions or development of interfaces for data exchange with various external systems: integration of tools for statistical data analysis, pattern recognition, and transcription tools.
    • Ability to save and describe evaluation results.
    • Adaptation of standardised interfaces to external analysis tools to meet the specific requirements of research project partners. 
  • Visualisation of data
    • Integration of external tools for visualisation or integration of the functions required within the eRIC framework.