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Welcome to MDF

What is MDF?

MDF stands for Multipurpose Data Framework. It is a framework geared toward managing experimental data and the metadata data associated with it.

Everything in the MDF is rapresented as an object. The mdf object is the smallest entity that can be created within the framework. It can be populated with data and metadata on-the-fly without previous definition. The user instantiate the object and can start populate it right away. Each object is identified by a unique id and has a type associated. By default the unique id is a uuid (, but any string can be assigned as id, as long as it is unique within the same group of objects. The object type can be defined as the best string to describe the object created and its data. There are no limitations within the system, it can be any string that the user would like to use. It is suggested to define the type as a short string to uniquely identify the type of data and metadata that is contained in the object itself. It is also suggested to use consistent type across object that represents and contains the same type of data and info.

It is considered data any time series or any series of numeric values acquired through measurement or sampling. They are usually vectors or matrix. On the contrary metadata are any property that describe and define the data saved in this object and by definition is simple and limited in dimension. There is no limitation of what goes in metadata and in data, it is up to the user to decide. One difference defined by designed is that metadata are loaded when the object is retrieved and created in memory, while data follow the lazy-loading paradigm: they are loaded in memory only when they are accessed. Metadata and object definition can be queried by means of the mongodb instance that the MDF uses transparently.

Current active branch is 1.6.x. Latest/Current version is 1.6.2

Deprecated versions (please do not use them):

  • 1.4.x
  • 1.5.x


This section contains instructions on how to set up the latest/current versionof MDF

  • Requirements / Dependencies You need to have oneof the latest versionof Matlab installed and mongodb, which could be installed locally, in a docker container (please check mdf-db project) or on a remote machine. The current version has been tested on:

    • Matlab R2019b, mdf-db v2.0 (Mongodb 4.2)
    • Matlab R2018a, mdf-db v2.0 (Mongodb 4.2)
  • Install MDF Clone prod-v1.6 branch or download the zip file for tag v1.6.2. Place the code in a folder that is accessible to matlab. We suggest C:/GIT/mdf under windows, or /opt/mdf under linux

  • Configuration Start matlab, make sure to add mdf/mMdf/core folder to your matlab path. Also make sure that you have an instance of MongoDB running and that it is accessible fromt he machine where you are running matlab. If you do not want to add permanently mdf to your matlab path, you can use the function StartMdf that you can find under mdf/mMdf/templates. Copy it in your MATLAB folder and personalize it to your setup

  • Data Collection configuration MDF uses an xml configuration file to define which data collections are accessible. Please check under mdf/templates for confiuguration examples. By default, when mdf.init or StartMdf is called, mdf looks for the file mdf.conf.xml. Multiple configurations can be used on the same machine. Just copy everything within the configuration tags and change as it is needed. MDF will automatically check the following folders in the user home (Linux: /home/, OS X: /Users/, Windows: /Users/) for the mdf.conf.xml file:

    • .mdf
    • mdf
    • .MDF
    • MDF
    • .rnel
    • rnel
    • .RNEL
    • RNEL
    • MATLAB
    • Documents/MATLAB

    If the user would like to store the configuration file in other locations or wants to use an alternative one, just pass the full path to the conf file as it is specified in the next section

  • Matlab Startup In order to start using mdf, the user has to instantiate the core classes. The main class mdf provides a static method to set up the correct environment. Here are the different method that mdf environment can be initialized:

    • let mdf check the standard location and ask which configuration we would like to use omdfc = mdf.init()
    • specify configuration file omdfc = mdf.init('<configuration_file_path>')
    • specify which configuration (#2 in this example) we would like to use specified in the configuration file saved in a standard location omdfc = mdf.init(2)
    • specify both configuration file and configuration to load omdfc = mdf.init('<configuration_file_path>',2)
    • specify both configuration file and configuration to load using a matlab struct omdfc = mdf.init( struct( 'confFile', '<configuration_file_path>', 'confSel', 2))

    The value returned by mdf.init and saved in omdfc is a structure with handler to the core classes used in the mdf environment: omdfc = mdf: [1x1 mdf] conf: [1x1 mdfConf] db: [1x1 mdfDB] manage: [1x1 mdfManage]

    where mdf is class containing useful methods used throughout the framework, conf contains all the value defined in the configuration file, db is the connection to the database and manage is the memory management class. User should not be concern with this variable unless any troubleshooting is required.

  • How to test MDF on your platform

    • Linux

      • install mdf code in a folder that matches your needs
      • create the following structure under your home folder +- mdf +- conf +- data
      • make sure that mongodb is running on your local machine and is accepting connection on the standard port
      • open matlab and addpath mdf core folder <your_installation_folder>/mdf/mMDF/core
      • run the test environment 1 script in mdf/mMDF/test omdfc = testEnv1() this function should instantiate the correct mdf environment for the test, populate with a test hierarchical structure and return the omdfc data structure as specified above. it uses the following configuration file mdf/mMDF/templates/mdf.conf.test.env1.xml
      • Once the script has run successfully, you should find the omdfc variable in your matlab workspace.
      • If you do not find omdfc defined in your workspace, you can instantiate it with the following command: omdfc = mdf.init('<your_home_folder>/mdf/conf/mdf.conf.test.env1.xml')
      • you can now start exploring the test data from the root object that is of type subject: sbj = mdf.load(struct('mdf_type':'subject')
    • OS X coming soon

    • Windows coming soon


Multipurpose Data Framework






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