1.1. Key IMAS element: the Data Model

• Joint scientific exploitation of ITER by multiple teams requires a Data Model to name and communicate physical and technical information → ITER Physics Data Model
• The Data Model provides information for data providers and data consumers on…
  • What data exist ?
  • What are they called ?
  • How are they structured as seen by the user ?
• IMAS components use the ITER Physics Data Model to:
  • Read & Write simulation results or experimental data
  • Interface codes together

1.2. The ITER Physics Data Model

• Aims at being the main gate to data for scientific exploitation, both for code interfacing and hands-on data browsing
• is unique for simulated and experimental data (same data structures)
• is device-generic → usable for ITER or any other fusion device
• has precise design rules for global homogeneity
• has precise lifecycle procedure to be able to evolve and be jointly developed by multiple teams

1.3. Interface Data Structures (IDS) to couple codes

• For Integrated Modelling, the Data Model defines Interface Data Structures (IDS). These are structures within the Data Model that are used as standard interfaces between codes
• Solves the N2 problem (large number of components from various ITER members expected in IMAS)
• The usage of the IDSs makes the coupling of codes straightforward if they are in the same programming language
• The usage of the IDSs + AL allows coupling of codes even if they are not written in the same language
• The usage of the IDSs does NOT constrain your choice of coupling method. Codes can be coupled as:
  • Subroutines within a main program
  • Executables within a script
  • Components within a workflow engine

https://portal.eufus.eu/documentation/ITM/imports/itm/public/imas_data_dictionary/3.23.1/dd_data_dictionary.xml.html

1.4. Data Model: Interface Data Structure

• The Data Model has a tree structure, for the sake of clarity
• At the top level, a collection of modular structures representing
  
  • Abstract physical quantities (e.g. distribution functions)
  • Tokamak subsystems (e.g. PF systems)
• These modular structures have the appropriate granularity for exchange in an IM workflow → they also represent standardised interfaces for communication between codes, named Interface Data Structure (IDS)
  • Each has an “ids_properties” substructure (metadata + comments + timebase usage)
  • Each has a “code” substructure (trace the code-specific parameters of the code that has generated this IDS)
  • Each has a generic timebase (“time”)

1.5. Data Model: Occurrences

There can be multiple instances, or “occurrences” of a given IDS in a Database Entry  (see 5.2) or used in an IMAS workflow. These occurrences can correspond to different methods for computing the physical quantities of the IDS, or to different functionalities in a workflow (e.g. store initial values, prescribed values, values at next time step, …).

By default, the IDS name without specification of the occurrence number (e.g. “equilibrium”) corresponds to occurrence “0”. IDS occurrences above the default value (occurrence “0”) are accessed by concatenating the name of the IDS with the occurrence number, with a “/” in between. For example “equilibrium/2” is the name of the occurrence number 2 of the equilibrium IDS. Note that “equilibrium/0” is not valid (temporary limitation).

In the present implementation, there is a pre-set maximum number of occurrences of a given IDS usable in a Database entry or in a workflow. This number is indicated in the documentation in the “Max. occurrence number” column of the list of IDS table. This limitation should be removed in the future

1.6. Data Model documentation

• Dynamically generated

• Open the documentation by typing: dd_doc

1.7. What is in the documentation ?

• List of all IDSs. For each of them, a detailed documentation:
• Full path name: name of all variables of the IDSs, with their path in the structure. Replace “/” by the structure operator in a programming language, e.g. “%” in Fortran, “.” in C++, Matlab, Java, Python
• Description
• Definition
• Units in []
• In {}, whether it is STATIC (constant over a range of pulses, e.g. machine configuration), CONSTANT (constant over the pulse or the simulation), or DYNAMIC (time-dependent within the pulse or the simulation)
• Data_Type: indicates whether it is a string, an integer or a real, and its dimension (0D, 1D, 2D, …)
• Coordinates: for each dimension, the full path name to the related coordinate. If the dimension simply refers to a quantity not present in the Data Model, it is indicated as “1…N”

1.8. IDS can be used in two different ways: Homogeneous timebase or not

• The Data Model provides the flexibility that every node has its own timebase. This is mandatory to represent experimental data as it has been acquired.
  • pf_active%coil(i1)%current%data(itime)
  • pf_active%coil(i1)%current%time(itime)
• However, a frequent use case is that a code will provide its output IDS(s) on a unique timebase
• Therefore there is a simplifying option to use an IDS structure with a homogeneous timebase, i.e. that will apply to all dynamic nodes of the IDS. This timebase is located at the top level of every IDS
  • pf_active%time
• The ids_properties/homogeneous_time flag tells whether the IDS has been written with a homogeneous (unique) timebase (1) or not (0). In the latter case, the coordinates documentation provides the information on the localisation of the timebase in the structure. 
• The code writing the IDS has the responsibility of defining this parameter and fill the appropriate time coordinate(s)

1.9. IDS and time slices

• An IDS potentially contains many time slices, possibly in different time bases
• Because this is used frequently during workflows, time slicing operations are allowed by the Access Layer
  • GET_SLICE returns an IDS with all time dimensions of size 1 (representing thus a single "time slice"). Dynamic signals are interpolated (different options available)
  • PUT_SLICE appends the content of an IDS variable (with all time dimensions of size) to an IDS stored on disk. This allows accumulating time slices in an IDS progressively during a time loop
• More options can be added in the future
• In a Kepler workflow, only the reference of the IDS is circulating, so operations can be performed on this IDS either in SLICE mode or in FULL mode (applies to the full IDS with all time slices)

1.10. Data Entries

• A Data Entry is a collection of potentially all IDS 
• Multiple occurrences of a given IDS can co-exist, e.g. multiple equilibria calculated by different codes / assumptions
• A Data Entry is defined by:
  
  • IMAS version
  • User name
  • Machine name
  • Pulse number
  • Run number

2. Conclusion

• This introduction presented the IMAS basic concepts and some details on the ITER Physics Data Model
• Other training sections will guide you for interfacing codes, generating workflow components, running workflows
• The Physics Data Model User Guide is the technical reference for using IMAS and the Access Layer. You can find it (and many other information) on https://confluence.iter.org/display/IMP

In case of any question, raise it on https://jira.iter.org