Feature/Fix gui name rename crash

[ThomasKroes]

This pull request refactors the ScalarSourceModel and related classes to use a more flexible and extensible item-based model, transitioning from QAbstractListModel to QStandardItemModel. The changes improve dataset management, enable support for multiple columns (such as name and ID), and clean up how datasets are tracked, displayed, and updated in the UI.

The most important changes are:

Model architecture and extensibility

• Refactored ScalarSourceModel to inherit from QStandardItemModel instead of QAbstractListModel, enabling support for multiple columns and more flexible item management. Introduced Item, NameItem, and IdItem classes to represent dataset properties as model items. [1] [2] [3]
• Added a Row helper class to group related items (name and ID) for each dataset, simplifying row management and data retrieval.

Dataset management improvements

• Replaced the internal _datasets list with dynamic item-based tracking, updating all methods (addDataset, removeDataset, getDatasets, etc.) to operate on the model's items. This improves robustness and reduces manual bookkeeping. [1] [2]
• Improved dataset lookup and row indexing using the dataset's unique ID, making operations like hasDataset, removeDataset, and getRowIndex more reliable and efficient. [1] [2]

API and usability changes

• Added support for multiple columns (Name and ID), with custom header data and per-role display logic for each item type.
• Updated method signatures for clarity and correctness, such as changing setCurrentSourceIndex to take a std::int32_t instead of bool, and using {} for default-constructed return values. (src/ScalarAction.hL54-R54, F3d0657dL72R75)

Code cleanup and removal of obsolete logic

• Removed the now-unnecessary updateData method and related manual update logic, since data changes are now handled by item signals and the model's structure.
• Commented out an obsolete signal connection in ScalarAction::addDataset, clarifying its redundancy. [1] [2]

These changes collectively modernize the dataset model, improve maintainability, and lay the groundwork for future UI enhancements.