1
0
-1
1 respuesta
- 10-1
Hi Richard -
Once you create a k.LAB project of your own, import new data as resources, and annotate them using the same semantics as those used as inputs to an ARIES model, the machine reasoner in k.LAB chooses your data over the global data when the model is run in your context of interest (i.e., which overlaps with your local data), effectively customizing your model.
To understand how to do this, you should definitely dedicate substantial time to learn how to use k.Modeler. Sections 0 and 1 of k.IM Quick Tips (beginning here 0. Getting started) provide this background; Section 2 is important for learning how to write new models and customize existing ones while Section 3 covers advanced topics.
Regards,
KenAñada su comentario...
Hi
I've now managed to start using k.Explorer to work on my research area in New Zealand. As part of my research, I wish to add locally sourced data (soil tests etc.) to the analysis provided by the coarser datasets used by k.Explorer / ARIES. Reading the guidance online, the only reference I can find on how to do this is under k.Modeller quicktips @ 1.1.1 Importing raster data, which details this drag and drop approach for bringing in raster or vector data into the model:
However I am not clear on how this will update the map I'm developing in k.Explorer. Could you please advise?
Am I correct in assuming that for the purposes of my research I will need to invest more of my time in learning how to use k.Modeller (ie k.Explorer, and SEEA Explorer will not be able to deliver the level of specific, localised analysis I require)? This is OK, I would just appreciate confirming this before I start spending considerable time learning the platform.
Many thanks
Richard