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Are questions such as:

  • What metadata is required to make a specific data product useable (and how should I format it?)
  • How can I make sure my raster data complies with standard X?
  • What type of metadata format should I use for data of type Y?
  • Is there a preferred vocabulary or ontology for data in domain Z?

On topic?

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  • $\begingroup$ Any examples? I'm still on the borderline on those :) $\endgroup$ – Dawny33♦ May 13 at 5:13
  • $\begingroup$ @Dawny33: datascience.stackexchange.com/questions/51768/… $\endgroup$ – Stephen Rauch♦ May 13 at 23:05
  • $\begingroup$ Gotha. I think they are on-topic if properly structured w.r.t a particular algorithm. However, they are very prone to get off-topic/broad. @StephenRauch what do you think? $\endgroup$ – Dawny33♦ May 14 at 2:33
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    $\begingroup$ @Dawny33 why wrt a particular algorithm? I'd like to create data that can be used by many types of algorithms. $\endgroup$ – David LeBauer May 14 at 4:19
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They probably belong to this spectrum of questions that could be on topic on multiple sites. Questions about portability lean more towards the implementation side and are possibly more appropriate for software engineering stackexchange.

Compliance questions, in my opinion, are off-topic here unless they have some clear connection to the "science" part of data science.

Questions like

Is there a preferred vocabulary or ontology for data in domain Z?

are probably also on topic on open data stackexchange.

In general, I think other sites will generate more and better answers. However, at this point it's fair to assume that they will be decided on a case by case basis if posted here first.

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