Ok thanks so this is the solution I was asking for. We can separate between technosphere and rest by using an external list of names. And yes you are right about the matrix operation it will work even if the order of columns and rows is not the same. So we neither need the ref flow predicate nor any product subclass in the ontology.
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On 20 Mar 2019, at 15.29, Chris Mutel via Groups.Io <email@example.com> wrote:
On Wed, 20 Mar 2019 at 12:30, Massimo Pizzol <firstname.lastname@example.org> wrote:This is a great comment, and is to me a perfect example of how
“product”, “emission”, etc. are subjective.
Agree, and formalizing them limits our flexibility. But indeed some of those might be useful to work in LCA context. I think that the only two pieces of information we actually need for doing LCA are: if a flow belongs to the technosphere (all the rest is B matrix) and if a flow is a reference flow (diagonal of tech matrix). Right now I can’t think of any automatic way of determining this information from a raw list of inputs and outputs. So we have to include this info in the ontology because we can’t use an algorithm or write a code to figure this out. But perhaps I am wrong and somebody in the group has a solution for this and then we can skip these classifications altogether, that would be perfect. I also recognize that this means introducing some subjective elements in the model, because who decides what is technosphere? But as I wrote before if we want to use the liked data for LCA we have to accept that there is an LCA framework.
people's experience leads them to accept restraints without even
1. Mathematically, we don't need to distinguish between technosphere
and biosphere, this can be one big matrix. In practical terms, our
biosphere will be a different set of names; or, they will be flows for
which there is no associated producing activity.
2. We don't need the concept of a reference flow to make a
technosphere matrix, and there isn't anything special about positive
numbers of the diagonal. Production amounts can be randomly ordered,
and in any case everything produced is positive, everything consumed
is negative, regardless of whether it is a reference product,
co-product, or whatever. The notion of reference product is helpful
for humans trying to understand the reason a particular dataset was
modelled, but irrelevant for the computer doing the math.