- From: Paola Di Maio <paola.dimaio@gmail.com>
- Date: Sun, 24 May 2020 09:20:05 +0800
- To: Paul Alagna <pjalagna@gmail.com>
- Cc: W3C AIKR CG <public-aikr@w3.org>
- Message-ID: <CAMXe=SonSVm_9U5X-519yXuRAawN0px9gcUdYm3gEjyQ-dtHwg@mail.gmail.com>
Paul KRID > A Knowledge Resource IDentifier is the unique name for a particular > Instance of discourse. > who says that? where is this stated? to what discourse does this apply? what type of instance, in which context? It thus becomes a reference point for any discussion of that instance. If > this KRID is stable then it becomes THE reference point for ALL discussions > of that instance. > > very premature to talk about stability, when this identified has not yet been defined sufficiently to be able to talk about it I cannot comment on the rest of your email until I see the taxonomy for KRID please start the definition of KRID in a document, its purpose and explain what kind of values would be there, so that we can understand what you are talking about? Thanks!! > In an XML report knowledge is gathered into its repository (roughly a > storage array) > Information like: > > - Operational information - its position in the report > - And some meta data like tag-name, attributes and values, value after > the tag, peer resolution, etc. > > All of this information needs to be collected under an instance > identifier. The KRID developed for an XML report is by nature unstable. It > only exists for the moment of the XML. > > BUT we can find a stable KRID IF add more information to our repository by > including the XSD’s knowledge. Like a definition identifier and its text. > And it’s this definition identifier as a KRID that is stable across ALL > XML reports in this XSD’s format. > > One of the Goals of The AIKR group is to: > Discover, name and define the usage of XSD information items that can be > added to XML repositories. In AI (machine learning or neural networks) this > KRID names the input/information feed CONSISTENTLY for ALL XML reports in > this XSD format. > > Other information comes from the XSD that can be applied to the XML > report. Like > - a format identifier and its text, > - The provenance (history or lineage) of this “Tag”, the parsing workflow. > format : is this date month/day/year? Or year/month/day? Is this 24 hour > time? Or AM/PM? > Provenance: that a “Goal” has a string format is useful but answering > “Who’s goal under WHAT circumstances” is important too. (see also below for > more). NOTE: To provide provenance AIKR processes MUST follow the rules > laid out by our standards . > - The Parsing workflow: with the advent of “wizards” the validation has > been “worked out” (well until the next version of the XSD comes out) . > “worked out” also means that Validation is reduced to a developer's > afterthought. But with KRID based repositories we can perform extra-session > analysis across XML reports. > like: > Rooting: reducing words to their roots by removing the prefix and suffix. > “Precasts” becomes ‘cast’. Also capitalization is reduced to lower case. > This produces a set of search contenders. > > Acronymization: > > - coring: cores like the dublin core have definitions for known > phrases like : > > “Author of” or > “Date of publication” > > - Industrial cores: all industries have their jargon (a tennis court > is very different from a municipal court , “playing ball” means different > things ) > > Categorization: by usage of different cores for acronymization industrial > categories can be registered. > > Patterns: phone numbers have a unique pattern, as do zip codes, URI’s and > filenames. All of these add to our knowledge. > > Framing and frame completion: > Framing simply is the discovery of the largest domain under a reduced tag. > A “reduced tag” is an endpoint in a provenance chain. > This point can have several value choices, the collection of which is > called its domain. > From one XML to the next XML the largest set can be collected. Thereafter > this set can be offered to the XML creator as a possible set of options. OR > offered to the XML report creator as an option for expansion or improvement. > > > > definitions: > In data science we acknowledge: > Dominion: the “table” in an SQL Database is the dominion of discourse. In > object class definition we acknowledge the class to be the dominion. > > Attribute: column names in an SQL database. > > Peers: a set of attributes associated with a dominion. > > Attribute;value pair: an attribute AND its value (one of its Domain values) > > Dominion instance or instance: An instance is a named or keyed set of peer > attributes in a Dominion > > Instance key: the unique name or set of attribute;value pairs that > uniquely identify this instance. > > Domain: for each attribute there can exist a set of values called the > “domain” of that attribute. > > Provenance: > https://www.w3.org/TR/prov-aq/ > Provenance records for dynamic and context-dependent resources are > possible through a notion of constrained resources. A constrained resource > <https://www.w3.org/TR/prov-aq/#dfn-constrained-resource> is simply a > resource (in the sense defined by [WEBARCH > <https://www.w3.org/TR/prov-aq/#bib-WEBARCH>], section 2.2 > <http://www.w3.org/TR/webarch/#id-resources>) that is a specialization or > instance of some other resource. For example, a W3C specification typically > undergoes several public revisions before it is finalized. A URI that > refers to the "current" revision might be thought of as denoting the > specification throughout its lifetime. Each individual revision would also > have its own target-URI <https://www.w3.org/TR/prov-aq/#dfn-target-uri> > denoting the specification at that particular stage in its development. > Using these, we can make provenance assertions that a particular revision > was published on a particular date, and was last modified by a particular > editor > > > > > Paul > Thoughts? , comments? > > Thanks > PAUL ALAGNA > PJAlagna@Gmail.com <PJAlagna@gmail.com> > 732-322-5641 > > > >
Received on Sunday, 24 May 2020 01:20:56 UTC