- From: Paola Di Maio <paoladimaio10@gmail.com>
- Date: Tue, 26 May 2020 07:26:38 +0800
- Cc: ProjectParadigm-ICT-Program <metadataportals@yahoo.com>, W3C AIKR CG <public-aikr@w3.org>
- Message-ID: <CAMXe=SqisC99CwxhZKShXHr_OggwT6avvk9iF9Wz33NVvX5tsA@mail.gmail.com>
Either way it would be interesting to see - what kind of use could it have in what context, etc we cannot realistically evaluate a property which has not yet been formulated pdm On Tue, May 26, 2020 at 12:48 AM carl mattocks <carlmattocks@gmail.com> wrote: > Milton > Thanks for critique. I am in total agreement about the complexity of the > challenge. I also agree that using > information ( and Data) science methods are essential... Especially if > augmented by AI Strategist plans. > > Carl > > > > On Mon, May 25, 2020, 12:02 PM ProjectParadigm-ICT-Program < > metadataportals@yahoo.com> wrote: > >> I would like to DISAGREE on the UNIQUENESS of a KRID. Whereas in linked >> data and semantic web technologies we can create UNIQUE identifiers for >> data, this is not the case for knowledge. In our modern world thousands of >> scientific domains of discourse exist, and even agreeing upon uniquely >> naming each of these can get us into trouble. >> >> There will always be ambiguity in knowledge, both in the domains of >> discourse or instances or identified objects therein. The closest we will >> get is unique coding systems as used in library information systems. >> >> The problem is natural language, its richness allows us multiple ways to >> exactly describe the same things, and just like there are synonyms in >> natural language, there are competing terminologies in similar but slightly >> different domains of discourse. >> >> Milton Ponson >> GSM: +297 747 8280 >> PO Box 1154, Oranjestad >> Aruba, Dutch Caribbean >> Project Paradigm: Bringing the ICT tools for sustainable development to >> all stakeholders worldwide through collaborative research on applied >> mathematics, advanced modeling, software and standards development >> >> >> On Saturday, May 23, 2020, 10:21:00 PM ADT, Paola Di Maio < >> paola.dimaio@gmail.com> wrote: >> >> >> 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 Monday, 25 May 2020 23:27:29 UTC