- From: Graham Klyne <graham.klyne@zoo.ox.ac.uk>
- Date: Tue, 08 May 2012 13:20:28 +0100
- To: Paul Groth <p.t.groth@vu.nl>
- CC: W3C provenance WG <public-prov-wg@w3.org>
On 06/05/2012 12:01, Paul Groth wrote: > It would really be good to get specific suggestions from you. What > should be cut? What should be changed? <TL:DR> For "normal" developers: 1. A simple structural core model/vocabulary for provenance, also identifying extension points 2. Common extension terms 3. Ontology (i.e. expressing provenance in RDF) 4. A simple guide for generating provenance information For advanced users of provenance: 5. Formal semantics (incorporating PROV-N) 6. An advanced guide for using and interpreting provenance </TL:DR> ... Paul, I've been thinking about your question, and will try to articulate here my thoughts. They will be quite radical, and I don't really expect the group to accept them - but I hope they may trigger some useful reflection. (Separating collections is a useful step, but I feel it's rather nibbling at the edge of the complexity problem rather than facing it head-on.) Before diving in, I think it's worth reviewing my motivation for this... At the heart of my position is the question: "For provenance, what does success look like?" (a) Maybe it looks like this: rich and fully worked out specifications which are shown to address a range of described use-cases, complete with a consistent underlying theory that can be used to construct useful proofs around provenance information, reviewed and accepted for standards-track publication in the W3C. Software implementations that capture and exploit this provenance information in all its richness, and peer reviewed papers showing how provenance information, if provided according to the specification, can be used to underpin a range of trust issues around data on the web. (b) Or maybe like this: a compact easily-grasped structure that makes it easy for developers to attach available information to their published datasets with just a few extra lines of code. So easy to understand and apply that it becomes the norm to provide for every published dataset on the web, so that provenance information about data becomes as ubiquitous as data on the web, as ubiquitous as FOAF information about people. I think we are pretty much on course for (a), which is a perfectly reasonable position, but for me the massive potential we have for real impact is (b), which I think will be much harder to achieve on the basis of the current specifications. (My following comments are based in part on my experience as a developer working with other complex ontologies (notably FRBR and CIDOC-CRM): by isolating and clearly explaining the structural core, the whole ontology comes much easier to approach and utilize.) So what does it take to stand a chance of achieving (b)? My thoughts: 1. Identify the simple, structural core of provenance and describe that in a normative self-contained document for developers, with sufficient rigor and detail that developers who follow the spec can consistently generate basic provenance information structures, and with enough simplicity that developers whose primary interest is not provenance *can* follow the spec. This should be less than 20 terms overall (the current "starting point" consists of 13 terms; OPMV (http://open-biomed.sourceforge.net/opmv/ns.html) has 15). This structural core should also identify the intended extension points, and how to add the "epistemic" aspects of provenance. (That's a term I've adopted for this purpose- meaning the vocabulary terms that convey specific knowledge in conjunction with the underlying provenance structure; e.g. the specific role of an agent in an activity, the author of a document. Is there a more widely used term for this?) The document at http://code.google.com/p/opmv/wiki/OPMVGuide2 (esp. section 3) covers many of the relevant issues, including how to use common provenance-related vocabularies in concert with the structural core. (NOTE: I say "normative" here, because I think the approach of directing developers first to a non-normative primer is a kind of admission of failure, and still leaves a developer needing to master the normative documents if there are to be confident that their code is generating valid provenance information.) This could use information currently in the Primer (section 2, but not the stuff about specialization/alternative) and/or Ontology documents (section 3.1). 2. Introduce "epistemic" provenance concepts that deal with common specific requirements (e.g. collections, quotation, etc.), without formalization. I would expect this to be organized as reference material, consisting of several optional and free-standing sub-sections (or even separate documents). Examples of the kind of material might be http://code.google.com/p/opmv/wiki/GuideOfCommonModule, http://code.google.com/p/opmv/wiki/OPMVExtensionsDataCollections. This would cover the parts of the model corresponding to ""Expanded terms" and "Dictionary terms" in the ontology document, and maybe aspects of "Qualified terms" (see below). 3. Ontology - specific terms for representing provenance in RDF. The current provenance document seems to me to be pretty well organized from a high-level view. (My assumption is that any of the subsections of "expanded terms", "qualified terms" and "Dictionary terms" can be skipped by anyone who does not need access to the capabilities they provide.) I have not been involved in the discussions about qualified terms, and I am somewhat concerned by the level of complexity the introduce into the RDF model (22 additional classes and 26 properties). I can only hope that most applications that generate provenance information do not have to be concerned with these. (Looking at figure 2 in the ontology document, it seems to me that for many practical purposes the intent of these properties could be captured by properties applied directly to the Activity ... it seems there's a kind of "double reification" going on here with respect to the naive presentation of provenance via something like DC. In practice, if I were developing an application around this model using RDF that had to work with data at any reasonable scale, I'd probably end up introducing such properties in any case for performance reasons - cf. http://code.google.com/p/milarq/). 4. Describe how to generate provenance information in very simple terms for developers who are not and do not what to be specialists in provenance information (e.g. think of a developer creating a web site using Drupal - we want it to be really easy for them to design provenance information into their system). 5. Formal semantics, including the formal definition of PROV-N upon which it is based. This would include material from http://www.w3.org/2011/prov/wiki/FormalSemanticsWD3 6. Describe how to consume/interpret provenance information, in particular with reference to the formal semantics. This would be aimed at more specialist users (and creators) of provenance information, and would address the subtleties such as specialization, alternative, etc. Among other things, it would cover more formal aspects such as constraints, inferences, mappings from common patterns, mapping from subproperties of the basic structural properties, and other simplified ways of expressing information, to the qualified terms pattern, etc. Much of the material currently in the DM "constraints" document might end up here. ... In summary: 1. A simple structural core model/vocabulary for provenance (Normative) This should be the entry point, easy to read and absorb, for all users. 2. Common extension terms (Normative) This should be structured more as a reference work, so relevant parts are easily accessed and others can be ignored. 3. Ontology (i.e. expressing provenance in RDF) (Normative) Pretty much as the current document. 4. A simple guide for generating provenance information (Informative) This would contain primer material dealing with the core concepts. For most developers, the above would be all they need to know about. 5. Formal semantics (incorporating PROV-N) (Normative) A dense, formal description of PROV-N syntax and model theoretic formal semantics for a strict interpretation of the provenance model. 6. An advanced guide for using and interpreting provenance (Informative) For advanced developers of provenance applications and/or theory, exploring and explaining the more formal aspects of provenance and how they might affect applications that use provenance. ... So those are my thoughts. They involve a fairly radical reorganization of the material we have, but I don't think that they call for fundamental changes to the technical consensus, or for the creation significant new material. Existing material may need sub-editing, heavily in places. #g --
Received on Tuesday, 8 May 2012 12:21:13 UTC