- From: Prof. Amandeep S. Sidhu <asidhu@zettascaledata.com>
- Date: Wed, 18 Sep 2019 21:23:57 +0000
- To: Amirouche Boubekki <amirouche.boubekki@gmail.com>
- CC: "paoladimaio10@googlemail.com" <paoladimaio10@googlemail.com>, W3C AIKR CG <public-aikr@w3.org>
Totally agree with the thread and thanks for summarising the SW thread too. Here are my 2 cents: There is gap between KR/KG because we haven’t really looked at efficient graph based KR and graph based query frameworks. Gartner putting a spin on KG as saviour for everything AI doesn’t help either - only feeds the marketing campaign of KG. I did some work on an OWL based Query Language specifically for Protein Ontology back in 2008/9 and i think lessons need to learnt from Association Rule Mining and a domain agnostic graph based query framework will help. > On 19 Sep 2019, at 06:34, Amirouche Boubekki <amirouche.boubekki@gmail.com> wrote: > >> Le mer. 28 août 2019 à 07:40, Paola Di Maio <paola.dimaio@gmail.com> a écrit : >> >> I do not normally like to call stuff I disagree with rubbish. I rarely do that. >> >> but To propose KG as the future of KR sounds like complete rubbish to me >> (shall try to justify this statement more scientifically) > > > It would be best but getting into the actual analysis of all the poor > work around it would take much time. I was teached to "be positive" > and "show the way" instead of being not-very-diplomatic. > >> I am shocked to see the cream of our research community being part of this >> disinformation campaign >> /aic.ai.wu.ac.at/~polleres/publications/bona-etal-DagstuhlReport18371.pdf > > > To this I heartedly agree. For once in my life I can say "I was there" > in the sense I was involved in graph database related work since 2011. > And since that time a massive marketing campaign was happening when > marketing is involved little or no Science is involved. > > Here is the thing that I skimmed, if anyone else wants to shim in the > conversation: > > - http://blog.liu.se/semanticweb/2018/09/15/dagstuhl-seminar-on-knowledge-graphs/ > - https://thinklinks.wordpress.com/2018/09/18/trip-report-dagstuhl-seminar-on-knowledge-graphs/ > - http://www.juansequeda.com/blog/2018/09/18/trip-report-on-knowledge-graph-dagstuhl-seminar/ > - https://aic.ai.wu.ac.at/~polleres/presentations/20190827DEXA_keynote.pdf :( > - https://aic.ai.wu.ac.at/~polleres/publications/bona-etal-DagstuhlReport18371.pdf > - http://www.mkbergman.com/2244/a-common-sense-view-of-knowledge-graphs/ > - First thread in > https://lists.w3.org/Archives/Public/semantic-web/2019Aug/thread.html > > To repeat myself from a previous post, KG is mostly a marketing > slogan. Still, it might have good ideas and (closed) implementation. > > To me the primary mistake they do in the above writings is that they > mix successful results of closed source software companies with the > blurry view they have of it and knowledge representation (KR). They > take the shortcut of saying that "KG is the way to go" because that is > the marketing term those successful companies choose to use for some > reasons. (KG is easier to spell and say that KR...) > > The idea of what KG / KR is or should be is still blurry. > > There is always a gap between what you want to express or represent > and the implementation because physical limitations. Take for instance > the relational-database-management-systems (RDBMS) which are at the > end of the day .csv files on steroids. They draw on paper or > blackboard using a graph. Are they graph? Yes! Everything is graph. > Are they Knowledge Graph: Yes! They represent knowledge, rows can > relate to each other so they are definitely graph in the common sense > not just single dot points in vast empty space. They are graphs, but > still we do not call them graphs or knowledge graph. > > Something I note in the SW thread is that at least LinkedIn, Ebay, > Apple, WikiData, Uber and maybe Google are relying on some software > implementation that relates to n-tuple store (or chunks store). To me > it means that n-tuple stores are not a mistakes in terms of > implementation and are not a mistake in terms of representation even > if less common sense compared to property graphs. At the end of the > day, it is very clear to me that Ordered Key-Value Store (OKVS) are > the future of database management. And on top of OKVS, n-tuple > (chunks) is a very good candidate compared to other approaches because > it is both sparse, relational and more powerful that "document store" > approach (like mongodb). Any way all those consideration are mostly > implementation details. > > Maybe what happens to KG vs. KR is what happened to Probabilistic > Models vs. Machine Learning (don't quote me on that :). > > NB: KG as in property-graph ala neo4j is not a bullet proof solution > to data problems modern applications are facing. >
Received on Wednesday, 18 September 2019 21:26:09 UTC