[esip-semantictech] Linked Data Notifications (LDN) and Software Implementations

Sat Feb 2 00:02:24 EST 2019

Hi Tom,

Thanks for the heads up here. This looks great.

By the way, I’ve finished coding the Linked Data Notifications service which uses COR as the backend. The code can be seen at [0].
I provided a worked example at [1] demonstrating the REST API.

This essentially creates and uses the Inbox Graph [2] and creates new Linked Data Notifications as named graphs e.g. [3]. Incoming LDN’s are linked to from the Inbox Graph.
The Inbox Graph is not linked from individual LDN however so this may be something we want to address by simply adding a new edge back to the Inbox Graph.
Anyways, I will be working to have the service [4] up and running soon with the inbox being available at [5].

I really hope this service allow your Labs project to evolve and I am sure we can use the LDN service for loads of other things. I could see it even being used by the PO.DAAC to publish new Datasets in JSON-LD using geosci.schema.org.

I’ll update this thread and make an official announcement when the service goes live. We can also discuss the provision of clients which will make service interaction easier from your climate resilience applications.

Thanks, have a great weekend.
Lewis

[0] https://github.com/ESIPFed/pyldn
[1] https://github.com/ESIPFed/pyldn/wiki/LDN-Service-REST-Worked-Example
[2] http://cor.esipfed.org/ont/ldn/inbox
[3] http://cor.esipfed.org/ldn/inbox/f4a24af13e754884938c8f1ddae0468a
[4] http://cor.esipfed.org/ldn
[5] http://cor.esipfed.org/ldn/inbox/

Dr. Lewis John McGibbney Ph.D., B.Sc.
Data Scientist II
Computer Science for Data Intensive Applications Group (398M)
Instrument Software and Science Data Systems Section (398)
Jet Propulsion Laboratory
California Institute of Technology
4800 Oak Grove Drive
Pasadena, California 91109-8099
Mail Stop : 158-256C
Tel:  (+1) (818)-393-7402
Cell: (+1) (626)-487-3476
Fax:  (+1) (818)-393-1190
Email: lewis.j.mcgibbney at jpl.nasa.gov<mailto:lewis.j.mcgibbney at jpl.nasa.gov>
ORCID: orcid.org/0000-0003-2185-928X

           [signature_900883239]

 Dare Mighty Things

From: "Narock, Thomas" <tnarock at ndm.edu>
Date: Friday, February 1, 2019 at 1:18 PM
To: "Mcgibbney, Lewis J (398M)" <Lewis.J.McGibbney at jpl.nasa.gov>
Cc: "esip-semanticweb at lists.esipfed.org" <esip-semanticweb at lists.esipfed.org>
Subject: Re: [esip-semantictech] Linked Data Notifications (LDN) and Software Implementations

Hi Lewis,

I saw the COR notifications re: LDN. Thanks for pushing ahead with that. I just submitted a test version of our decision provenance ontology to COR - http://cor.esipfed.org/ont/~narock/decprov   It’s still very primitive, but will give us something to test with. Let me know when you are ready with the LDN setup and we’ll try submitting/querying some examples.

Tom

From: esip-semanticweb <esip-semanticweb-bounces at lists.esipfed.org> on behalf of ESIP Cluster <esip-semanticweb at lists.esipfed.org>
Reply-To: Tom Narock <tnarock at ndm.edu>
Date: Friday, January 18, 2019 at 6:35 PM
To: Lewis Mcgibbney <Lewis.J.McGibbney at jpl.nasa.gov>
Cc: ESIP Cluster <esip-semanticweb at lists.esipfed.org>
Subject: Re: [esip-semantictech] Linked Data Notifications (LDN) and Software Implementations

CAUTION: This email originated from outside NDMU. Do not click links or open attachments unless you recognize the sender and know the content is safe.

Hi Lewis,

I agree there are lots of interesting use cases for a Linked Data Notifications (LDN) architecture across ESIP projects. Thanks for keeping this discussion moving forward.

Our particular use case deals with provenance and its PROV encoding. We are interested in using PROV to encode climate resilience and climate mitigation decisions. There at least 3 efforts underway to semantically encode decision making [1][2][3]. [1] extends PROV to include decision related concepts. [2] is built off of formal decision theory research, but, as far as I can tell, it only currently exists in UML. USGS is interested in [2] and there seems to be efforts underway to encode it in OWL with possible links to PROV. In [1] Nick Car showed that [3] could be rewritten purely in PROV so we’ve been focusing on [1] as a lightweight encoding of decisions and following the progression of [2] for more detailed decision encoding. We’ll soon be submitting to COR our proposed extensions of [1] to make it more specific for climate decisions.

The connection to LDN is that once these provenance documents exist, we’d like to have a repository to submit them to and a means of notifying interested parties that a new decision exists. We think LDN is a straightforward means of providing these capabilities. Ultimately, we’d like to compare climate decision provenance and provide suggestions/recommendations for decision makers facing similar situations. Although, that seems outside the scope of LDN and would be a service built on top of it.

I would also mention that there’s another W3C spec (this one is a Note, not a Recommendation) called PROV-AQ, Provenance Answer and Query. Doug Fils and I looked at that one in the past for provenance submission and discovery. Having looked at both, I think LDN can provide the same functionality, is easier to implement, and works with JSON-LD, which a lot of developers are comfortable with. I think our use case would move forward faster with LDN, and the LDN spec aligns well with other ESIP use cases.

If you were to stand up an LDN instance I think we’d have a number of people willing to try it out.

Tom

[1] Car, N. (2017), Modelling causes for actions with the Decision and PROV Ontologies, 22nd International Congress on Modelling and Simulation, Hobart, Tasmania,  Australia, 3-8 December 2017, paper: https://www.mssanz.org.au/modsim2017/C2/car.pdf ontology: http://promsns.org/def/decprov

[2] Kornyshova, Elena, and Rébecca Deneckère. 2010. “Decision-Making Ontology for Information System Engineering.” In Conceptual Modeling – ER 2010, 104–17. Lecture Notes in Computer Science. Vancouver, BC, Canada: Springer. doi:10.1007/978-3-642-16373-9_8.

[3] Nowara, Piotr. 2012. Decision Ontology OWL ontology. Katowice, Poland. http://promsns.org/def/do.

From: Lewis Mcgibbney <Lewis.J.McGibbney at jpl.nasa.gov>
Date: Thursday, January 17, 2019 at 12:13 PM
To: Tom Narock <tnarock at ndm.edu>
Cc: ESIP Cluster <esip-semanticweb at lists.esipfed.org>
Subject: Linked Data Notifications (LDN) and Software Implementations

CAUTION: This email originated from outside NDMU. Do not click links or open attachments unless you recognize the sender and know the content is safe.

Hi Tom,

CC esip-semanticweb@,
As we discussed yesterday after your presentation [0], there are lots of interesting use cases for a Linked Data Notifications (LDN) architecture across ESIP projects. I wanted to open this up to the community and have it on the mailing list so we can reference it moving forward.

What are Linked Data Notifications?
LDN [1] support sharing and reuse of notifications across applications, regardless of how they were generated. This allows for more modular systems, which decouple data storage from the applications which display or otherwise make use of the data. The protocol is intended to allow senders, receivers and consumers of notifications, which are independently implemented and run on different technology stacks, to seamlessly work together, contributing to decentralisation of our interactions on the Web.

Why would we care… provide a practical example of how we would use LDN?
Let’s take the COR for example… there are numerous areas where LDN could be utilized and helpful. Here are a few…

1.      Say maintainers of the ENVO ontology are interested in changes to SWEET. Let’s also say they also have knowledge-based applications which utilize linked data to make decisions. This linked data relies upon accurate relationships between SWEET and ENVO. They want to be notified for any changes to SWEET such that their application behaves as expected. If a think LDN layer was layered over the COR then an incoming message regarding a change to SWEET would be persisted. The LDN service would then push a message to the ENVO client to notify of a change to SWEET and what that change was. The ENVO application could then react accordingly.

2.      Say other data providers who are using COR are interested in being notified when any other new resource is stored within COR. Well, again, a LDN could be sent to any specific subscriber and they could act accordingly.

3.      Say we run the AllegroGraph (the underlying RDF datastore powering COR) reasoning capability over data within COR and it results in linkages between resources. You would think the maintainers of the linked resources would want to know. Well with LDN, a push notification could be sent to those parties and action could be taken to address the data linkage.

4.      … Tom you had a few more use cases which were related to provenance for connecting climate adaption decisions to data.

How does this fit in with COR?
Well for one, the above use cases justify that a notifications system would be useful. One of the underlying requirements of LDN is that all payloads MUST be encoded as JSON-LD, meaning that these message can be persisted within COR itself as amongst other things it is a native RDF store.

What software implementation could provide an LDN service?
As you would expect, the W3C editors draft [1] does not mention or endorse a specific software implementation. Loads of implementations do however exist at [3] meaning that a LDN service would probably not be difficult to establish as a thin layer over COR and hosted on in the same computing environment as COR.

How does this fit in with the Linked Data-as-a-Service initiative?
It actually harmonizes very nicely with the LDaaS initiative by offering a managed and hosted LDN service for data providers which compliments everything else we’ve described in the LDaaS effort thus far.

Tom, can you please chime in here and expand upon your use cases. It would be great to hear what your thoughts are.
Thank you, interesting presentation yesterday.
Lewis

[0] https://sched.co/JORx
[1] https://linkedresearch.org/ldn/
[2] https://allegrograph.com/products/allegrograph/
[3] https://github.com/search?q=linked+data+notifications

Dr. Lewis John McGibbney Ph.D., B.Sc.
Data Scientist II
Computer Science for Data Intensive Applications Group (398M)
Instrument Software and Science Data Systems Section (398)
Jet Propulsion Laboratory
California Institute of Technology
4800 Oak Grove Drive
Pasadena, California 91109-8099
Mail Stop : 158-256C
Tel:  (+1) (818)-393-7402
Cell: (+1) (626)-487-3476
Fax:  (+1) (818)-393-1190
Email: lewis.j.mcgibbney at jpl.nasa.gov<mailto:lewis.j.mcgibbney at jpl.nasa.gov>
ORCID: orcid.org/0000-0003-2185-928X

           [signature_752128785]

 Dare Mighty Things
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.esipfed.org/pipermail/esip-semanticweb/attachments/20190202/7917b2d8/attachment-0001.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image001.png
Type: image/png
Size: 3430 bytes
Desc: image001.png
URL: <http://lists.esipfed.org/pipermail/esip-semanticweb/attachments/20190202/7917b2d8/attachment-0002.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image002.png
Type: image/png
Size: 3433 bytes
Desc: image002.png
URL: <http://lists.esipfed.org/pipermail/esip-semanticweb/attachments/20190202/7917b2d8/attachment-0003.png>