Presentation made on IoT Day 2016 about the importance of API-first, cloud services role in implementing ontologies for IoT. The use case is homely: providing proper humidity to my electric violin and guitar instruments while in their cases.

1. CLOUD SERVICES
SUPPORT FOR IOT
SEMANTIC
INTEROPERABILITY
IOT DAY 2016
IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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MARK UNDERWOOD
KRYPTON BROTHERS LLC

2. ABOUT @KNOWLENGR (ME)
• CEO Krypton Brothers (NYC area)
• Co-chair Summit on Ontologies for IoT
(2015)
• Co-chair Security and Privacy
subgroup of the NIST Big Data Public
Working Group
• Book chapter on Complex Event
Processing for IoT Security (in press)
• ACM, IEEE, AAAI, ISACA, SHRM etc,
etc.
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3. MY IOT USE “CASES”
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4. USE CASE:
ELECTRIC VIOLIN
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5. YAMAHA EV-5 CASE
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6. SENSOR, DEVICE TYPES
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7. REQUIREMENT: SENSOR,
DEVICE UPGRADE
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8. “TECHNICAL”
REQUIREMENTS
• Remote monitoring
• Interface with existing applications
• Recognize case placement
• Issue alerts, not just continuous data stream
• Support multiple models of humidistats
• Identify location (geospatial)
• Identify which instrument ($$$$ vs. $)
• Recognize sensor failure
• Full “ecosystem” (humidistat | humidifier | case
environment | location)
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9. “BUSINESS”
REQUIREMENTS
• Limited budget
• Limited expertise for sensor technology
• Access through smartphone
• Access through web page
• Prevent “catastrophic” drying
• Address “case open” condition
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10. FRONT-OF-NOSE
CONSIDERATIONS?
• What solutions are already out there?
• What are the sensor manufacturers providing?
• What protocols are “winning”?
• What giant, widely used apps or platforms should it
interface with (Facebook, Google, Microsoft, Verizon)?
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11. BIG PICTURE
CONSIDERATIONS
• Use case contains multiple paradigmatic aspects
• Hidden analytics needs (practical sweet spot for case
climate control)
• Numerous rabbit holes for Not-Invented-Here development
• Confluence of idiosyncratic requirements and “universal”
IoT requirements
• Software development life cycle (SDLC) realities
• Error tolerance
• Maintenance will exceed development costs
• Potential big distraction from practicing for performance
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12. THE GO-TO, DEFAULT
AGILE DEVELOPER
SOLUTION IN 2016?
CLOUD SERVICES
DRIVEN BY
API-FIRST DESIGN
►Cloud often morphs to hybrid (connectivity, resilience, cost
considerations apply), but folks embrace cloud-first mentality
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13. CHECKERED SEMANTIC
INTEROPERABILITY
“SOLUTIONS” HISTORY
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Credit: Leo Obrst, PhD at Mitre

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This slide credit: Leo Obrst (Mitre)
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15. ONTOLOGY MOTIVATORS
• Abstract models for devices, processes, events
• “Upper ontology”
• Describe code fragments (e.g., classes) using taxonomies
& vocabularies recognized by other developers
• Leverage stereotypical design patterns for UI
• Recognize blurring with big data issue
• Access “model-oriented” communities of interest
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16. TRADEOFF DANCE
• Implement an elegant solution
• Avoid slippery floor spots
• endless refinement
• unresolvable representation alternatives
• Devil is in the details
• Cautionary tale:
Example from Financial Industry Business Ontology
(FIBO)
• EHR Blockbuster film: EPIC vs. the Ontologists
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17. QUESTIONS
• What is the shape of existing cloud service design
patterns?
• Are ontologies part of these patterns?
• If so, what does it look like?
• Which enterprise influencers are at work?
• Which tools are being used? (Artifacts?)
• Who are the people to watch?
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18. CLOUD SERVICES
ABSTRACT
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Two important consequences of the “cloudification” of computing are DevOps and
an API-first (espoused by Intel’s Brian Krzanich) design philosophy. While SOA and
“composable services” introduced many of the same concepts in earlier generations
(indeed, both DevOps and API-first steal from well-burnished concepts), the level of
adoption across software and data providers is unprecedented. Computing
environments for large scale projects can be stood up in minutes, tested and
disposed of the following day. Products like Zapier and IFTTT allow for
orchestration of cloud services across providers. The Zapier App Directory offers
around 100 integrations. Interop exists across platforms (as in hybrid cloud
storage), applications (e.g., between QuickBooks and a telephony app like
DialMyCalls), and also what some are calling “cognitive services.” Cloudify
suggests using TOSCA (a cloud orchestration standard) to connect resources like
OpenStack or VMware using open source tools.)
Github repositories can store ontologies, but can this be scaled up to build
applications, sharing ontologies within or across domains? Will developers tempted
to use ontologies be able to gain the same productivity benefits they experience
elsewhere with cloud services? We ask a few vendors.

19. API-FIRST DESIGN
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API-first design is a result of ubiquitous cloud services
and DevOps, but its impact is not limited to that: IoT
development is inspired by the same design patterns.
Ontologies could / should be similarly ubiquitous to
deploy. Are they?

20. WHY API-FIRST?
Browse cloud service integrations at Zapier,
ProgrammableWeb and IFTTT
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21. IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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22. PROGRAMMABLE WEB
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23. CLOUD SOLUTIONS:
COMMERCIAL TRACTION
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24. IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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25. IBM WATSON:
“ONTOLOGY ANALYSIS”
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26. IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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27. SAS: ONTOLOGY FOR
ANALYTICS & BI
http://www.sas.com/en_us/software/analytics/ontology-management.html
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28. SAS: ONTOLOGY
MANAGEMENT STUDIO
Includes class editing, XML import, RDF formats
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29. ORCHESTRATION AS KEY
• Emerging as central issue
in NIST Big Data Working
Group Security and
Privacy
(bigdatastandards.com)
• Reality: multiple services,
vendors, standards
• Role of people must be
surfaced design patterns
• Re-emergence of
workflow
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30. OASIS TOSCA
TOSCA: Topology and Orchestration Specification for Cloud
Applications
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31. SDN MEETS ONTOLOGY?
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32. SAP RESEARCH
Via: Florian Probst (c. 2012) “SAP Research: An
Industry Perspective on Semantic Technologies”
• Probst walks through several use cases and
prototypes, including EMS, oil & gas
• Lessons learned:
• Establish role for “ontology engineer”
• Improved browsers for ontology editors, help, &
visualization metaphors
• “Ontologies are still hard to use for software
engineers while the benefit is not directly obvious”
• There are performance issues
• Need new mechanisms for semantic annotations
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33. PROGRESS WITHIN THE DOMINANT DESIGN
PATTERN? HTTP://ISERVE.KMI.OPEN.AC.UK/
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34. ISERVE (CONT’D)
Open Source: https://github.com/kmi/iserve
•Web Application -iServe Browser
•Read&Write RESTful API
•Linked Data principles
•SPARQL endpoint
•Content negotiation (RDF, HTML)
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35. IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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36. ISERVE ON SWAGGER + GITHUB
“By this all people will know you are my discipline.”
(refactoring of John 13:25)
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37. IoT Day 2016 - Mark Underwood @Knowlengr Krypton Brothers - Creative Commons Attribution Share-Alike
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“Swagger is a simple yet powerful representation of your RESTful API.
With the largest ecosystem of API tooling on the planet, thousands of developers are supporting Swagger
in almost every modern programming language and deployment environment.
With a Swagger-enabled API, you get interactive documentation, client SDK generation and discoverability.
We created Swagger to help fulfill the promise of APIs. Swagger helps companies like Apigee, Getty Images,
Intuit, LivingSocial, McKesson, Microsoft, Morningstar, and PayPal build the best possible services with
RESTful APIs.

38. PROGRESS?
CLOUD SERVICES FOR ONTOLOGIES
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39. WHERE ARE ONTOLOGIES?
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40. CURRENT STATUS OF ONTOLOGY
CLOUD SERVICE OFFERINGS
• Too few initiatives (search Github, Swagger)
• Some of the few are industry giants
• Adoption is being pushed from top (SAS), bottom (Nakina
Systems), and middle (SAP)
• There are clear use cases (e.g., CRM  marketing
automation)
• Competing software development life cycle models still
prevail
• Among semantically rich alternative development models,
even they have light traction (model-driven development,
domain-specific development)
• Roll-your-own (without ontologies) must get harder.
• iServe, ProgrammableWeb potential influencers
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41. PROJECT STALL
• Which upper ontologies do I
need?
• Evolving home monitoring
ecosystem (Verizon?)
• Lack of APIs
• Low tech commercial
landscape
• Use case not compelling
enough
• Development challenge
nontrivial
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42. MEANS TO AN END
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Standards, APIs, even programming languages have limited lifetimes.
(MIDI is a mind-numbing exception.)
Building apps that endure is a nontrivial challenge.
Think Bach, not Google.

43. SEMANTIC INTEROP
VIA CLOUD SERVICES
MARK UNDERWOOD
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KRYPTON BROTHERS LLC | KRYPTONBROTHERS.COM
@KNOWLENGR
MARK.UNDERWOOD@KRYPTONBROTHERS.COM
SEE ALSO: ONTOLOGYSUMMIT.ORG