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Internet Architecture Board (IAB)                             J. Jimenez
Request for Comments: 8477                                 H. Tschofenig
Category: Informational                                        D. Thaler
ISSN: 2070-1721                                             October 2018

                Report from the Internet of Things (IoT)
            Semantic Interoperability (IOTSI) Workshop 2016


   This document provides a summary of the "Workshop on Internet of
   Things (IoT) Semantic Interoperability (IOTSI)", which took place in
   Santa Clara, California March 17-18, 2016.  The main goal of the
   workshop was to foster a discussion on the different approaches used
   by companies and Standards Developing Organizations (SDOs) to
   accomplish interoperability at the application layer.  This report
   summarizes the discussions and lists recommendations to the standards
   community.  The views and positions in this report are those of the
   workshop participants and do not necessarily reflect those of the
   authors or the Internet Architecture Board (IAB), which organized the
   workshop.  Note that this document is a report on the proceedings of
   the workshop.  The views and positions documented in this report are
   those of the workshop participants and do not necessarily reflect IAB
   views and positions.

Status of This Memo

   This document is not an Internet Standards Track specification; it is
   published for informational purposes.

   This document is a product of the Internet Architecture Board (IAB)
   and represents information that the IAB has deemed valuable to
   provide for permanent record.  It represents the consensus of the
   Internet Architecture Board (IAB).  Documents approved for
   publication by the IAB are not candidates for any level of Internet
   Standard; see Section 2 of RFC 7841.

   Information about the current status of this document, any errata,
   and how to provide feedback on it may be obtained at

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Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  What Problems to Solve  . . . . . . . . . . . . . . . . . . .   5
   4.  Translation . . . . . . . . . . . . . . . . . . . . . . . . .   7
   5.  Dealing with Change . . . . . . . . . . . . . . . . . . . . .   9
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  10
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  10
   8.  Collaboration . . . . . . . . . . . . . . . . . . . . . . . .  11
   9.  Informative References  . . . . . . . . . . . . . . . . . . .  12
   Appendix A.  Program Committee  . . . . . . . . . . . . . . . . .  14
   Appendix B.  Accepted Position Papers . . . . . . . . . . . . . .  14
   Appendix C.  List of Participants . . . . . . . . . . . . . . . .  17
   IAB Members at the Time of Approval . . . . . . . . . . . . . . .  18
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .  18
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  18

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1.  Introduction

   The Internet Architecture Board (IAB) holds occasional workshops
   designed to consider long-term issues and strategies for the
   Internet, and to suggest future directions for the Internet
   architecture.  The investigated topics often require coordinated
   efforts from many organizations and industry bodies to improve an
   identified problem.  One of the targets of the workshops is to
   establish communication between relevant organizations, especially
   when the topics are out of the scope of the Internet Engineering Task
   Force (IETF).  This long-term planning function of the IAB is
   complementary to the ongoing engineering efforts performed by working
   groups of the IETF.

   With the expansion of the Internet of Things (IoT), interoperability
   becomes more and more important.  Standards Developing Organizations
   (SDOs) have done a tremendous amount of work to standardize new
   protocols and profile existing protocols.

   At the application layer and at the level of solution frameworks,
   interoperability is not yet mature.  Particularly, the work on data
   formats (in the form of data models and information models) has not
   seen the same level of consistency throughout SDOs.

   One common problem is the lack of an encoding-independent
   standardization of the information, the so-called information model.
   Another problem is the strong relationship between data formats and
   the underlying communication architecture, such as a design in Remote
   Procedure Call (RPC) style or a RESTful design (where REST refers to
   Representational State Transfer).  Furthermore, groups develop
   solutions that are very similar on the surface but differ slightly in
   their standardized outcome, leading to interoperability problems.
   Finally, some groups favor different encodings for use with various
   application-layer protocols.

   Thus, the IAB decided to organize a workshop to reach out to relevant
   stakeholders to explore the state of the art and identify commonality
   and gaps [IOTSIAG] [IOTSIWS].  In particular, the IAB was interested
   to learn about the following aspects:

   o  What is the state of the art in data and information models?  What
      should an information model look like?

   o  What is the role of formal languages, such as schema languages, in
      describing information and data models?

   o  What is the role of metadata, which is attached to data to make it

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   o  How can we achieve interoperability when different organizations,
      companies, and individuals develop extensions?

   o  What is the experience with interworking various data models
      developed from different groups, or with data models that evolved
      over time?

   o  What functionality should online repositories for sharing schemas

   o  How can existing data models be mapped against each other to offer

   o  Is there room for harmonization, or are the use cases of different
      groups and organizations so unique that there is no possibility
      for cooperation?

   o  How can organizations better work together to increase awareness
      and information sharing?

2.  Terminology

   The first roadblock to interoperability at the level of data models
   is the lack of a common vocabulary to start the discussion.
   [RFC3444] provides a starting point by separating conceptual models
   for designers, or "information models", from concrete detailed
   definitions for implementers, or "data models".  There are concepts
   that are undefined in that RFC and elsewhere, such as the interaction
   with the resources of an endpoint, or "interaction model".
   Therefore, the three "main" common models that were identified were:

   Information Model
      An information model defines an environment at the highest level
      of abstraction and expresses the desired functionality.
      Information models can be defined informally (e.g., in prose) or
      more formally (e.g., Unified Modeling Language (UML), Entity-
      Relationship Diagrams, etc.).  Implementation details are hidden.

   Data Model
      A data model defines concrete data representations at a lower
      level of abstraction, including implementation- and protocol-
      specific details.  Some examples are SNMP Management Information
      Base (MIB) modules, World Wide Web Consortium (W3C) Thing
      Description (TD) Things, YANG modules, Lightweight Machine-to-
      Machine (LwM2M) Schemas, Open Connectivity Foundation (OCF)
      Schemas, and so on.

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   Interaction Model
      An interaction model defines how data is accessed and retrieved
      from the endpoints, being, therefore, tied to the specific
      communication pattern that the system has (e.g., REST methods,
      Publish/Subscribe operations, or RPC calls).

   Another identified terminology issue is the semantic meaning overload
   that some terms have.  The meaning can vary depending on the context
   in which the term is used.  Some examples of such terms are as
   follows: semantics, models, encoding, serialization format, media
   types, and encoding types.  Due to time constraints, no concrete
   terminology was agreed upon, but work will continue within each
   organization to create various terminology documents.  The
   participants agreed to set up a GitHub repository [IOTSIGIT] for
   sharing information.

3.  What Problems to Solve

   The participants agreed that there is not simply a single problem to
   be solved but rather a range of problems.  During the workshop, the
   following problems were discussed:

   o  Formal Languages for Documentation Purposes

   To simplify review and publication, SDOs need formal descriptions of
   their data and interaction models.  Several of them use a tabular
   representation found in the specification itself but use a formal
   language as an alternative way of describing objects and resources
   for formal purposes.  Some examples of formal language use are as

   The Open Mobile Alliance (OMA), now OMA SpecWorks, used an XML Schema
   [LWM2M-Schema] to describe their object and resource definitions.
   The XML files of standardized objects are available for download at

   The Bluetooth Special Interest Group (SIG) defined Generic Attribute
   Profile (GATT) services and characteristics for use with Bluetooth
   Smart/Low Energy.  The services and characteristics are shown in a
   tabular form on the Bluetooth SIG website [SIG] and are defined as
   XML instance documents.

   The Open Connectivity Foundation (OCF) uses JSON Schemas to formally
   define data models and RESTful API Modeling Language (RAML) to define
   interaction models.  The standard files are available online at

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   The AllSeen Alliance uses AllJoyn Introspection XML to define data
   and interaction models in the same formal language, tailored for
   RPC-style interaction.  The standard files are available online on
   the AllSeen Alliance website, but both standard and vendor-defined
   model files can be obtained by directly querying a device for them at

   The World Wide Web Consortium (W3C) uses the Resource Description
   Framework (RDF) to define data and interaction models using a format
   tailored for the web.

   The Internet Engineering Task Force (IETF) uses YANG to define data
   and interaction models.  Other SDOs may use various other formats.

   o  Formal Languages for Code Generation

   Code-generation tools that use formal data and information modeling
   languages are needed by developers.  For example, the AllSeen Visual
   Studio Plugin [AllSeen-Plugin] offers a wizard to generate code based
   on the formal description of the data model.  Another example of a
   data modeling language that can be used for code generation is YANG.
   A popular tool to help with code generation of YANG modules is pyang
   [PYANG].  An example of a tool that can generate code for multiple
   ecosystems is OpenDOF [OpenDOF].  Use cases discussed for code
   generation included easing development of server-side device
   functionality, clients, and compliance tests.

   o  Debugging Support

   Debugging tools are needed that implement generic object browsers,
   which use standard data models and/or retrieve formal language
   descriptions from the devices themselves.  As one example, the nRF
   Bluetooth Smart sniffer from Nordic Semiconductor [nRF-Sniffer] can
   be used to display services and characteristics defined by the
   Bluetooth SIG.  As another example, AllJoyn Explorer
   [AllJoynExplorer] can be used to browse and interact with any
   resource exposed by an AllJoyn device, including both standard and
   vendor-defined data models, by retrieving the formal descriptions
   from the device at runtime.

   o  Translation

   The working assumption is that devices need to have a common data
   model with a priori knowledge of data types and actions.  However,
   that would imply that each consortium/organization will try to define
   their own data model.  That would cause a major interoperability

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   problem, possibly a completely intractable one given the number of
   variations, extensions, compositions, or versioning changes that will
   happen for each data model.

   Another potential approach is to have a minimal amount of information
   on the device to allow for a runtime binding to a specific model, the
   objective being to require as little prior knowledge as possible.

   Moreover, gateways, bridges and other similar devices need to
   dynamically translate (or map) one data model to another one.
   Complexity will increase as there are also multiple protocols and
   schemas that make interoperability harder to achieve.

   o  Runtime Discovery

   Runtime discovery allows IoT devices to exchange metadata about the
   data, potentially along with the data exchanged itself.  In some
   cases, the metadata not only describes data but also the interaction
   model as well.  An example of such an approach has been shown with
   Hypermedia as the Engine of Application State (HATEOAS) [HATEOAS].
   Another example is that all AllJoyn devices support such runtime
   discovery using a protocol mechanism called "introspection", where
   the metadata is queried from the device itself [AllSeen].

   There are various models, whether deployed or possible, for such
   discovery.  The metadata might be extracted from a specification,
   looked up on a cloud repository (e.g., oneIoTa for OCF models),
   looked up via a vendor's site, or obtained from the device itself
   (such as in the AllJoyn case).  The relevant metadata might be
   obtained from the same place or different pieces might be obtained
   from different places, such as separately obtaining (a) syntax
   information, (b) end-user descriptions in a desired language, and (c)
   developer-specific comments for implementers.

4.  Translation

   In an ideal world where organizations and companies cooperate and
   agree on a single data model standard, there is no need for gateways
   that translate from one data model to another one.  However, this is
   far from reality today, and there are many proprietary data models in
   addition to the already standardized ones.  As a consequence,
   gateways are needed to translate between data models.  This leads to
   (n^2)-n combinations, in the worst case.

   There are analogies with gateways back in the 1980s that were used to
   translate between network layer protocols.  Eventually, IP took over,
   providing the necessary end-to-end interoperability at the network
   layer.  Unfortunately, the introduction of gateways leads to the loss

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   of expressiveness due to the translation between data models.  The
   functionality of IP was so valuable in the market that advanced
   features of other networking protocols became less attractive and
   were not used anymore.

   Participants discussed an alternative that they called a "red star",
   shown in Figure 1, where data models are translated to a common data
   model shown in the middle.  This reduces the number of translations
   that are needed down to 2n (in the best case).  The problem, of
   course, is that everyone wants their own data model to be the red
   star in the center.

      +-----+                                        +-----+
      |     |                                        |     |
      |     |  --                                 -- |     |
      |     |    --                             --   |     |
      +-----+      --                         --     +-----+
                     --                    ---
                       --                --
                         --            --
                           --        --
        ---                  -- A  --                  ---
       /   \                ___/ \___                 /   \
      |     | ---------------',   .'---------------  |     |
       \   /                 /. ^ .\                  \   /
        ---                 /'     '\                  ---
                           --        --
                         --            --
                       --                --
                     --                    --
                   --                        --
          /\     --                            --     /\
         /  \  --                                --  /  \
        /    \                                      /    \
       /      \                                    /      \
      /--------\                                  /--------\

            Figure 1: The "Red Star" in Data/Information Models

   While the workshop itself was not a suitable forum to discuss the
   design of such translation in detail, several questions were raised:

   o  Do we need a "red star" that does everything, or could we design
      something that offers a more restricted functionality?

   o  How do we handle loss of data and functionality?

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   o  Should data be translated between data models, or should data
      models themselves be translated?

   o  How can interaction models be translated?  They need to be dealt
      with in addition to the data models.

   o  Many (if not all) data and interaction models have some bizarre
      functionality that cannot be translated easily.  How can those be

   o  What limitations are we going to accept in these translations?

   The participants also addressed the question of when translation
   should be done.  Two use cases were discussed:

   (a)  Design time: A translation between data model descriptions, such
        as translating a YANG module to a RAML/JSON model, can be
        performed once, during design time.  A single information model
        might be mapped to a number of different data models.

   (b)  Run time: Runtime translation of values in two standard data
        models can only be algorithmically done when the data model on
        one side is algorithmically derived from the data model on the
        other side.  This was called a "derived model".  It was
        discussed that the availability of runtime discovery can aid in
        semantic translation, such as when a vendor-specific data model
        on one side of a protocol bridge is resolved and the translator
        can algorithmically derive the semantically equivalent vendor-
        specific data model on the other side.  This situation is
        discussed in [BridgeTaxonomy].

   The participants agreed that algorithm translation will generally
   require custom code whenever one is translating to anything other
   than a derived model.

   Participants concluded that it is typically easier to translate data
   between systems that follow the same communication architecture.

5.  Dealing with Change

   A large part of the workshop was dedicated to the evolution of
   devices and server-side applications.  Interactions between devices
   and services and how their relationship evolves over time is
   complicated by their respective interaction models.

   The workshop participants discussed various approaches to deal with
   change.  In the most basic case, a developer might use a description
   of an API and implement the protocol steps.  Sometimes, the data or

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   information model can be used to generate code stubs.  Subsequent
   changes to an API require changes on the clients to upgrade to the
   new version, which requires some development of new code to satisfy
   the needs of the new API.

   These interactions could be made machine understandable in the first
   place, enabling for changes to happen at runtime.  In that scenario,
   a machine client could discover the possible interactions with a
   service, adapting to changes as they occur without specific code
   being developed to adapt to them.

   The challenge seems to be to code the human-readable specification
   into a machine-readable format.  Machine-readable languages require a
   shared vocabulary to give meaning to the tags.

   These types of interactions are often based on the REST architectural
   style.  Its principle is that a device or endpoint only needs a
   single entry point, with a host providing descriptions of the API
   in-band by means of web links and forms.

   By defining IoT-specific relation types, it is possible to drive
   interactions through links instead of hard-coding URIs into a RESTful
   client, thus making the system flexible enough for later changes.
   The definition of the basic hypermedia formats for IoT is still a
   work in progress.  However, some of the existing mechanisms can be
   reused, such as resource discovery, forms, or links.

6.  IANA Considerations

   This document has no IANA actions.

7.  Security Considerations

   There were two types of security considerations discussed: use of
   formal data models for security configuration and security of data
   and data models in general.

   It was observed that the security assumptions and configuration, or
   "security model", varies by ecosystem today, making the job of a
   translator difficult.  For example, there are different types of
   security principals (e.g., user vs. device vs. application), the use
   of Access Control Lists (ACLs) versus capabilities, and what types of
   policies can be expressed, all vary by ecosystem.  As a result, the
   security model architecture generally dictates where translation can
   be done.

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   One approach discussed was whether two endpoints might be able to use
   some overlay security model across a translator between two
   ecosystems, which only works if the two endpoints agree on a common
   data model for their communication.  Another approach discussed was
   simply having a translator act as a trusted intermediary, which
   enables the translator to translate between different data models.

   One suggestion discussed was either adding metadata into the formal
   data model language or having it accompany the data values over the
   wire, tagging the data with privacy levels.  However, sometimes even
   the privacy level of information might itself be sensitive.  Still,
   it was observed that being able to dynamically learn security
   requirements might help provide better UIs and translators.

8.  Collaboration

   The participants discussed how best to share information among their
   various organizations.  One discussion was around having joint
   meetings.  One current challenge reported was that organizations were
   not aware of when and where each other's meetings were scheduled, and
   sharing such information could help organizations better collocate
   meetings.  To facilitate this exchange, the participants agreed to
   add links to their respective meeting schedules from a common page in
   the IOTSI repository [IOTSIGIT].

   Another challenge reported was that organizations did not know how to
   find each other's published data models, and sharing such information
   could better facilitate reuse of the same information model.  To
   facilitate this exchange, the participants discussed whether a common
   repository might be used by multiple organizations.  The OCF's
   oneIoTa repository was discussed as one possibility, but it was
   reported that its terms of use at the time of the workshop prevented
   this.  The OCF agreed to take this back and look at updating the
   terms of use to allow other organizations to use it, as the
   restriction was not the intent.  <schema.org> was discussed as
   another possibility.  In the meantime, the participants agreed to add
   links to their respective repositories from a common page in the
   IOTSI repository [IOTSIGIT].

   It was also agreed that the iotsi@iab.org mailing list would remain
   open and available for sharing information between all relevant

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9.  Informative References

              Microsoft, "AllJoyn".

   [AllSeen]  Thaler, D., "Summary of AllSeen Alliance Work Relevant to
              Semantic Interoperability", 2016, <https://www.iab.org/

              Rockwell, B., "Using the AllJoyn Studio Extension", August

              Thaler, D., "IoT Bridge Taxonomy", IAB IOTSI
              Workshop 2016, <https://www.iab.org/wp-content/

   [HATEOAS]  Kovatsch, M., Hassan, Y., and K. Hartke, "Semantic
              Interoperability Requires Self-describing Interaction
              Models: HATEOAS for the Internet of Things", Proceedings
              of the IAB IoT Semantic Interoperability Workshop 2016,

   [IOTSIAG]  IAB, "IoT Semantic Interoperability Workshop Agenda",

              "Starting place for the IoT Semantic Interoperability
              Workshop (IOTSI) Information Resource", commit ff21f74,
              July 2018, <https://github.com/iotsi/iotsi>.

   [IOTSIWS]  IAB, "IoT Semantic Interoperability Workshop 2016", 2016,

              OMA, "LWM2M XML Schema - LWM2M Editor Schema", July 2018.

              Nordic Semiconductor, "nRF Sniffer: Smart/Bluetooth low
              energy packet sniffer".

   [OMNA]     OMA, "OMA LightweightM2M (LwM2M) Object and Resource

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   [OpenDOF]  OpenDOF, "The OpenDOF Project", <https://opendof.org>.

   [PYANG]    "An extensible YANG validator and converter in python",
              commit 15c807f, September 2018,

   [RFC3444]  Pras, A. and J. Schoenwaelder, "On the Difference between
              Information Models and Data Models", RFC 3444,
              DOI 10.17487/RFC3444, January 2003,

   [SIG]      Bluetooth SIG, "GATT Specifications",

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Appendix A.  Program Committee

   This workshop was organized by the following individuals: Jari Arkko,
   Ralph Droms, Jaime Jimenez, Michael Koster, Dave Thaler, and Hannes

Appendix B.  Accepted Position Papers

   o  Jari Arkko, "Gadgets and Protocols Come and Go, Data Is Forever"

   o  Carsten Bormann, "Noise in Specifications hurts"

   o  Benoit Claise, "YANG as the Data Modelling Language in the IoT

   o  Robert Cragie, "The ZigBee Cluster Library over IP"

   o  Dee Denteneer, Michael Verschoor, and Teresa Zotti, "Fairhair:
      interoperable IoT services for major Building Automation and
      Lighting Control ecosystems"

   o  Universal Devices, "Object Oriented Approach to IoT

   o  Bryant Eastham, "Interoperability and the OpenDOF Project"

   o  Stephen Farrell and Alissa Cooper, "It's Often True: Security's
      Ignored (IOTSI) - and Privacy too"

   o  Christian Groves, Lui Yan, and Yang Weiwei, "Overview of IoT
      semantics landscape"

   o  Ted Hardie, "Loci of Interoperability for the Internet of Things"

   o  Russ Housley, "Vehicle-to-Vehicle and Vehicle-to-Infrastructure

   o  Jaime Jimenez, Michael Koster, and Hannes Tschofenig, "IPSO Smart

   o  David Jones, "IOTDB - interoperability Through Semantic

   o  Sebastian Kaebisch and Darko Anicic, "Thing Description as Enabler
      of Semantic Interoperability on the Web of Things"

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   o  Achilleas Kemos, "Alliance for Internet of Things Innovation
      Semantic Interoperability Release 2.0, AIOTI WG03 - IoT

   o  Ari Keraenen and Cullen Jennings, "SenML: simple building block
      for IoT semantic interoperability"

   o  Dongmyoung Kim, Yunchul Choi, and Yonggeun Hong, "Research on
      Unified Data Model and Framework to Support Interoperability
      between IoT Applications"

   o  Michael Koster, "Model-Based Hypertext Language"

   o  Matthias Kovatsch, Yassin N.  Hassan, and Klaus Hartke, "Semantic
      Interoperability Requires Self-describing Interaction Models"

   o  Kai Kreuzer, "A Pragmatic Approach to Interoperability in the
      Internet of Things"

   o  Barry Leiba, "Position Paper"

   o  Marcello Lioy, "AllJoyn"

   o  Kerry Lynn and Laird Dornin, "Modeling RESTful APIs with JSON

   o  Erik Nordmark, "Thoughts on IoT Semantic Interoperability: Scope
      of security issues"

   o  Open Geospatial Consortium, "OGC SensorThings API: Communicating
      "Where" in the Web of Things"

   o  Jean Paoli and Taqi Jaffri, "IoT Information Model
      Interoperability: An Open, Crowd-Sourced Approach in Three
      Parallel Parti"

   o  Joaquin Prado, "OMA Lightweight M2M Resource Model"

   o  Dave Raggett and Soumya Kanti Datta, "Input paper for IAB Semantic
      Interoperability Workshop"

   o  Pete Rai and Stephen Tallamy, "Semantic Overlays Over Immutable
      Data to Facilitate Time and Context Specific Interoperability"

   o  Jasper Roes and Laura Daniele, "Towards semantic interoperability
      in the IoT using the Smart Appliances REFerence ontology (SAREF)
      and its extensions"

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   o  Max Senges, "Submission for IAB IoT Sematic Interoperability

   o  Bill Silverajan, Mert Ocak and Jaime Jimenez, "Implementation
      Experiences of Semantic Interoperability for RESTful Gateway

   o  Ned Smith, Jeff Sedayao, and Claire Vishik, "Key Semantic
      Interoperability Gaps in the Internet-of-Things Meta-Models"

   o  Robert Sparks and Ben Campbell, "Considerations for certain IoT-
      based services"

   o  J.  Clarke Stevens, "Open Connectivity Foundation oneIoTa Tool"

   o  J.  Clarke Stevens and Piper Merriam, "Derived Models for
      Interoperability Between IoT Ecosystems"

   o  Ravi Subramaniam, "Semantic Interoperability in Open Connectivity
      Foundation (OCF) - formerly Open Interconnect Consortium (OIC)"

   o  Andrew Sullivan, "Position paper for IOTSI workshop"

   o  Darshak Thakore, "IoT Security in the context of Semantic

   o  Dave Thaler, "IoT Bridge Taxonomy"

   o  Dave Thaler, "Summary of AllSeen Alliance Work Relevant to
      Semantic Interoperability"

   o  Mark Underwood, Michael Gruninger, Leo Obrst, Ken Baclawski, Mike
      Bennett, Gary Berg-Cross, Torsten Hahmann, and Ram Sriram,
      "Internet of Things: Toward Smart Networked Systems and Societies"

   o  Peter van der Stok and Andy Bierman, "YANG-Based Constrained
      Management Interface (CoMI)"

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RFC 8477                   IOTSI Workshop 2016              October 2018

Appendix C.  List of Participants

      Andy Bierman, YumaWorks
      Carsten Bormann, Uni Bremen/TZI
      Ben Campbell, Oracle
      Benoit Claise, Cisco
      Alissa Cooper, Cisco
      Robert Cragie, ARM Limited
      Laura Daniele, TNO
      Bryant Eastham, OpenDOF
      Christian Groves, Huawei
      Ted Hardie, Google
      Yonggeun Hong, ETRI
      Russ Housley, Vigil Security
      David Janes, IOTDB
      Jaime Jimenez, Ericsson
      Shailendra Karody, Catalina Labs
      Ari Keraenen, Ericsson
      Michael Koster, SmartThings
      Matthias Kovatsch, Siemens
      Kai Kreuzer, Deutsche Telekom
      Barry Leiba, Huawei
      Steve Liang, Uni Calgary
      Marcello Lioy, Qualcomm
      Kerry Lynn, Verizon
      Mayan Mathen, Catalina Labs
      Erik Nordmark, Arista
      Jean Paoli, Microsoft
      Joaquin Prado, OMA
      Dave Raggett, W3C
      Max Senges, Google
      Ned Smith, Intel
      Robert Sparks, Oracle
      Ram Sriram, NIST
      Clarke Stevens
      Ram Subramanian, Intel
      Andrew Sullivan, DIN
      Darshak Thakore, CableLabs
      Dave Thaler, Microsoft
      Hannes Tschofenig, ARM Limited
      Michael Verschoor, Philips Lighting

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RFC 8477                   IOTSI Workshop 2016              October 2018

IAB Members at the Time of Approval

      Jari Arkko
      Alissa Cooper
      Ted Hardie
      Christian Huitema
      Gabriel Montenegro
      Erik Nordmark
      Mark Nottingham
      Melinda Shore
      Robert Sparks
      Jeff Tantsura
      Martin Thomson
      Brian Trammell
      Suzanne Woolf


   We would like to thank all paper authors and participants for their
   contributions and Ericsson for hosting the workshop.

Authors' Addresses

   Jaime Jimenez

   Email: jaime.jimenez@ericsson.com

   Hannes Tschofenig

   Email: hannes.tschofenig@arm.com

   Dave Thaler

   Email: dthaler@microsoft.com

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