April 2019 - Yongjing Zhang represents Huawei at oneM2M's Technical Plenary (TP).
In this interview, he discusses the importance of semantic interoperability in Internet of Things (IoT) solutions and how oneM2M is advancing standardisation in this area.
Q. Please begin by describing your roles and responsibilities within oneM2M.
YZ I have been working in oneM2M as the Management, Abstraction and Semantics (MAS) working group chair for almost six years (three terms).
To begin with, I focused on the areas of device management, data modelling and semantics.
After the recent re-structuring of oneM2M, I took on a new role as a oneM2M TP Vice Chair. Now, my job is to serve the oneM2M community from a higher perspective and this now includes external cooperation with other IoT organisations.
Within Huawei, I work for the IoT Platform Product Line (belonging to the Cloud & AI Product & Service) as a senior standard manager. My team is responsible for standardisation and research around the IoT platform. We also deal with supported service domains such as the Connected Vehicle, Smart Cities, etc.
We participate in many related standardisation organisations and industry alliances in China and globally. oneM2M is one of the most important organisations
that we have been contributing to as Huawei is one of the founding members.
Q. China is a large IoT market in the global context. Let us begin by talking about your impressions of what is happening locally?
YZ I would say that China is among the fastest developing regions in the world in terms of the IoT market. The government plays a very important and active role in terms of forming national policies, innovation projects and industry development guidelines and standards. All these are beneficial to the IoT industry. On top of this, there is a lot of internal innovation momentum from different enterprises. Together, these factors stimulate the domestic IoT market and will help it grow rapidly.
For example, over 500 cities in China are planned or being constructed as Smart City projects. The size of the market is projected to be 1.87 trillion RMB by 2021 and IoT technologies like NB-IoT and city-level IoT platforms are key enablers of this growth. We are seeing these trends in many of the projects where Huawei is participating, including Yingtan which is the first NB-IoT enabled Smart City in China.
Another recent growth story in China is the Connected Vehicle and Smart Transportation sector, thanks to the maturing C-V2X (e.g. LTE-V) technology and the release of the V2X spectrum (20MHz) at 5.9GHz. Several provinces and cities have built the test fields in either closed sites, highways or open roads (such as Wuxi) for car-to-road coordinated autonomous driving and Smart Transportation. End-to-end solutions from the chipset to the On-Board Unit (OBU), the Roadside Unit (RSU) platform and applications can now be provided together by industry partners including Huawei, Qualcomm and Datang (who are also the members of oneM2M).
There are also many other IoT driven or related initiatives happening in China across different domains, like the "Industrial IoT/Internet" and "Internet+". We don't have the time to address them all today, but I'd like to just highlight two key successful factors from all these activities - the availability of a common service IoT platform and the readiness of interoperable standards.
Q. In addition to being a Vice-Chair of the Technical Plenary, you have a strong interest in semantic interoperability. What is semantic interoperability?
YZ We know that standards are the tools to enable interoperability. If we take the OSI 7-layer protocol stack as a reference, interoperability can happen at all different layers. Low-layer protocols can ensure the interoperability of data transport from one entity to another, while high-layer protocols (including schemas) can provide the interoperability to enable understanding of the data exchanged between entities. Semantic Interoperability is at the top level of data understanding, compared to other related concepts like Syntactic Interoperability or Transport Interoperability.
If we take the analogy of communications between two people, the use of email or SMS to transmit a message are two different data transport services. One can only receive the message correctly if both sides choose the same service. This is an example of Transport Interoperability.
Assuming SMS is chosen as the transport means, the two people might not be able to communicate if the message is written in different languages, for example English vs. Chinese. Using a common language is a prerequisite for communication and understanding. This can be considered as an example of Syntactic Interoperability.
However, this is not yet enough to ensure the accurate understanding of each other. Imagine that two parties are negotiating a business contract. When the message says, "the price is 100 dollars", it may mean totally different things on each side since 1 US dollar is different from 1 Singapore dollar. In other cases, people may mean the same thing but use different words or abbreviations due to cultural factors or domain knowledge differences (for instance, soccer vs football). So, there must be some common understanding of the communication context and alignment of terminologies. We call this Semantic Interoperability.
Q. Why is semantic interoperability so important to the IoT industry?
YZ In the IoT world, semantic interoperability is especially important because machines are much less capable of processing ambiguous information than humans. Semantic interoperability ensures the meaning of the data (or command) to be interpreted (or executed) correctly.
To turn on a light bulb, different implementations (even standards) may choose to send the command as 'turn on' or 'switch on', or simply '1'. This causes the issue of interoperability and results in market fragmentation.
For example, to deploy a smart home solution, you may have to choose between ZigBee or Z-Wave technologies from the very beginning. It won't be easy to change or plug in a fancy new device later if it uses another technology. From the perspective of developers, service providers and users, this increases the cost of system development, integration and maintenance.
And this is even more true for a complex system like a smart city, which requires interoperability not only within a single domain, but also across multiple domains. For example, monitoring involves collecting data from various departments such as utilities, transportation, public security, and environment. Information must then be fused to generate city-wide actions to increase efficiency and effectiveness of public services and emergency response. Semantic interoperability is a must-have on top of IoT data collection and sharing in this case.
Q. What is oneM2M doing in the area of semantic interoperability?
YZ oneM2M has positioned semantic interoperability as one of the key enabling technologies from the very beginning. The related topics have been studied and standardised in the MAS WG through to Release 3. Now, Release 4 work will continue in the Requirements and Domain Models and the System Design and Security working groups.
There are two tracks in oneM2M to address the semantic interoperability issues in a broad sense. One is through abstract data modeling; the other is using ontology and semantic description.
On data modeling, oneM2M has consolidated a common data model that abstracts from individual technology specific models, such as OCF and OMA GotAPI, using the Smart Device Template as the schema base. oneM2M inherited the Smart Device Template from the Home Gateway Initiative (HGI). Using this common model, an application can interact with different devices consistently without worrying about the device-specific implementations. This work was developed in close collaboration with external organisations like OCF, thanks to contributions from joint members on both sides. As a result, the oneM2M Home Domain Information Model is fully aligned with the OCF. oneM2M is now extending this work to other vertical domains such as smart cities, health, vehicular, railway, etc.
On ontology and semantic description, oneM2M leverages powerful semantic tools like RDF/OWL (defined by W3C) to construct the oneM2M Base Ontology as the common vocabulary for interworking with heterogeneous systems. On top of that, advanced features like semantic annotation, discovery, query, validation and mashup are also provided to enable the applications to better describe, understand, search and orchestrate IoT data. The ontology work was aligned with ETSI SAREF ontology development so that SAREF based solutions can be run on top of oneM2M smoothly. oneM2M also liaised with W3C Web of Things and IEEE P2413, and developed a whitepaper on semantic interoperability jointly (link here).
Q. What should IoT users be doing to maximise their benefits from semantic interoperability?
YZ As I mentioned earlier, semantic interoperability would greatly save the cost of system development, integration and maintenance. System designers and developers should choose common data models, ontologies and semantic tools, very often found in open standards like oneM2M, as the basis to build an open and flexibly interwork able system architecture.
End users, including consumers, enterprises and city governments, should also be careful about the technologies they select during the procurement process. Long term evolution should be considered with the support of semantically interoperable technologies to ensure they are not limited as their immediate needs evolve.
Q. Are there any other observations or topics you would like to cover?
YZ The IoT industry is breaking new ground and it won't be simple to achieve semantic interoperability. Technically, there is a learning curve to overcome if one chooses to implement the technologies we discussed earlier. This involves making a strategic choice and commitment, especially when the Return of Investment (ROI) is not very significant at an early stage. However, the return would be seen in future large-scale deployments.
From a business perspective, some communities and companies would still like to keep their differential competitiveness by building closed technology stacks. Also, incumbents are reluctant to give up their advantages (stickiness) that may be jeopardised by opening up to semantic interoperability.
However, we are already seeing many endeavors in the research and standards communities to build a more harmonised and semantically interoperable IoT ecosystem. Collaborations are ongoing between organisations. I'm looking forward to some break-throughs and large-scale market take-up within the coming few years.
