Page 165 - Trust in ICT 2017

Trust in ICT 2

Before making a clear consensus of the future information infrastructure, discussion among people may be
used to make conceptual distinctions and organize ideas. The conceptual framework identifies their priority
and chooses initial action items. The conceptual framework is abstract representations, connected to the
research that directs the collection and analysis of data. By collecting data and assessing the evidence, formal
hypotheses take place with possible explanations. Finally, the conceptual model of the ICT infrastructure for
the knowledge society is characterized without regard to their underlying assumptions and technologies. The
abstract model may partition a set of functions or layers with certain classifications of the knowledge
information infrastructure. An open, voluntary, and consensus-based standardization process will be critical
to build the ICT infrastructure toward a future knowledge society.
When the ICT infrastructure may extend to other convergence industries, it may provide computing, storage,
and networking resources for energy, transport, health, education, and environments, etc. Since people
relating to other industries have their own data formats to share and distribute their idea, the data sharing
platform is very important to access data with confidence. For the future ICT industry, the collective
intelligence framework is essential to accumulate data from various sensors, networking systems, and cloud
servers, etc. The location and presence information of the IoT systems are used to extract the context-aware
information from raw data. However, there are some limitations in these types of data. All the data sources
have their own output format by given types. In the current Internet and web, for example, only
URL/URI/uniform source name (URN) are available to identify data types for certain Internet protocol (IP)
domains of the Internet. There are only available for the telephone numbering and addressing structure for
fixed and mobile telephony. Toward future convergence services, the data types including identification,
numbering, and addressing should be extended to support IoT/M2M devices and equipment of other
convergence industries.

Moreover, data sources are mainly classified into private data and public data. For private data, malicious
threats may attack to obtain user sensitive information for identification, detection, and tracking, etc. The
malicious activity may be based on IP addresses, numbering, and URLs. Some data may be discovered through
an incident monitoring process which is shared with private communities. Therefore, the trust framework
for the future knowledge society should be built to observe data from any source and protect against
malicious activities.

Technically, in order to get a common understanding of the future knowledge society, the following
outstanding issues for standardization can be investigated as follows:
– How to connect the forms of knowledge in relationship to data:

• Writing books and documents is not enough. The recursive mechanism to accumulate individual
knowledge and opinions including tacit knowledge are needed to create new forms of
knowledge.
– Metadata is like a glue to connecting data, information, and knowledge:
• Various types of metadata may be defined when data is created, delivered, processed, shared,
and consumed by users and communities. It may be called source metadata, content metadata,
service metadata, user metadata, and application-specific context metadata, etc.
• Metadata may be parsed to extract the useful meanings of data, a capability which is part of
the intelligent processing of data.
• Metadata may be created after pre-processing or post-processing of data with related context-
aware information such as condition, situation, and environment.

• The discrimination between information and knowledge from raw data is the understanding
and interpretation of their contents, which may be described as metadata.

– New forms of development, acquisition, and spread of knowledge:
• The new tools to create, collect, accumulate, share and distribute data, information, and
knowledge are needed to invent new forms of knowledge. This may evolve from social media
with the progress of user interface and human perception technologies.

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