Page 125 - Trust in ICT 2017

Trust in ICT 2

and waterways, etc. Moreover, abstraction references like images, vectors, points, lines, and polygons are
mapped to location attributes. A new hybrid method of data is identifying the physical location which
combines three-dimensional vector points of physical space. This information is becoming more realistically
visually descriptive. Recently, the web access to huge amounts of geographic data enables users to create
customer applications and make complex spatial information, which is called mashup application of the web.
An editable map of the geographical data is used to offer street maps, aerial/satellite imageries, geocoding,
search, and car navigation, etc.

For the identification-related applications, the identification can mean the process of recognizing or
identifying persons, objects, or animals, etc. The bar code is increasingly being used in the industry, and the
radio frequency identification (RFID) is being used as an alternative. In these applications, the identification
is used to reduce running out of stock or wasted products. Credit cards and passports in the wallet are to
prove who you are. Recently, biometrics, iris recognition, and voice recognition technologies are used for
identification. Theft and counterfeiting of critical or costly items such as drugs, food, repair parts, or
electronic components will be reduced because manufacturers will know where their products are at all
times. Product wastage or spoilage will be reduced because environmental sensors will alert suppliers or
consumers when sensitive products are exposed to excessive heat, cold, vibration, or other risks. Supply
chains will operate far more efficiently because suppliers will ship only the products needed when and where
they are needed. Consumer and supplier prices should also drop accordingly.
For data intensive applications, a large volume of data typically terabytes in size and referred to as big data
are processed. Computing applications requiring large volumes of data and their processing times to I/O are
deemed data intensive. The rapid growth of the Internet led to vast amounts of information available online.
Parallel processing can typically involve partitioning or subdividing the data into multiple segments which can
be processed independently using the same executable application program in parallel on an appropriate
computing platform. The data-intensive computing are managing and processing exponentially growing data
volumes, significantly reducing associated data analysis cycles to support practical and timely applications.
Information extraction and indexing of web documents can derive significant performance benefits on data
parallel executions since the web can be processed in parallel. The semantic query language like
SPARQL protocol and RDF query language (SPARQL) may be enabled to retrieve and manipulate data stored
in RDF format of the web. Massive data from millions of IoT sensors may need the non-structured query
language (NoSQL) database for storage and retrieval of data, making some operations faster than the
relational database. The high-speed ICT infrastructure allows the data to be partitioned among the available
computing resources and processed independently to achieve performance and scalability based on the
amount of data. The cloud computing system controls the scheduling, execution, load balancing,
communications, and movement of programs and data across the distributed computing cluster.

For science and engineering applications, various types of signals or information such as electromagnetic
signals or biometric information are converted to digital forms. The weather conditions and chemical formula
are represented by digital data. The conversion of analogue symbols or signals to digital is needed to relevant
mapping methods or converting rules.
The data formats described above are summarized as follows:
• Telecommunication and broadcast applications:
– Audio data encoding including analogue and digital audio;

– Visual data encoding including film, colour, graphic, 3D display, and holographic format, etc.
– Descriptive data encoding including metadata, etc.
• Internet and web applications (including semantic contexts):
– File, image, documents, computer language, etc.
– Chunk-based formats (e.g. MIME, CSV, XML, JSON, etc.).

• Location-related applications:
– Geographical information including geographical map and physical 3D spaces;
– Mainly used for transport and logistics industry (by using geolocation maps).

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