Information is typically mapped manually using syntax. Whilst this approach has been very successful - especially when the information to be mapped is not too complex - there are several clear disadvantages:
However, if a company wishes to trade electronically with other companies or public administrations, they would like to exchange different types of information ranging from orders to company returns as easily as possible. Today, the greatest barrier to this wish is not the cost of hardware, software or communications. Rather, it is the "interoperability" barrier – i.e. the difficulty in providing information to potential trading and manufacturing partners in a format their systems can understand. Companies do not have time to learn the technical specifications of XML, EDI or IDOCs. However, they do know the user concepts (semantics) of their information. They want something that allows information transformation, but based on their knowledge only, and for it to be easy and inexpensive to do without the reliance on technicians or consultants. The aim is to address many of the aforementioned problems by allowing anyone to create mappings based upon semantics – even if they are not realising they are using semantics - Ie instead of focussing on syntax, to concentrate on identifying semantic assets and mapping those instead. For example, two concepts <Town> and <Ville> may be grouped into one logical semantic entity called "XX" which is mapped to a well defined concept of an address. This could apply across language barriers but also within them eg <Pavement> and <Sidewalk>. The mapping process is typically based on ontologies used to define and link these semantic assets. The link to the original syntax is still made, but this is completely transparent to the user. This is necessary since the mapping between the two need to operate on a syntax level to extract information and then reformat it in a way required by the target.
CREMA states that it intends to apply its approach ‘to integrate data from concrete existing software systems [and] to do this a software application will be developed  which will enable a business analyst driven approach for the automatic linking of organisations data schema (databases, sensors, messages, spreadsheets, knowledge sources). Thus CREMA Task “Data Harmonisation Services” purpose is to link these sources to the model identified in the CREMA Task on “CREMA Data Model”. The approach will be to use annotations, ontologies and semantic mapping techniques to rapidly construct the links and then from there generate standalone automatic transformation executables (manufacturing maps). These will be available in the CREMA map store
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