Methods for Semantic Interoperability in AutomationML-based Engineering

Industrial engineering is an interdisciplinary activity that involves human experts from various technical backgrounds working with different engineering tools. In the era of digitization, the engineering process generates a vast amount of data. To store and exchange such data, dedicated international standards are developed, including the XML-based data format AutomationML (AML). While AML provides a harmonized syntax among engineering tools, the semantics of engineering data remains highly heterogeneous. More specifically, the AML models of the same domain or entity can vary dramatically among different tools that give rise to the so-called semantic interoperability problem. In practice, manual implementation is often required for the correct data interpretation, which is usually limited in reusability. Efforts have been made for tackling the semantic interoperability problem. One mainstream research direction has been focused on the semantic lifting of engineering data using Semantic Web technologies. However, current results in this field lack the study of building complex domain knowledge that requires a profound understanding of the domain and sufficient skills in ontology building. This thesis contributes to this research field in two aspects. First, machine learning algorithms are developed for deriving complex ontological concepts from engineering data. The induced concepts encode the relations between primitive ones and bridge the semantic gap between engineering tools. Second, to involve domain experts more tightly into the process of ontology building, this thesis proposes the AML concept model (ACM) for representing ontological concepts in a native AML syntax, i.e., providing an AML-frontend for the formal ontological semantics. ACM supports the bidirectional information flow between the user and the learner, based on which the interactive machine learning framework AMLLEARNER is developed. Another rapidly growing research field devotes to develop methods and systems for facilitating data access and exchange based on database theories and techniques. In particular, the so-called Query By Example (QBE) allows the user to construct queries using data examples. This thesis adopts the idea of QBE in AML-based engineering by introducing the AML Query Template (AQT). The design of AQT has been focused on a native AML syntax, which allows constructing queries with conventional AML tools. This thesis studies the theoretical foundation of AQT and presents algorithms for the automated generation of query programs. Comprehensive requirement analysis shows that the proposed approach can solve the problem of semantic interoperability in AutomationML-based engineering to a great extent

Compressing Labels of Dynamic XML Data using Base-9 Scheme and Fibonacci Encoding

The flexibility and self-describing nature of XML has made it the most common mark-up language used for data representation over the Web. XML data is naturally modelled as a tree, where the structural tree information can be encoded into labels via XML labelling scheme in order to permit answers to queries without the need to access original XML files. As the transmission of XML data over the Internet has become vibrant, it has also become necessary to have an XML labelling scheme that supports dynamic XML data. For a large-scale and frequently updated XML document, existing dynamic XML labelling schemes still suffer from high growth rates in terms of their label size, which can result in overflow problems and/or ambiguous data/query retrievals. This thesis considers the compression of XML labels. A novel XML labelling scheme, named “Base-9”, has been developed to generate labels that are as compact as possible and yet provide efficient support for queries to both static and dynamic XML data. A Fibonacci prefix-encoding method has been used for the first time to store Base-9’s XML labels in a compressed format, with the intention of minimising the storage space without degrading XML querying performance. The thesis also investigates the compression of XML labels using various existing prefix-encoding methods. This investigation has resulted in the proposal of a novel prefix-encoding method named “Elias-Fibonacci of order 3”, which has achieved the fastest encoding time of all prefix-encoding methods studied in this thesis, whereas Fibonacci encoding was found to require the minimum storage. Unlike current XML labelling schemes, the new Base-9 labelling scheme ensures the generation of short labels even after large, frequent, skewed insertions. The advantages of such short labels as those generated by the combination of applying the Base-9 scheme and the use of Fibonacci encoding in terms of storing, updating, retrieving and querying XML data are supported by the experimental results reported herein

Labelling Dynamic XML Documents: A GroupBased Approach

Documents that comply with the XML standard are characterised by inherent ordering and their modelling usually takes the form of a tree. Nowadays, applications generate massive amounts of XML data, which requires accurate and efficient query-able XML database systems. XML querying depends on XML labelling in much the same way as relational databases rely on indexes. Document order and structural information are encoded by labelling schemes, thus facilitating their use by queries without having to access the original XML document. Dynamic XML data, data which changes, complicates the labelling scheme. As demonstrated by much research efforts, it is difficult to allocate unique labels to nodes in a dynamic XML tree so that all structural relationships between the nodes are encoded by the labels. Static XML documents are generally managed with labelling schemes that use simple labels. By contrast, dynamic labelling schemes have extra labelling costs and lower query performance to allow random updates irrespective of the document update frequency. Given that static and dynamic XML documents are often not clearly distinguished, a labelling scheme whose efficiency does not depend on updating frequency would be useful. The GroupBased labelling scheme proposed in this thesis is compatible with static as well as dynamic XML documents. In particular, this scheme has a high performance in processing dynamic XML data updates. What differentiates it from other dynamic labelling schemes is its uniform behaviour irrespective of whether the document is static or dynamic, ability to determine all structural relationships between nodes, and the improved query performance in both types of document. The advantages of the GroupBased scheme in comparison to earlier schemes are highlighted by the experiment results