Towards MKM in the Large: Modular Representation and Scalable Software Architecture

MKM has been defined as the quest for technologies to manage mathematical knowledge. MKM "in the small" is well-studied, so the real problem is to scale up to large, highly interconnected corpora: "MKM in the large". We contend that advances in two areas are needed to reach this goal. We need representation languages that support incremental processing of all primitive MKM operations, and we need software architectures and implementations that implement these operations scalably on large knowledge bases. We present instances of both in this paper: the MMT framework for modular theory-graphs that integrates meta-logical foundations, which forms the base of the next OMDoc version; and TNTBase, a versioned storage system for XML-based document formats. TNTBase becomes an MMT database by instantiating it with special MKM operations for MMT.Comment: To appear in The 9th International Conference on Mathematical Knowledge Management: MKM 201

A Model-Based Approach for the Management of Electronic Invoices

The globalized market pushes companies to expand their business boundaries to a whole new level. In order to efficiently support this environment, business transactions must be executed over the Internet. However, there are several factors complicating this process, such as the current state of electronic invoices. Electronic invoice adoption is not widespread because of the current format fragmentation originated by national regulations. In this paper we present an approach based on Model-Driven Engineering techniques and abstractions for supporting the core functions of invoice management systems. We compare our solution with the traditional implementations and try to analyze the advantages MDE can bring to this specific domain

HUDDL for description and archive of hydrographic binary data

Many of the attempts to introduce a universal hydrographic binary data format have failed or have been only partially successful. In essence, this is because such formats either have to simplify the data to such an extent that they only support the lowest common subset of all the formats covered, or they attempt to be a superset of all formats and quickly become cumbersome. Neither choice works well in practice. This paper presents a different approach: a standardized description of (past, present, and future) data formats using the Hydrographic Universal Data Description Language (HUDDL), a descriptive language implemented using the Extensible Markup Language (XML). That is, XML is used to provide a structural and physical description of a data format, rather than the content of a particular file. Done correctly, this opens the possibility of automatically generating both multi-language data parsers and documentation for format specification based on their HUDDL descriptions, as well as providing easy version control of them. This solution also provides a powerful approach for archiving a structural description of data along with the data, so that binary data will be easy to access in the future. Intending to provide a relatively low-effort solution to index the wide range of existing formats, we suggest the creation of a catalogue of format descriptions, each of them capturing the logical and physical specifications for a given data format (with its subsequent upgrades). A C/C++ parser code generator is used as an example prototype of one of the possible advantages of the adoption of such a hydrographic data format catalogue

A Grammatical Inference Approach to Language-Based Anomaly Detection in XML

False-positives are a problem in anomaly-based intrusion detection systems. To counter this issue, we discuss anomaly detection for the eXtensible Markup Language (XML) in a language-theoretic view. We argue that many XML-based attacks target the syntactic level, i.e. the tree structure or element content, and syntax validation of XML documents reduces the attack surface. XML offers so-called schemas for validation, but in real world, schemas are often unavailable, ignored or too general. In this work-in-progress paper we describe a grammatical inference approach to learn an automaton from example XML documents for detecting documents with anomalous syntax. We discuss properties and expressiveness of XML to understand limits of learnability. Our contributions are an XML Schema compatible lexical datatype system to abstract content in XML and an algorithm to learn visibly pushdown automata (VPA) directly from a set of examples. The proposed algorithm does not require the tree representation of XML, so it can process large documents or streams. The resulting deterministic VPA then allows stream validation of documents to recognize deviations in the underlying tree structure or datatypes.Comment: Paper accepted at First Int. Workshop on Emerging Cyberthreats and Countermeasures ECTCM 201

Compressed materialised views of semi-structured data

Query performance issues over semi-structured data have led to the emergence of materialised XML views as a means of restricting the data structure processed by a query. However preserving the conventional representation of such views remains a significant limiting factor especially in the context of mobile devices where processing power, memory usage and bandwidth are significant factors. To explore the concept of a compressed materialised view, we extend our earlier work on structural XML compression to produce a combination of structural summarisation and data compression techniques. These techniques provide a basis for efficiently dealing with both structural queries and valuebased predicates. We evaluate the effectiveness of such a scheme, presenting results and performance measures that show advantages of using such structures