Database Usability Enhancement in Data Exploration

Database usability has become an important research topic over the last decade. In the early days, database management systems were maintained by sophisticated users like database administrators. Today, due to the availability of data and computing resources, more non-expert users are involved in database computation. From their point of view, database systems lack ease of use. So researchers believe that usability is as important as the performance and functionality of databases and therefore developed many techniques such as natural language interface to enhance the ease of use of databases. In this thesis, we find some deeper technical issues in database usability, so we look at several core database technologies to further improve the ease of use of databases in two dimensions: we help users process data and exploit computing capacities. We start by helping users find the data. In the real world, public data is everywhere on the Web, but it is scattered around. We extract a prototype relational knowledge base to solve this problem. We start from the most basic binary mapping relationships (sometimes also named bridge tables) between entities from the web. This mapping relationship facilitates many data transformation applications such as auto-correct, auto-fill, and auto-join. After finding the data, we help users explore the data. When users issue queries to explore the data, their query results may contain too many items. So the system designer has to present a small subset of representative and diverse items rather than all items. This is known as the query result diversification problem. We propose the RC-Index, which helps to solve the diversification problem by significantly reducing the number of items that must be retrieved by the database to form a diverse set of a desired size. It is nearly an order of magnitude faster than the state-of-the-art and has a good performance guarantee, which improves the ease of use of databases in terms of querying. Finally, we shift our focus from data to computing capacities. We propose a framework to help users choose configurations in the cloud. Cloud computing has revolutionized data analysis, but choosing the right configuration is challenging because the common pricing mechanism of the public cloud is too complicated. Users have to consider low-level resources to find the best plan for their computational tasks. To address this issue, we propose a new market-based framework for pricing computational tasks in the cloud. We introduce agents to help users configure their personalized databases, which improves the ease of use of databases in the cloud

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Computer Aided Verification

This open access two-volume set LNCS 10980 and 10981 constitutes the refereed proceedings of the 30th International Conference on Computer Aided Verification, CAV 2018, held in Oxford, UK, in July 2018. The 52 full and 13 tool papers presented together with 3 invited papers and 2 tutorials were carefully reviewed and selected from 215 submissions. The papers cover a wide range of topics and techniques, from algorithmic and logical foundations of verification to practical applications in distributed, networked, cyber-physical, and autonomous systems. They are organized in topical sections on model checking, program analysis using polyhedra, synthesis, learning, runtime verification, hybrid and timed systems, tools, probabilistic systems, static analysis, theory and security, SAT, SMT and decisions procedures, concurrency, and CPS, hardware, industrial applications

Value enhanced collaborative working (VECW)

In recent years, the service industry has been made aware of the advantages of risk sharing and inter-firm collaborations. In the current turbulent business environment, a large proportion of Small and Medium sized Enterprises (SME) firms rely on collaboration and partnering with other businesses. The value of such collaboration is highly enhanced by pooling resources to help exploit complementarities between the collaborating businesses and significantly increasing performance and management. Many studies have been conducted on the determinants of collaboration success or failures. However, authors have suggested further research to provide a framework to cover the factors responsible for enhanced value within collaborative working. In particular, the susceptibility of SMEs to successfully collaborate is significantly less than that of large organisations. Hence this was the focus of the current study. The research was focused on establishing the value enhancement of collaborative working within ServQ’s, the sponsoring organisation’s, collaborative environment. The main aim of this research project is ‘To investigate the potential of Value-Enhanced Collaborative Working (VECW) in an SME management advisory firm’. The aim was achieved with the help of the development of a VECW framework based on the issues faced by ServQ’s collaborative environment. To achieve this aim, an inductive research approach was adopted; this was facilitated by literature reviews and research methods such as semi-structured interviews, focus groups and scenario planning. This was to ensure that the project was an applied research based on the sound foundations of available theories on collaborative working. The research was initiated with a preliminary case study of the sponsoring organisation to better understand it. This period of initial investigation entailed learning more about the organisation’s management and working culture. Parallel to the initial case study, a literature review helped establish a definition of Value Enhanced Collaborative Working (VECW) as well as a conceptual VECW framework. Three key factors were identified in the conceptual VECW framework; these were considered as three separate but equally important branches that together will create a sustainable longterm collaborative working environment. The first factor identified was the People factor; the main output from this was the development of a Collaboration Charter. The Process factor developed a business process model for ServQ while the Tools factor was established through scenario planning. The output of this research was a development of a VECW framework. The research work progressed chronologically by first developing a conceptual VECW framework followed by the development of each of the People, Process and Tool factors in further detail with the help of mechanisms such as Collaboration Charter and business process models. Eventually the framework recommended how all these three factors together enhance the value of collaboration in ServQ. These outputs established the mechanisms to balance all the three factors within ServQ resulting in development of a sustainable collaboration environment. The research has contributed to knowledge by providing a VECW framework in an industrial setting that can be replicated in similar organisations with required changes. In addition, it complements the wide array of literature pertaining to Collaborative Working, SMEs, services organisations and Value