DeeDS combines active database functionality with critical timing constraints and integrated system monitoring. Since the reactive database mechanisms, or rule management system, must meet critical deadlines, we must employ methods that make triggering of rules and execution of actions predictable. We will focus on the scheduling issues associated with dynamic scheduling of workloads where the triggered transactions have hard, firm or soft deadlines, and how transient overloads may be resolved by substituting transactions by computationally cheaper ones. The rationale for a loosely coupled general purpose event monitoring facility, that works in tight connection with the scheduler, is presented. For performance and predictability, the scheduler and event monitor are executing on a separate CPU from the rest of the system. Real-time database accesses in DeeDS are made predictable and efficient by employing methods such as main memory resident data, full replication, eventual consistency, and prevention of global deadlocks.
One important feature for the current and next generation of information systemsis the ability to be able tocooperate. Information systems that are able to cooperateare referred to as cooperative information systems. The problem of moving the stateof the art from information systems designed asislands of automationto cooperativeinformation systems has primarly been addressed by the distributed artificial intelli-gence community and the database community. For example, the distributed artificialintelligence community has investigated cooperation strategies such as task sharingand result sharing, whereas the database community has developed techniques forinteroperability over heterogenous databases. One characteristic of cooperative infor-mation systems is that no individual solution can satisfactorily support all requiredcharacteristics of cooperative information systems. This thesis takes the position thata synthesis of results from the distributedartificial intelligence community and thedatabase community is a promising direction for developing cooperative informationsystems.In this thesis, active capability (as defined within active databases) is considered asan important core technology for cooperative information systems. Active capabilityis supported by event condition action (ECA) rules with the following semantics:when an event E occurs, evaluate condition C, and if the condition is satisfied, thenexecute action A. The applicability of using ECA rules has primarly been exploredwithin database systems and has recently initiated ECA related research within otherresearch communities such as real-time and workflow.This thesis focuses on what is required in an interface between information sys-tems when using an active capability approach to supporting the major cooperationstrategies as formulated in distributed artificial intelligence. The significance of the2work reported in this thesis concerns two major issues. First, advanced types ofcooperation strategies such as task sharing and result sharing can now span the do-mains of database and distributed artificial intelligence architectures. Second, as thiswork synthesizes and extends results from two different research communities, it pro-vides a good foundation for using active capability as one of the core technologies forcooperative information systems.
This paper presents and analyzes an object-oriented analysis and design course that has been given in three different configurations for students who are already familiar with object-oriented programming. The results show that the course configurations have not had a major impact on the students' performances.
This paper proposes a new approach to associating rules with events in object-oriented database systems. In it we propose a new run time mechanism, which associates rules with specific event definitions. This provide a basis for indexing rules by event definitions, which reduces rule checking to a minimum. The proposed subscription mechanism is general, in that it can be applied to both primitive events and composite events. Both rules and events are represented as first class objects. This architecture has been adopted in the ACOOD2 prototype on top of ONTOS.
This paper propose a simple and powerful approach to associating rules with events in reactive object-oriented database systems. In it we propose a new run time subscription mechanism, which associates rules with specific event definitions. This brings optimization considerations - when to fire a rule - to the language level. The proposed subscription mechanism reduces rule checking to a minimum. It can be applied to both primitive and composite events. Both rules and events are represented as first class objects. This architecture has been adopted in the ACOOD2 prototype on top of ONTOS.
This paper describes our approach and experiences of applying techniques in complex event processing to fleet management systems. Current fleet management systems do not have support for complex event processing, hence they are limited to reacting to simple events such as door open, and vehicle reached waypoint. We argue that fleet management systems can benefit from having support for complex event processing. In this paper we present an implemented fleet management system that supports complex event processing.
Active rules (i.e., event condition action rules, triggers) have been put forward as a technique for reacting to important events, and thereby avoiding polling or embedding rule processing in applications. Despite the promises of active rules technology, the usage of active rules is low in practice. It has often been claimed (by database researchers) that the reason why few active rules applications have been built is due to the lack of support in analysis and design phases. Hence, there are very few notations or guidelines available for software engineers who develop active rules applications.In this paper, we propose modelling templates for UML state-charts and UML-A statecharts for how software engineers can capture the fundamentals of active rules. By following the proposed modelling templates and notations for active rules, it will be easier for software engineers to develop applications that rely on active rules technology.
Interest has increased recently in synthesizing solutions to CIS problems by using results from the database and distributed AI communities. Such synthesis is not without its difficulties; results do not always transfer seamlessly to a new, complex domain. In this paper we highlight the difficulties encountered in our attempts to use event detection and subscription mechanisms (proposed in current active databases) for the problem of efficient result sharing in CIS. A solution to such problems is described, in the form of a refined, context based subscription mechanism.
Coordination and collaboration are naturally used by groups for carrying out activities and solving problems that require cooperation. However, getting a set of computer agents to do the same has been a problem - primarily addressed by the AI community and recently by the database community as workflow and process management problems (for example, in business processes, electronic commerce, logistics). Not surprisingly, the problem has been addressed at different levels of abstraction by the two communities. Coordination protocols as well as task and result sharing have been investigated by the AI community; specification of alternative transaction models to meet the requirements of non-traditional applications, and their execution have been addressed by the database community. It is evident that there is a need for bringing the two approaches together to develop systems that support cooperative problem solving. This paper - argues for the use of active databases in general and active capability in particular as an enabling technology for cooperative problem solving and cooperative information systems - details a novel approach for supporting task sharing, a key aspect of CPS, using active capability - elaborates on a methodology for mapping task shared protocols expressed in high level speech acts to Event Condition-Action (ECA) rules.
This paper critically analyse the use of active databases as an enabling technology for result sharing as defined in the DAI literature. In particular, we demostrate how ECA (Event-Condition-Action) rules can be used for supporting result shared cooperation. Further, we demonstrate how composite events as defined within active databases can help a problem solving agent to precisely specify when to take responsive action to multiple result notifications.
Coordination and collaboration are naturally used by groups for carrying out activities and solving problems that require cooperation. However, getting a set of computer agents to do the same has been a problem-primarily addressed by the AI community and recently by the database community as workflow and process management problems. Not surprisingly, the problem has been addressed at different levels of abstraction by the two communities. It is evident that there is a need for bringing the two approaches together to develop cooperative information systems. This paper argues for the use of active databases as an enabling technology for cooperative information systems, details a novel approach for supporting task sharing (a key cooperation strategy within cooperative information systems) using active capability, and elaborates on a methodology for mapping task-shared protocols expressed in high-level speech acts to event-condition-action rules.
Coordination and collaboration are naturally used by groups for carrying out activities and solving problems that require cooperation. However, getting a set of computer agents to do that same has been a problem -- primarily addressed by the AI community and recently by the database community as workflow and process management problems (e.g. in business processes, electronic commerce, logistics).
Not surprisingly, the problem has been addressed at different levels of abstraction by the two communities. Coordination protocols (both static and dynamic) as well as task and result sharing have been investigated by the AI community; system level support as well as specification and execution of relaxed notions of transaction (sometimes termed an activity) have been addressed by the database community. It is evident that combining the two will provide an effective unified solution for a class of problems that require cooperation. This paper classifies problems addressed in the AI and database literature according to degree of coordination and collaboration. It reports on work done by the authors in utilising the reactive paradigm to synthesize, from the yechniques in these areas, a common framework for the support of multi-agent problem solving, workflow, and process management. In addition to resolving the terminology used by different groups, task sharing is used to demonstrate the approach described. It is accomplished by creating either static or dynamic plans that are coordinated by ECA rules -- both pre-defined and dynamically created. The paper details the applicability of ECA rules in this domain, their adequacy, and a prototype implementation.
Research on assessing a group’s maturity in data-driven culture is rare and fragmented. This article investigates how maturity in data-driven culture can be assessed from a historical perspective. A case study was done on how the Education Council evolved in analytics maturity and as a group during 2014-2023. The assessment showed that the Education Council experienced both successful progression of group development and usage of analytics, as well as regression in group development and analytics usage. The practical implications of the findings are that group leaders need to be aware of the interplay between analytics usage and group development when planning to improve their group’s maturity in data-driven culture.
Conducting pilot projects are a common approach among organizations to test and evaluate new technology. A pilot project is often conducted to remove uncertainties from a large-scale project and should be limited in time and scope. Nowadays, several organizations are testing and evaluating artificial intelligence techniques and more advanced forms of analytics via pilot projects. Unfortunately, many organizations are experiencing problems in scaling-up the findings from pilot projects to the rest of the organization. Hence, results from pilot projects become siloed with limited business value. In this article, we present an overview of barriers for conducting and scaling-up data-driven pilot projects. Lack of senior management support is a frequently mentioned top barrier in the literature. In response to this, we present our recommendations on what type of activities can be performed, to increase the chances of getting a positive response from senior management regarding scaling-up the usage of artificial intelligence and advanced analytics within an organization.
Organisations seeking competitive advantage in the age of big data often adopt the strategy of becoming data-driven. The paper describes research in progress with an organisation pursuing this strategy. Initial results from literature study and preliminary interviews are outlined, including a two layer factor model and prototype maturity model. The next research steps are also explained.
Active databases and real-time databases have gained increased interest in recent. Both active and real-time databases are considered as important technologies for supporting non-traditional applications such as computer integrated manufacturing (CIM), process control and air-traffic control. These applications are often event driven and need to react to events in a timely and efficient manner. In this paper we address the problem of merging active databases and real-time databases. Active real-time database is a fairly new area, in which very little research has been carried out so far. However, the use of active real-time database applications has a great potential. In this paper we address several issues and open questions such as semantics, assignment of time constraints and rule selection, which need to be considered when designing active real-time databases.
Applications that rely on coordination of messages are frequently based on multi-agent systems or workflow systems. Both implementation platforms use a rule engine for the coordination of messages. Currently, classical production rules are used within multi-agent systems, and workflow systems tend to rely on active database solutions (i.e. triggers). It has been envisioned that subsequent application generations are likely to require support for hundreds or even thousands of triggers. This is in contrast to the current state-of-the-art of implementations, which only scale to a few triggers. The paper outlines a vision where a scalable trigger system is the unifying concept between workflow and multi-agent approaches for applications that require coordination facilities. In particular, the paper defines scalability and performance within an active database context. The paper explores factors and situations that influence active database performance. Finally, the paper explores promising directions for how to move the state-of-the-art to trigger systems that scale to many triggers.
This report is a summary of the First International Workshop on Active and Real-Time Database Systems (ARTDB-95) [1], held at the University of Skövde in June 1995. The workshop brought together researchers and practitioners from both the active database community and the real-time database community. The major aims of ARTDB-95 were to identify motivations, problems and requirements when combining active and real-time capabilities.
Key elements for scaling advanced analytics.
Becoming a data-driven organization is a vision for several organizations. It has been frequently mentioned in the literature that data-driven organizations are likely to be more successful than organizations that mostly make decisions on gut feeling. However, few organizations make a successful shift to become data-driven, due to a number of different types of barriers. This article investigates, the initial journey to become a data-driven organization for 13 organizations. Data has been collected via documents and interviews, and then analyzed with respect to: i) how they scaled up the usage of analytics to become data-driven; ii) strategies developed; iii) barriers encountered; and iv) usage of an overall change process. The findings are that most organizations start their journey via a pilot project, take shortcuts when developing strategies, encounter previously reported top barriers, and do not use an overall change management process.
This paper presents an approach to support event-condition-action rules and logical events in an object-oriented environment. Previous approaches in active object-oriented databases support either traditional event-condition-action rules or logical events. We see the need to integrate these two concepts in order to efficiently support specialization of events.
This paper outlines the ongoing work in Reactive Object-oriented Database Systems between the Departments of Computer Science in the University of Exeter(UK) and the University of Skovde(Sweden). The group is currently designing a monitoring system based on a reactive object oriented database with the objective of supporting efficient interaction between the active DBMS and applications (including intelligent systems). Initial work has centered on a prototype reactive object-oriented system built on top of ONTOS, a commercial OODBMS which has C++ as its base language. The prototype is referred to as ACOOD (ACtive Object Oriented Database system). We briefly discuss this prototype, showing how reactive behaviour has been incorporated into a full OODBMS albeit with some restrictions. We also outline our plans for its future extensions, and how these are motivated.
Current prototype Active Object-Oriented database systems introduce powerful event and rule specification languages. We contend that this is not in general done in a uniform and integral manner. We present a modified design for an ACtive Object-Oriented DBMS (ACOOD) currently under development at the University of Skovde. The design emphasises the key concepts being investigated, namely Events and Rules as 1st Class (ER1C). It is important because it addresses the key issue of inheritance, something not prominent in current prototype systems with a fully developed event specification system. Key features in the design are that it has a unifying concept of primitive event and of behaviour, and achieves uniformity and power with respect to inheritance. It further relates this to event specification languages for composite events, guaranteeing orthogonality of features. The paper emphasises modeling concepts, and the design is therefore of relevance to all active, object-oriented database systems. It seeks to explore the wider implications and underpinnings of current active O-O suggestions rather than enriching event and/or rule specification languages.
Active database rules are problematic to explain, understand, debug, and design irrespective of knowledge about active rule semantics. In order to address this problem, various types of active database tools have been proposed in the literature such as browsers, debuggers, analyzers, and explanation tools.This paper focuses on visualization of event detection for an explanation tool and it presents the first study on what to visualize with respect to event detection at the lowest level (i.e. visualization of event detection for a specific event type).
Establishing a data-driven culture in teams is on the agenda for many managers and analytics leaders. With a data-driven culture in place, it is envisioned that investments in analytics can be used to their full potential. In practice, most organizations struggle to establish a data-driven culture in teams and have few tools available to assess the level of maturity.
Related research has focused on maturity models in business intelligence & analytics that target the organizational level. Hence, these maturity models provide limited support for assessing the team level, e.g., why some teams do not develop a data-driven culture.
This paper used a systematic literature review and an online questionnaire to develop a matrix for assessing a team's maturity in data-driven culture. The matrix synthesizes previous work in analytics and group development. Findings from the literature review revealed a mismatch between problems addressed by the research community and perceived problems in practice by organizations.
This paper describes the active object-oriented database system ACOOD developed at the universities of Skövde and Exeter. ACOOD adds active functionality on top of the commercially available Ontos DB. The active behaviour is modelled by using Event-Condition-Action (ECA) rules. ACOOD offers all essential functionality associated with an active database. The semantics and user interface have been clearly defined in order to produce a prototype that can be used to develop database applications. The historical background of active databases and the development of ACOOD are covered in the paper together with a detailed description of the latest, redesigned version of the system. There is also a discussion of experience gained through the work with ACOOD and a comparison with similar systems.
Master data management programs are large by nature since the aim is to provide the entire enterprise with a shared trusted view of the organisation’s most critical data assets. In this paper, we present what dimensions and activities a master data management program in a large organisation should consider and how to monitor such a program once it is up and running. A heatmap approach is used to visualize the inherent complexity of a master data management program. Our approach is derived from participating in four different master data management programs in four different global organisations during 2007-2020.
Many applications need to detect and respond to occurring events and combine these event occurrences into new events with a higher level of abstraction. Specifying how events can be combined is often supported by design tools specific to the current event processing engine. However, the issue of ensuring that the combinations of events provide the system with the correct combination of information is often left to the developer to analyze. We argue that analyzing correctness of event composition is a complex task that needs tool support. In this paper we present a novel development tool for specifying composition of events with time constraints. One key feature of our tool is to automatically transform composite events for real-time systems into a timed automaton representation. The timed automaton representation allow us to check for design errors, for example, whether the outcome of combining events with different operators in different consumption policies is consistent with the requirement specification
Complex Event Processing (CEP) is a technology with support for matching patterns in a cloud or streams of events in order to support detection of specific combinations of event occurrences. A clever specification of event patterns may, for example, detect fraud attempts in a banking system, fire an alarm in response to hazardous situations in a control system or report suspicious customer behavior.
Several CEP engines have support for graphically modelling applications as well as perform tests and provide execution traces to verify the application behavior. We argue that it is beneficial to complement testing with formal verification in order to detect errors in early stages of development.
In this paper, we present the research prototype tool REX. REX is built as a loosely coupled front end to the timed-automata CASE tool UPPAAL. CEP applications and application specific properties can be specified in REX. To support formal verification, REX seamlessly transforms the CEP application together with the specified properties to the timed automata CASE tool UPPAAL where the properties are verified by the model-checker provided by UPPAAL.
Formal methods are not used in their full potential for enhancing software quality in industry. We argue that seamless support in a high-level specification tool is a viable way to provide system designers with powerful and paradigm specific formal verification techniques. Event condition action (ECA) rules can be used to model and implement reactive behavior in, for example, the semantic web. Independently of target system, the behavior of rule-based systems are known to be hard to analyze. The REX tool is a rule-based front-end to the timed automata CASE-tool Uppaal. The model-checker in Uppaal is used by REX enabling seamless support for model-checking rule-based specifications in REX.
This paper presents experiences from modeling and verifying a system of industrial complexity as interacting rules using EX. We conclude that repeatedly performing normal analysis when constructing a system with interacting rules is a viable way of coping with the complexity of the model. Additionally, we present an implemented algorithm for optimizing the model to reduce the effect of state-space explosion.
Despite proven successful in previous projects, the use of formal methods for enhancing quality of software is still not used in its full potential in industry. We argue that seamless support for formal verification in a high-level specification tool enhances the attractiveness of using a formal approach for increasing software quality.
Commercial Complex Event Processing (CEP) engines often have support for modelling, debugging and testing CEP applications. However, the possibility of utilizing formal analysis is not considered.
We argue that using a formal approach for verifying a CEP system can be performed without expertise in formal methods. In this paper, a prototype tool REX is presented with support for specifying both CEP systems and correctness properties of the same application in a high-level graphical language. The specified CEP applications are seamlessly transformed into a timed automata representation together with the high-level properties for automatic verification in the model-checker UPPAAL.
This paper uses the BEAST benchmark to present the first comprehensive performance study of object‐oriented active database management systems (ADBMS). BEAST stresses the performance‐critical components of active systems: event detection, event composition, rule retrieval, and rule firing. Method invocation events and transactional events are taken into account. Four systems, namely ACOOD, NAOS, Ode, and SAMOS, have been tested with the benchmark tests of BEAST. The performance measurements demonstrate achievements in the area of active database technology, but also indicate trade‐offs (e.g., between performance and functionality). Finally, the benchmark identifies optimizations and provides hints to ADBMS designers about producing systems with adequate performance and functionality—as well as some open issues.