Data Workflow - A Workflow Model for Continuous Data Processing

Online data or streaming data are getting more and more important for enterprise information systems, e.g. by integrating sensor data and workflows. The continuous flow of data provided e.g. by sensors requires new workflow models addressing the data perspective of these applications, since continuous data is potentially infinite while business process instances are always finite.\ud In this paper a formal workflow model is proposed with data driven coordination and explicating properties of the continuous data processing. These properties can be used to optimize data workflows, i.e., reducing the computational power for processing the workflows in an engine by reusing intermediate processing results in several workflows

STREAM Journal, Vol. 1, No. 4, pp 1-16. October-December 2002

CONTENTS: Hon Mun MPA Pilot Project on community-based natural resources management, by Nguyen Thi Hai Yen and Bernard Adrien. An experience with participatory research in Tam Giang Lagoon, Thua Thien-Hue, by Ton That Chat. Experiences and benefits of livelihoods analysis, by Michael Reynaldo, Orlando Arciaga, Fernando Gervacio and Catherine Demesa. Lessons learnt in implementing PRA in livelihoods analysis, by Nguyen Thi Thuy. Lessons learnt from livelihoods analysis and PRA in the Trao Reef Marine Reserve, by Nguyen Viet Vinh. Using the findings from a participatory poverty assessment in Tra Vinh Province, by Le Quang Binh

Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)

Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data

STREAM Journal, Vol. 5, No. 1, pp 1-18. January-March 2006

CONTENTS: Policy development as a theme and policy briefs as a genre, by Graham Haylor and William Savage. Decriminalizing Cambodian family-scale fishers through a livelihoods approach to law reform, by Nao Thuok and Chun Sopha. Longer pond leases in Orissa, by Reshmee Guha and Rubu Mukherjee. One-stop aqua shop: a “one-window delivery” service center for aqua-farmers and fishers, by S.D. Tripathi, Rubu Mukherjee and Kuddus Ansary. Fisheries and aquaculture policy formulation process in Pakistan, by Muhammad Junaid Wattoo and Dr. Muhammad Hayat. Improving the international marine ornamental fish trade to sustain and improve the livelihoods of poor people involved in the trade, by Aniza Suspita, Michael J. Phillips and Samliok Ndobe

Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources

Apache Calcite is a foundational software framework that provides query processing, optimization, and query language support to many popular open-source data processing systems such as Apache Hive, Apache Storm, Apache Flink, Druid, and MapD. Calcite's architecture consists of a modular and extensible query optimizer with hundreds of built-in optimization rules, a query processor capable of processing a variety of query languages, an adapter architecture designed for extensibility, and support for heterogeneous data models and stores (relational, semi-structured, streaming, and geospatial). This flexible, embeddable, and extensible architecture is what makes Calcite an attractive choice for adoption in big-data frameworks. It is an active project that continues to introduce support for the new types of data sources, query languages, and approaches to query processing and optimization.Comment: SIGMOD'1

Intelligent student engagement management : applying business intelligence in higher education

Advances in emerging ICT have enabled organisations to develop innovative ways to intelligently collect data that may not be possible before. However, this leads to the explosion of data and unprecedented challenges in making strategic and effective use of available data. This research-in-progress paper presents an action research focusing on applying business intelligence (BI) in a UK higher education institution that has developed a student engagement tracking system (SES) for student engagement management. The current system serves merely as a data collection and processing system, which needs significant enhancement for better decision support. This action research aims to enhance the current SETS with BI solutions and explore its strategic use. The research attempts to follow socio-technical approach in its effort to make the BI application a success. Progress and experience so far has revealed interesting findings on advancing our understanding and research in organisation-wide BI for better decision-making

STREAM Journal, Vol. 4, No. 3, pp 1-19. July-September 2005

CONTENTS: One-stop Aqua Shops: an emerging phenomenon in Eastern India, by Graham Haylor, Rubu Mukerjee and S.D. Tripathi. Ranchi One-stop Aqua Shop, by Ashish Kumar. Kaipara One-stop Aqua Shop, by Kuddus Ansary. Bilenjore One-stop Aqua Shop, by Bhawani Sankar Panda. Patnagarh One-stop Aqua Shop, by Dipti Behera and Lingraj Otta. Using bar-coding in a One-stop Aqua Shop, by Christopher Keating