IEEE Conferences

Symposium on Services for Data Ecosystems (SDE)

Effectively unlocking data values and enabling seamless data flows across businesses, companies and organisations has become the ‘holy grail’ for data technologies and the data-driven world. The current practice and conditions in data management and governance in many areas or most organisations, and existing data sharing solutions, however, have significantly limited applications of data for internal and external applications crossing companies and organisations. The question on how to effectively unlock the data value remains to be answered. This necessitates a more holistic research on the concept of data economy and its ecosystem, rather than narrowly focusing on a single element, such as sharing technologies, trading platforms or marketplaces. Data ecosystems (DEs) are the future of data management that they allow companies to share data and collaborate in order to get valuable insights and develop value added services.

The Service Computing (SC) community has been developing standards and technologies for integration of software, applications, and collaboration of services and processes by overcoming system heterogeneity. SC technologies definitely can play a significant role in DEs, in which novel tools, best practices, solutions and platforms that will allow: (1) for organisations to transform their data to data products with governance, privacy protection, to extend and broaden data applications, and to enable data exchange and flow crossing organisations, domains and sectors; (2) for data consumers to search, query, explore, and combine data products for advanced data analytics and providing value added services.

Program

Date/Time	Session	Presentation
Monday 7/3 14:00 - 15:10 Location: Regency Ballroom A/B	CWS_SYM_1 Session Chair: Jian Yang, Macquarie University	Keynote: On the Governance of Data Flows and the Intentional Design and Implementation of Data Markets Raul Castro Fernandez, University of Chicago Raul is interested in understanding the economics and value of data, including the potential of data markets to unlock that value. His research aims to understand how to use data better and builds systems to share, discover, prepare, integrate, and process data. They use techniques from data management, statistics, and machine learning. Raul is an assistant professor in the Computer Science department at the University of Chicago. Before UChicago, he did a postdoc at MIT with Sam Madden and Mike Stonebraker. And before that, he completed his PhD at Imperial College London with Peter Pietzuch. He received a SIGMOD'23 test-of-time-award for his PhD work.
Monday 7/3 15:25 - 16:35 Location: Regency Ballroom A/B	CWS_SYM_2 Data Ecosystems: Governance and Transformation Session Chair: Amin Beheshti, Macquarie University	Process GPT: Transforming Business Process Management with Generative Artificial Intelligence Amin Beheshti, Jian Yang, Quan Z. Sheng, Boualem Benatallah, Fabio Casati, Schahram Dustdar, Hamid Reza Motahari Nezhad, Xuyun Zhang, Emma Xue Sustainability and Governance of Data EcosystemsEdoardo Ramalli, Barbara Pernici Decentralized Data Governance as Part of a Data Mesh Platform: Concepts and ApproachesArif Wider, Sumedha Verma, Atif Akhtar Data Product-Oriented Services for Data EcosystemWei Emma Zhang, Perry Chen, Jian Yang, Jianwen Su, Quan Z. Sheng
Tuesday 7/4 9:25 - 10:35 Location: Wrigley	CWS_SYM_3 Session Chair: Heiko Ludwig, IBM TJ Watson Research	Keynote: Empowering Generative AI with Knowledge Base 4.0: Towards Linking Analytical, Cognitive, and Generative Intelligence Amin Beheshti, Macquarie University Intelligence refers to the ability to acquire and apply knowledge and skills, comprising three fundamental components: knowledge, experience, and creativity. Consequently, three primary Artificial Intelligence (AI) systems exist: Analytical AI, Cognitive AI, and Generative AI. Through a fresh perspective, this keynote explores the concept of Generative AI and showcases its transformative capacity to revolutionize business processes. We will introduce Knowledge Base 4.0 as the backend data for AI engines, which allows for linking knowledge and experience to enable empowering generative AI. The primary objective is to integrate knowledge graphs into Large Language Models (LLMs) to address the challenge of factual knowledge deficiency and enhance their overall performance. We also introduce our innovation, ProcessGPT, which aims to facilitate automation, augmentation, and improvement of data-centric and knowledge-intensive processes. Amin Beheshti is a Full Professor of Data Science and the Director of the Centre for Applied Artificial Intelligence at Macquarie University, Sydney, Australia. Additionally, he is an Adjunct Professor of Computer Science at UNSW Sydney, Australia. Amin completed his PhD and Postdoc in Computer Science and Engineering at UNSW Sydney, and holds a Master's and Bachelor's degree in Computer Science, both with First Class Honours. As a distinguished Data and AI Science researcher, Amin has been invited to serve as a Keynote Speaker, General-Chair, PC-Chair, Organisation-Chair, and program committee member of top international conferences. He is the leading author of several authored books and has secured over $22.7 million, to date, in research grants for AI-Enabled, Data-Centric, and Intelligence-Led projects.
Tuesday 7/4 10:50 - 12:00 Location: Wrigley	CWS_SYM_4 Session Chair: Jian Yang, Macquarie University	Panel/Open Discussion: What is the role of service computing in data ecoystems?

Symposium Chairs

Jian Yang, Macquarie University, Australia (jian.yang@mq.edu.au)
Heiko Ludwig, IBM’s Almaden Research Center in San Jose, USA (hludwig@us.ibm.com)

Program Committee

Raul Castro Fernandez, University of Chicago, USA
Barbara Pernici, Politecnico di Milano, Italy
Arif Wider, HTW Berlin, Germany
Amin Beheshti, Macquarie University, Australia
Wei Zhang, University of Adelaide, Australia
Yanjun Shu, Harbin Institute of Technology, China