Report on the Third International Workshop on Semantic Web Meets Health Data Management (SWH 2020)

Creating a holistic view of patient data comes with many challenges but also brings many benefits for disease prediction, prevention, diagnosis, and treatment. Especially in the COVID-19 era, this is more important than ever before. The third International Workshop on Semantic Web Meets Health Data Management (SWH) was aimed at bringing together an interdisciplinary audience who was interested in the fields of Semantic Web, data management, and health informatics. The workshop goal was to discuss the challenges in healthcare data management and to propose new solutions for the next generation of data-driven healthcare systems. In this article, we summarize the outcomes of the workshop, and we present a number of key observations and research directions that emerged from presentations.

A Coding-Free Software Framework for Developing Lightweight Web Data Management Systems

Increasingly more enterprises are intending to deploy data management systems in the cloud. However, the complexity of software development significantly increases both time and learning costs of data management system development. In this paper, we investigate the coding-free construction of a data management system based on Software-as-a-Service (SaaS) architecture, in which a practical application platform and a set of construction methods are proposed. Specifically, by extracting the common features of data management systems, we design a universal web platform to quickly generate and publish customized system instances. Then, we propose a method to develop a lightweight data management system using a specific requirements table in a spreadsheet. The corresponding platform maps the requirements table into a system instance by parsing the table model and implementing the objective system in the running stage. Finally, we implement the proposed framework and deploy it on the web. The empirical results demonstrate the feasibility and availability of the coding-free method for developing lightweight web data management systems.

Intensional data on the web

We call data intensional when it is not directly available, but must be accessed through a costlyinterface. Intensional data naturally arises in a number of Web data management scenarios, suchas Web crawling or ontology-based data access. Such scenarios require us to model an uncertainview of the world, for which, given a query, we must answer the question “What is the best thingto do next?” Once data has been retrieved, the knowledge of the world is revised, and the wholeprocess is repeated, until enough knowledge about the world has been obtained for the particularapplication considered. In this article, we give an overview of the steps underlying all intensionaldata management scenarios, and illustrate them on three concrete applications: focused crawling,online influence maximization in social networks, and mining crowdsourced data.