Publication

ALL accepted iiWAS2022 papers will be published by Springer in their Lecture Notes in Computer Science (LNCS). LNCS volumes are indexed in the Conference Proceedings Citation Index (CPCI), part of Clarivate Analytics’ Web of Science; Scopus; EI Engineering Index; Google Scholar; DBLP; etc. Selected high-quality papers will be invited to be published, after revision and extension, in special issues of international journals.

Scope

Data and information are crucial in providing evidence based decision making in many aspect of human activities, as an individual or as a group. The way information and communication technology are used to collect, process, analysis and store data has always evolves. New techniques are invented, existing techniques are improved and old techniques are integrated to the new. Each of these provided some challenges and opportunities to our research community in finding the best way to meet these challenges. iiWAS provides research community with the opportunity to share and discuss their ideas. 

Prior to 2020, iiWAS has been held in Munich (2019), Yogyakarta (2018), Salzburg (2017), Singapore (2016), Brussels (2015), Hanoi (2014), Vienna (2013), Bali (2012), Ho Chi Minh City (2011), Paris (2010), Kuala Lumpur (2009), and Linz (2008). Last years, iiWAS2020 and iiWAS2021 conferences were held as virtual conference. This year, iiWAS2022 will be held in person in Italy.

Submissions

iiWAS accepted four different types of contributions:
- Original theoretical work:  The contributions are expected to show original work that provide foundations to further progress research in the area. Rigorous proofs and/or performance measurements are expected for this type of contribution.
- Real life case study:  The contributions are expected to show a real life case study of an adopted concept and technology. The analysis of the case study should provide an original insight and findings, backing up by data collected from experiments and/or observation.
- Experimental work:  The contributions are expected to show reporting of rigorous comparative experiments of existing algorithms/systems to provide insight to the current state of the art in a research domain.
- Lessons learnt reports: The contributions are expected to show lessons learnt from adoption of complex technology integration or implementation.

Topics

Specific topics of interest include, but are not limited to:
- Web Intelligence
- Data science and Data engineering
- Cloud and Edge Computing
- Trusted, Responsible and Interpretable AI
- Big data & Data Analytics
- Cloud data management
- NoSQL databases
- Crowdsourcing
- Social networks analysis
- Sensors data management
- Data Mining
- Semantic Web and Ontology
- Search and Information Technology
- Query Language and Processing
- Advanced web technology and application
- Spatial data storage, query and processing
- Health informatics
- Education informatics
- Data Integration, Metadata Management, and Interoperability
- Distributed, parallel and cloud databases
- Social media analytics and processing
- Data modelling and analysis
- Big data processing
- Web content analysis, semantic and knowledge
- Data systems integration
- Data connectivity in internet of things
- Blockchain Technologies
- Linked Open Data
- Deep/Hidden Web