Workshop on Best Practices and Dynamic Knowledge Graphs
Held at the 1st IBEROAMERICAN KNOWLEDGE GRAPHS AND SEMANTIC WEB CONFERENCE
Held at the 1st IBEROAMERICAN KNOWLEDGE GRAPHS AND SEMANTIC WEB CONFERENCE
The role of knowledge for machine understanding of natural phenomena and language has been growing during the last decade. Knowledge Graphs (KGs) have a large number of applications like semantic search, disambiguation of natural language, deep reasoning, machine reading, and text analytics. Additionally KG applied for Internet of Things use cases is an emerging topic, as demonstrated with iot.schema.org currently under development. However, the adoption of standards to create KG is not always consistent to make use of the full potential of the Open Web Platform’s ability to link one fact to another. This workshop intends to bring together researchers and practitioners that have faced and addressed the challenge of combining diverse methods for knowledge representations in different domains, and for different tasks with Knowledge Graphs by Linked Data experts with the goal of creating and sharing a set of best practices for generating and maintaining KGs.
This workshop aims at bringing together research and industry communities working on the different aspects of data semantics, and standards-based solutions for the Internet and Web of Things.
The role of knowledge for machine understanding of natural phenomena and language has been growing during the last decade. Knowledge Graphs (KG) are being widely used by companies such as Google, Facebook, Microsoft, Apple, etc. for this purpose to extract knowledge out of the vast amounts of information on the Web. Additionally KG applied for Internet of Things (IoT) use cases is an emerging topic, as demonstrated with iot.schema.org which is under development. Rapid growth in the Internet of Things (IoT) means that connected sensors and actuators will be inundating the Web infrastructure with data. Semantics is increasingly seen as a key enabler for integration of sensor data and the broader Web ecosystem. Building intelligent applications for everyday use is the long-cherished aim of Artificial Intelligence (AI). With numerous devices deployed and used in day-to-day applications including mobile phones, tablets, wearable and other connected sensing and actuation devices, collectively referred to as the Internet of Things (IoT). Thus, there is an unprecedented opportunity to develop contextually intelligent applications with far- reaching societal implications. They can deliver fine-grained services in various areas such as healthcare, manufacturing, transportation and social good. However, the adoption of standards to create KG is not always consistent to make use of the full potential of the Open Web Platform's ability to link one fact to another. There are several challenges such as how to design interoperable KGs to ensure reusability? How to measure the quality of KGs according to a set of qualitative criteria? Hence, there is a need to develop best practices to easily discover and reuse existing knowledge.
The purpose of the workshop is to discuss how Semantic Web standards and/or AI related techniques can help create and consume data in IoT following clear methodology to build intelligent applications. This workshop aims at bringing together research and industry communities working on the different aspects of data semantics, and standard-based solutions for the Internet and Web of Things.
Topics of interest include, but not limited to:
The submissions must be written in English using the Springer style (LNCS/CCIS one-column page format). We receive full papers (12-15 pages), short papers (6-8 pages) and demos (2-4 pages). Please note that HTML+RDFa contributions are also welcome as long as the layout complies with the LNCS style.
All proposed papers must be submitted using the KOGPIT19 conference management system.
Following is the list of program committee members in no particular order :
The workshop will take place at the Hotel Grand Memories Santa Maria , Villa Clara, Cuba .