Maxim Kolchin

LIPID MAPS (LIPID Metabolites and Pathways Strategy), www.lipidmaps.org, provides a systematic and standardized approach to organizing lipid structural and biochemical data. Founded 20 years ago, the LIPID MAPS nomenclature and classification has become the accepted community standard. LIPID MAPS provides databases for cataloging and identifying lipids at varying levels of characterization in addition to numerous software tools and educational resources, and became an ELIXIR-UK data resource in 2020. This paper describes the expansion of existing databases in LIPID MAPS, including richer metadata with literature provenance, taxonomic data and improved interoperability to facilitate FAIR compliance. A joint project funded by ELIXIR-UK, in collaboration with WikiPathways, curates and hosts pathway data, and annotates lipids in the context of their biochemical pathways. Updated features of the search infrastructure are described along with implementation of programmatic access via API and SPARQL. New lipid-specific databases have been developed and provision of lipidomics tools to the community has been updated. Training and engagement have been expanded with webinars, podcasts and an online training school.

Number of connected devices grows much faster than their manufacturers and customers agree on standards which could realise addressing, identification, discovery, composition, security and privacy of these devices. A result of such situation is a lack of interoperability among different clusters of connected devices and systems. This is one of the known research problems in Internet of Things. At the same time knowledge engineering methods and Semantic Web technologies proofs that they could be a solution to this problem. In this paper we present an architecture of a platform built using aforementioned technologies and a case study demonstrating the middleware in analysing measurements of air temperature in city.

Lack of commonly accepted standards for the connected devices' APIs caused the situation when each manufacturer or Smart Home enthusiast creates its own mobile application to control their devices. The authors propose a lightweight framework to the design of self-descriptive API on top of CoAP protocol using Hydra Core, Schema.org and Semantic Sensor Network vocabularies which allow to create a mobile application with an adaptive user interface to interact with any type of device. In this paper the authors enumerate the requirements, describe the framework, evaluate it on three exemplified devices built using ESP8266 Wi-Fi module and describe the architecture of the mobile application for interacting with such devices.

Knowledge-based Systems and Expert Systems, in particular, are expensive to build and difficult to validate and debug because of their complexity and dynamism. Therefore, it is not easy for knowledge engineer and domain expert to identify the gaps and mistakes in knowledge base. Unit testing is unable to cover validation process at all stages, in many cases manual thorough review of decision process is needed. In this paper we spot main approaches to validation and verification issue and describe a component that helps to debug a knowledge base by visualising execution of rules that derive a particular result. This component is developed for Knowledge-based Systems built on Drools Platform1 and we demonstrate application of this component in a knowledge-based engineering system for structural optical design.

In this paper we discuss our experience with the design, development and deployment of MneMojno Semantic Web Service and Mobile Application. MneMojno makes use of Semantic Web Technologies to create a Web service and a mobile application for rating and providing detail information about food products. This paper introduces the main components of the system: a framework to capture information about food products from various sources, a semantic web service and a framework to visualize and analyze usage statistics. Finally, we discuss challenges and problems we faced during the development and present our conclusions and future directions for exploration in terms of developing MneMojno further.