-connections of abstract description systems

Location-aware systems or location-based services: a survey with applications to CoViD-19 contact tracking

With the CoViD-19 pandemic, location awareness technologies have seen renewed interests due to the numerous contact tracking mobile application variants developed, deployed, and discussed. For some, location-aware applications are primarily a producer of geospatial Big Data required for vital geospatial analysis and visualization of the spread of the disease in a state of emergency. For others, comprehensive tracking of citizens constitutes a dangerous violation of fundamental rights. Commercial web-based location-aware applications both collect data and-through spatial analysis and connection to services-provide value to users. This value is what motivates users to share increasingly private and comprehensive data. The willingness of users to share data in return for services has been a key concern with web-based variants of the technology since the beginning. With a focus on two privacy preserving CoViD-19 contact tracking applications, this survey walks through the key steps of developing a privacy preserving context-aware application: from types of applications and business models, through architectures and privacy strategies, to representations.

Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn

Bio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study.

Community-Driven Linked Data Authoring and Production of Consolidated Linked Data

User-generated content can help the growth of linked data. However, we lack interfaces enabling ordinary people to author linked data. Secondly, people have multiple perspectives on the same concept and different contexts. Thirdly, not enough ontologies exist to model various data. Therefore, we propose an approach to enable people to share various data through an easy-to-use social platform. Users define their own concepts and multiple conceptualizations are allowed. These are consolidated using semi-automatic schema alignment techniques supported by the community. Further, concepts are grouped semi-automatically by similarity. As a result of consolidation and grouping, informal lightweight ontologies emerge gradually. We have implemented social software, called StYLiD, to realize our approach. It can serve as a platform motivating people to bookmark and share different things. It may also drive vertical portals for specific communities with integrated data from multiple sources. Experimental observations support the validity of our approach.