The amounts of data available are unceasingly increasing, and data-driven research is becoming evermore common. The use of data-driven techniques presents several challenges such as managing the large volumes of data, coping with data in different forms and formats, and dealing with differences in data consistency and quality. The pace at which new data arrive and existing data are modified is also a challenge. New challenges are continually arising also within the fields where we use, share and integrate data. LiU researchers are getting to grips with all of these challenges.
Ontologies
Work is under way to define and standardise terminology in the form of ontologies. In this way, the challenge posed by data of different types and different forms can be met. Ontologies provide a formal and unambiguous representation of knowledge within a certain field, or “domain”. This makes it possible to share, reproduce and integrate data within this particular domain.
Researchers at LiU contribute to developing high-quality ontologies. One way in which they do this is by producing methods and tools to develop ontologies, for debugging and alignment, and for the visualisation of ontologies and networks of ontologies.
Linked data
Resource Description Framework (RDF) is a language to describe information, and its use is one of the fundamental techniques within the semantic web. Data elements are identified by URLs, and can in this way be coupled to another set of data, and the coupling can be global.
The vison is to view the web as a single interconnected database.
The development of the web has come a long way, but challenges remain. One example is the use of federated solutions, a technique that makes it possible to seek information in several searchable resources at the same time. This is an important aid in managing the large amount of data. In this case, LiU researchers face and deal with problems of both volume and variation.
Other studies include why some content is more popular than other, why one video becomes viral while others receive zero showings, how fake news spreads, and how confidential information is leaked.
Research at LiU concerns not only the theoretical bases but also the technology required to build systems around graph data.
The semantic web
The semantic web standardizes how one refers to various objects that one wants to describe – the meaning of a concept or object. Researchers at LiU work both connecting and ascribing semantics to data.Ontologies
Work is under way to define and standardise terminology in the form of ontologies. In this way, the challenge posed by data of different types and different forms can be met. Ontologies provide a formal and unambiguous representation of knowledge within a certain field, or “domain”. This makes it possible to share, reproduce and integrate data within this particular domain.
Researchers at LiU contribute to developing high-quality ontologies. One way in which they do this is by producing methods and tools to develop ontologies, for debugging and alignment, and for the visualisation of ontologies and networks of ontologies.
Linked data
Resource Description Framework (RDF) is a language to describe information, and its use is one of the fundamental techniques within the semantic web. Data elements are identified by URLs, and can in this way be coupled to another set of data, and the coupling can be global.
The vison is to view the web as a single interconnected database.
The development of the web has come a long way, but challenges remain. One example is the use of federated solutions, a technique that makes it possible to seek information in several searchable resources at the same time. This is an important aid in managing the large amount of data. In this case, LiU researchers face and deal with problems of both volume and variation.
Web-based services
The research attempts to provide insights, understanding and improvements to existing web-based services, while making possible the services of tomorrow. The work encompasses a broad spectrum of topics and embodies many aspects of performance, integrity and security. It provides new solutions to deliver interactive services over the web.Other studies include why some content is more popular than other, why one video becomes viral while others receive zero showings, how fake news spreads, and how confidential information is leaked.
Graph databases
Connections and relationships are becoming increasingly important in both research and business. Since this type of data when expressed mathematically appears as a graph, it is known as “graph data”.Research at LiU concerns not only the theoretical bases but also the technology required to build systems around graph data.
