Exchanging and analyzing ideas across different software tools and repositories is needed to implement the concepts of open innovation and holistic innovation management. However, a precise and formal definition for the concept of an idea is hard to obtain. In this paper, the authors introduce an ontology to represent ideas. This ontology provides a common language to foster interoperability between tools and to support the idea life cycle. Through the use of an ontology, additional benefits like semantic reasoning and automatic analysis become available. Our proposed ontology captures both a core idea concept that covers the ‘heart of the idea’ and further concepts to support collaborative idea development, including rating, discussing, tagging, and grouping ideas. This modular approach allows the idea ontology to be complemented by additional concepts like customized evaluation methods. The authors present a case study that demonstrates how the ontology can be used to achieve interoperability between innovation tools and to answer questions relevant for innovation managers that demonstrate the advantages of semantic reasoning.

Exchanging and analyzing ideas across different software tools and repositories is needed to implement the concepts of open innovation and holistic innovation management. However, a precise and formal definition for the concept of an idea is hard to obtain. In this paper, the authors introduce an ontology to represent ideas. This ontology provides a common language to foster interoperability between tools and to support the idea life cycle. Through the use of an ontology, additional benefits like semantic reasoning and automatic analysis become available. Our proposed ontology captures both a core idea concept that covers the ‘heart of the idea’ and further concepts to support collaborative idea development, including rating, discussing, tagging, and grouping ideas. This modular approach allows the idea ontology to be complemented by additional concepts like customized evaluation methods. The authors present a case study that demonstrates how the ontology can be used to achieve interoperability between innovation tools and to answer questions relevant for innovation managers that demonstrate the advantages of semantic reasoning.

Today, lots of online communities co-exist where users suggest and discuss ideas and problems. However, the diversity of such idea networks and the high launch rate of new platforms make it hard to keep track of the current idea community landscape. This article presents an approach to integrate arbitrary online ideation platforms that allow users to publicly utter and discuss new ideas or provide solutions to previously announced problems. We introduce our prototypical implementation of the approach that provides a single point of access for innovation managers, problem solvers and solution seekers

This article presents results from a survey of web-based idea portals. We focus on such portals that allow users to publicly utter and discuss new ideas or provide solutions to previously announced problems. We note that the number of such portals has been continuously growing ever since the late nineties and are concerned with the question of how to support interested companies in selecting a suitable portal

This paper proposes a common ontology for ratings, i.e. for quantitative user feedback data. Such a framework allows for semantic interoperability of data that adheres to it, which in turn enables the re-use, by making it independent from the original system.In contrast to prior attempts to establish an unambiguous vocabulary, this approach introduces two components that are in our view necessary to formally understand what a user's rating actually means. The first is the aspect or facet, i.e. the viewing angle that was chosen to look at the rated thing. The second is the meta-model of scales following the scales of measurement that are widely used in descriptive statistics. So in plain words, we allow to formally specify how many out of how many score points something gets and with regards to what.We follow the open world assumption of the Web Ontology Language (OWL) and design a vocabulary that is not specific to any domain. In turn, we rely on the premise that all domain specific concepts are available as semantic web resources with appropriate URIs.