Interaction for Information Discovery Empowering Information Consumers
Information Discovery (ID) is predominantly addressed by approaches from Artificial Intelligence (AI). Automatic ID scans large amounts of data and identifies as many potential candidates for discovery as possible. Mass discovery may in fact serve the needs of many information consumers. However, that does not mean that it addresses a broad range of user interests, too. Economies of scale urge the development of automatic tools to address user needs only from a certain critical mass. Hence, many user needs remain unaddressed. This is where HCI comes into play and provides fundamentals for pattern languages that empower information consumers to stage their own information discovery. With this paper we want to draw attention to an approach that is developed around the paradigm of human-centered interaction design. We present an Open Discovery Language that can completely be controlled by information consumers.
KeywordsInformation Discovery Information extraction Data science Collaborative work Interaction design Participatory design Pattern languages Human-centred information management
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