14 research outputs found

    Accurator: Nichesourcing for Cultural Heritage

    Full text link
    With more and more cultural heritage data being published online, their usefulness in this open context depends on the quality and diversity of descriptive metadata for collection objects. In many cases, existing metadata is not adequate for a variety of retrieval and research tasks and more specific annotations are necessary. However, eliciting such annotations is a challenge since it often requires domain-specific knowledge. Where crowdsourcing can be successfully used for eliciting simple annotations, identifying people with the required expertise might prove troublesome for tasks requiring more complex or domain-specific knowledge. Nichesourcing addresses this problem, by tapping into the expert knowledge available in niche communities. This paper presents Accurator, a methodology for conducting nichesourcing campaigns for cultural heritage institutions, by addressing communities, organizing events and tailoring a web-based annotation tool to a domain of choice. The contribution of this paper is threefold: 1) a nichesourcing methodology, 2) an annotation tool for experts and 3) validation of the methodology and tool in three case studies. The three domains of the case studies are birds on art, bible prints and fashion images. We compare the quality and quantity of obtained annotations in the three case studies, showing that the nichesourcing methodology in combination with the image annotation tool can be used to collect high quality annotations in a variety of domains and annotation tasks. A user evaluation indicates the tool is suited and usable for domain specific annotation tasks

    Crowd vs Experts: Nichesourcing for Knowledge Intensive Tasks in Cultural Heritage

    Get PDF
    The results of our exploratory study provide new insights to crowdsourcing knowledge intensive tasks. We designed and performed an annotation task on a print collection of the Rijksmuseum Amsterdam, involving experts and crowd workers in the domain-specific description of depicted flowers. We created a testbed to collect annotations from flower experts and crowd workers and analyzed these in regard to user agreement. The findings show promising results, demonstrating how, for given categories, nichesourcing can provide useful annotations by connecting crowdsourcing to domain expertise

    The Rijksmuseum collection as linked data

    Get PDF
    Many museums are currently providing online access to their collections. The state of the art research in the last decade shows that it is beneficial for institutions to provide their datasets as Linked Data in order to achieve easy cross-referencing, interlinking and integration. In this paper, we present the Rijksmuseum linked dataset (accessible at http://datahub.io/dataset/rijksmuseum), along with collection and vocabulary statistics, as well as lessons learned from the process of converting the collection to Linked Data. The version of March 2016 contains over 350,000 objects, including detailed descriptions and high-quality images released under a public domain license

    Modeling cultural heritage data for online publication

    Get PDF
    An increasing number of cultural heritage institutions publish data online. Ontologies can be used to structure published data, thereby increasing interoperability. To achieve widespread adoption of ontologies, institutions such as libraries, archives and museums have to be able to assess whether an ontology can adequately capture information about their artifacts. We identify six requirements that should be met by ontologies in the cultural heritage domain, based upon modeling challenges encountered while publishing data of the Rijksmuseum Amsterdam and challenges observed in related work. These challenges regard specialization, object- and event-centric approaches, temporality, representations, views and subject matter. For each challenge, we investigate common modeling approaches, by discussing two models regularly used in the museum sector: the CIDOC Conceptual Reference Model and the Europeana Data Model. The outlined approaches and requirements provide insights for data modeling practices reaching beyond the cultural heritage sector

    Invenit: Exploring cultural heritage collections while adding annotations

    No full text
    The growing number of cultural heritage collections published as Linked Data has given rise to a vast source of collection objects to explore. To provide an experience which goes beyond traditional search, the links from objects to terms from structured vocabularies can be used to create new paths to explore. We present INVENiT, a semantic search system which leverages these paths for result diversification and clustering. Users can freely explore the collection, but are also able to contribute their knowledge by annotating collection objects. The added information is directly incorporated in the search results. The demo can be found at http://sealinc.ops.few.vu.nl/invenit/
    corecore