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The way information is presented to users in online community platforms has an influence on the way the users create new information. This is the case, for instance, in question-answering fora, crowdsourcing platforms or other social computation settings. To better understand the effects of presentation policies on user activity, we introduce a generative model of user behaviour in this paper. Running simulations based on this user behaviour we demonstrate the ability of the model to evoke macro phenomena comparable to the ones observed on real world data.
Modeling and publishing Linked Open Data (LOD) involves the choice of which vocabulary to use. This choice is far from trivial and poses a challenge to a Linked Data engineer. It covers the search for appropriate vocabulary terms, making decisions regarding the number of vocabularies to consider in the design process, as well as the way of selecting and combining vocabularies. Until today, there is no study that investigates the different strategies of reusing vocabularies for LOD modeling and publishing. In this paper, we present the results of a survey with 79 participants that examines the most preferred vocabulary reuse strategies of LOD modeling. Participants of our survey are LOD publishers and practitioners. Their task was to assess different vocabulary reuse strategies and explain their ranking decision. We found significant differences between the modeling strategies that range from reusing popular vocabularies, minimizing the number of vocabularies, and staying within one domain vocabulary. A very interesting insight is that the popularity in the meaning of how frequent a vocabulary is used in a data source is more important than how often individual classes and properties arernused in the LOD cloud. Overall, the results of this survey help in understanding the strategies how data engineers reuse vocabularies, and theyrnmay also be used to develop future vocabulary engineering tools.
Various best practices and principles guide an ontology engineer when modeling Linked Data. The choice of appropriate vocabularies is one essential aspect in the guidelines, as it leads to better interpretation, querying, and consumption of the data by Linked Data applications and users.
In this paper, we present the various types of support features for an ontology engineer to model a Linked Data dataset, discuss existing tools and services with respect to these support features, and propose LOVER: a novel approach to support the ontology engineer in modeling a Linked Data dataset. We demonstrate that none of the existing tools and services incorporate all types of supporting features and illustrate the concept of LOVER, which supports the engineer by recommending appropriate classes and properties from existing and actively used vocabularies. Hereby, the recommendations are made on the basis of an iterative multimodal search. LOVER uses different, orthogonal information sources for finding terms, e.g. based on a best string match or schema information on other datasets published in the Linked Open Data cloud. We describe LOVER's recommendation mechanism in general and illustrate it alongrna real-life example from the social sciences domain.
Schema information about resources in the Linked Open Data (LOD) cloud can be provided in a twofold way: it can be explicitly defined by attaching RDF types to the resources. Or it is provided implicitly via the definition of the resources´ properties.
In this paper, we analyze the correlation between the two sources of schema information. To this end, we have extracted schema information regarding the types and properties defined in two datasets of different size. One dataset is a LOD crawl from TimBL- FOAF profile (11 Mio. triple) and the second is an extract from the Billion Triples Challenge 2011 dataset (500 Mio. triple). We have conducted an in depth analysis and have computed various entropy measures as well as the mutual information encoded in this two manifestations of schema information.
Our analysis provides insights into the information encoded in the different schema characteristics. It shows that a schema based on either types or properties alone will capture only about 75% of the information contained in the data. From these observations, we derive conclusions about the design of future schemas for LOD.
The Multimedia Metadata Ontology (M3O) provides a generic modeling framework for representing multimedia metadata. It has been designed based on an analysis of existing metadata standards and metadata formats. The M3O abstracts from the existing metadata standards and formats and provides generic modeling solutions for annotations, decompositions, and provenance of metadata. Being a generic modeling framework, the M3O aims at integrating the existing metadata standards and metadata formats rather than replacing them. This is in particular useful as today's multimedia applications often need to combine and use more than one existing metadata standard or metadata format at the same time. However, applying and specializing the abstract and powerful M3O modeling framework in concrete application domains and integrating it with existing metadata formats and metadata standards is not always straightforward. Thus, we have developed a step-by-step alignment method that describes how to integrate existing multimedia metadata standards and metadata formats with the M3O in order to use them in a concrete application. We demonstrate our alignment method by integrating seven different existing metadata standards and metadata formats with the M3O and describe the experiences made during the integration process.
In this paper, we compare two approaches for exploring large,rnhierarchical data spaces of social media data on mobile devicesrnusing facets. While the first approach arranges thernfacets in a 3x3 grid, the second approach makes use of arnscrollable list of facets for exploring the data. We have conductedrna between-group experiment of the two approachesrnwith 24 subjects (20 male, 4 female) executing the same set ofrntasks of typical mobile users" information needs. The resultsrnshow that the grid-based approach requires significantly morernclicks, but subjects need less time for completing the tasks.rnFurthermore, it shows that the additional clicks do not hamperrnthe subjects" satisfaction. Thus, the results suggest thatrnthe grid-based approach is a better choice for faceted searchrnon touchscreen mobile devices. To the best of our knowledge,rnsuch a summative evaluation of different approaches for facetedrnsearch on mobile devices has not been done so far.
Expert-driven business process management is an established means for improving efficiency of organizational knowledge work. Implicit procedural knowledge in the organization is made explicit by defining processes. This approach is not applicable to individual knowledge work due to its high complexity and variability. However, without explicitly described processes there is no analysis and efficient communication of best practices of individual knowledge work within the organization. In addition, the activities of the individual knowledge work cannot be synchronized with the activities in the organizational knowledge work.rnrnSolution to this problem is the semantic integration of individual knowledgernwork and organizational knowledge work by means of the patternbased core ontology strukt. The ontology allows for defining and managing the dynamic tasks of individual knowledge work in a formal way and to synchronize them with organizational business processes. Using the strukt ontology, we have implemented a prototype application for knowledge workers and have evaluated it at the use case of an architectural fifirm conducting construction projects.
We present the user-centered, iterative design of Mobile Facets, a mobile application for the faceted search and exploration of a large, multi-dimensional data set of social media on a touchscreen mobile phone. Mobile Facets provides retrieval of resources such as places, persons, organizations, and events from an integration of different open social media sources and professional content sources, namely Wikipedia, Eventful, Upcoming, geo-located Flickr photos, and GeoNames. The data is queried live from the data sources. Thus, in contrast to other approaches we do not know in advance the number and type of facets and data items the Mobile Facets application receives in a specific contextual situation. While developingrnMobile Facets, we have continuously evaluated it with a small group of fifive users. We have conducted a task-based, formative evaluation of the fifinal prototype with 12 subjects to show the applicability and usability of our approach for faceted search and exploration on a touchscreen mobile phone.
Ontologies play an important role in knowledge representation for sharing information and collaboratively developing knowledge bases. They are changed, adapted and reused in different applications and domains resulting in multiple versions of an ontology. The comparison of different versions and the analysis of changes at a higher level of abstraction may be insightful to understand the changes that were applied to an ontology. While there is existing work on detecting (syntactical) differences and changes in ontologies, there is still a need in analyzing ontology changes at a higher level of abstraction like ontology evolution or refactoring pattern. In our approach we start from a classification of model refactoring patterns found in software engineering for identifying such refactoring patterns in OWL ontologies using DL reasoning to recognize these patterns.
With the Multimedia Metadata Ontology (M3O), we have developed a sophisticated model for representing among others the annotation, decomposition, and provenance of multimedia metadata. The goal of the M3O is to integrate the existing metadata standards and metadata formats rather than replacing them. To this end, the M3O provides a scaffold needed to represent multimedia metadata. Being an abstract model for multimedia metadata, it is not straightforward how to use and specialize the M3O for concrete application requirements and existing metadata formats and metadata standards. In this paper, we present a step-by-step alignment method describing how to integrate and leverage existing multimedia metadata standards and metadata formats in the M3O in order to use them in a concrete application. We demonstrate our approach by integrating three existing metadata models: the Core Ontology on Multimedia (COMM), which is a formalization of the multimedia metadata standard MPEG-7, the Ontology for Media Resource of the W3C, and the widely known industry standard EXIF for image metadata
