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In this system paper we describe metaphactory, a platform for building knowledge graph management applications. The metaphactory platform aims at supporting different categories of knowledge graph users within the organization by realizing relevant services for knowledge graph data management tasks, providing a rich and customizable user interface, and enabling rapid building of use case-specific applications. The paper discusses how the platform architecture design built on open standards enables its reusability in various application domains and use cases as well as facilitates integration of the knowledge graph with other parts of the organizational data and software infrastructure. We highlight the capabilities of the platform by describing its usage in four different knowledge graph application domains and share the lessons learnt from the practical experience of building knowledge graph applications in the enterprise context.

Abstract. The Internet of Things aims to connect networked information systems and real-world business processes. Technologies, such as barcodes, radio transponders (RFID) and wireless sensor networks, which are directly attached to physical items and assets transform objects into Smart Items. These Smart Items deliver the data to realize the accurate real-time representation of 'things' within the information systems. In particular for supply chain applications this allows monitoring and control throughout the entire process involving suppliers, customers and shippers. However, the problem remains what Smart Item technology should be favored in a concrete application in order to implement the Internet of Things most suitably. This paper analyzes different types of Smart Item technology within a typical logistics scenario. We develop a quantification cost model for Smart Items in order to evaluate the different views of the supplier, customer and shipper. Finally, we conclude a criterion, which supports decision makers to estimate the benefit of the Smart Item. Our approach is justified using performance numbers from a supply chain case with perishable goods. Further, we investigate the model through a selection of model parameters, e.g. the technology price, fix costs and utility, and illustrate them in a second use case. We also provide guidelines how to estimate parameters for use in our cost formula to ensure practical applicability of the model. The overall results reveal that the model is highly adaptable to various use cases and practical.

An increasing amount of structured data on the Web has attracted industry attention and renewed research interest in what is collectively referred to as semantic search. These solutions exploit the explicit semantics captured in structured data such as RDF for enhancing document representation and retrieval, or for finding answers by directly searching over the data. These data have been used for different tasks and a wide range of corresponding semantic search solutions have been proposed in the past. However, it has been widely recognized that a standardized setting to evaluate and analyze the current state-of-the-art in semantic search is needed to monitor and stimulate further progress in the field. In this paper, we present an evaluation framework for semantic search, analyze the framework with regard to repeatability and reliability, and report on our experiences on applying it in the Semantic Search Challenge 2010 and 2011.

Abstract. Semantic wikis extend wiki platforms with the ability to represent structured information in a machine-processable way. On top of the structured information in the wiki, novel ways to search, browse, and present the wiki content become possible. However, while powerful query languages offer new opportunities for semantic search, the syntax of formal query languages is not adequate for end users. In this work we present an approach to semantic search that combines the expressiveness and capabilities of structured queries with the simplicity of keyword interfaces and faceted search. Users articulate their information need in keywords, which are translated into structured, conjunctive queries. This translation may result in multiple possible interpretations of the information need, which can then be selected and further refined by the user via facets. We have implemented this approach to semantic search as an extension to Semantic MediaWiki. The results of a user study in the SMW-based community portal semanticweb.org show the efficiency and effectiveness of the approach as well as its ease of use.