Steffen Stadtmüller

RaDON -- Repair and Diagnosis in Ontology Networks

One of the major challenges in managing networked and dynamic ontologies is to handle inconsistencies in single ontologies, and inconsistencies introduced by integrating multiple distributed ontologies. Our RaDON system provides functionalities to repair and diagnose ontology networks by extending the capabilities of existing reasoners. The system integrates several new debugging and repairing algorithms, such as a relevance-directed algorithm to meet the various needs of the users.

Data-Fu: a language and an interpreter for interaction with read/write linked data

An increasing amount of applications build their functionality on the utilisation and manipulation of web resources. Consequently REST gains popularity with a resource-centric interaction architecture that draws its flexibility from links between resources. Linked Data offers a uniform data model for REST with self-descriptive resources that can be leveraged to avoid a manual ad-hoc development of web-based applications. For declaratively specifying interactions between web resources we introduce Data-Fu, a lightweight declarative rule language with state transition systems as formal grounding. Data-Fu enables the development of data-driven applications that facilitate the RESTful manipulation of read/write Linked Data resources. Furthermore, we describe an interpreter for Data-Fu as a general purpose engine that allows to perform described interactions with web resources by orders of magnitude faster than a comparable Linked Data processor.

On the diversity and availability of temporal information in linked open data

An increasing amount of data is published and consumed on the Web according to the Linked Data paradigm. In consideration of both publishers and consumers, the temporal dimension of data is important. In this paper we investigate the characterisation and availability of temporal information in Linked Data at large scale. Based on an abstract definition of temporal information we conduct experiments to evaluate the availability of such information using the data from the 2011 Billion Triple Challenge (BTC) dataset. Focusing in particular on the representation of temporal meta-information, i.e., temporal information associated with RDF statements and graphs, we investigate the approaches proposed in the literature, performing both a quantitative and a qualitative analysis and proposing guidelines for data consumers and publishers. Our experiments show that the amount of temporal information available in the LOD cloud is still very small; several different models have been used on different datasets, with a prevalence of approaches based on the annotation of RDF documents.

Survey of Semantic Description of REST APIs

The REST architectural style assumes that client and server form a contract with content negotiation, not only on the data format but implicitly also on the semantics of the communicated data, i.e., an agreement on how the data have to be interpreted [247]. In different application scenarios such an agreement requires vendor-specific content types for the individual services to convey the meaning of the communicated data. The idea behind vendor-specific content types is that service providers can reuse content types and service consumers can make use of specific processors for the individual content types. In practice however, we see that many RESTful APIs on the Web simply make use of standard non-specific content types, e.g., text/xml or application/json [150]. Since the agreement on the semantics is only implicit, programmers developing client applications have to manually gain a deep understanding of several APIs from multiple providers.

Querying the Global Cube: Integration of Multidimensional Datasets from the Web

National statistical indicators such as the Gross Domestic Product per Capita are published on the Web by various organisations such as Eurostat, the World Bank and the International Monetary Fund. Uniform access to such statistics will allow for elaborate analysis and visualisations. Though many datasets are also available as Linked Data, heterogeneities remain since publishers use several identifiers for common dimensions and differing levels of detail, units, and formulas. For queries over the Global Cube, i.e., the integration of available datasets modelled in the RDF Data Cube Vocabulary, we extend the well-known Drill-Across operation over data cubes to consider implicit overlaps between datasets in Linked Data. To evaluate more complex mappings we define the Convert-Cube operation over values from a single dataset. We generalise the two operations for arbitrary combinations of multiple datasets with the Merge-Cubes operation and show the feasibility of the analytical operations for integrating government statistics.

Accessing Information About Linked Data Vocabularies with vocab.cc

Linked Data vocabulary designers and application developers need means to easily identify relevant vocabularies, to allow them to reuse existing vocabularies and to develop applications making use of Linked Data. We describe a system that provides information about the popularity of classes and properties based on the Billion Triple Challenge data set. The information about classes and properties can be accessed via a web portal or via Linked API resources. We describe both the data analysis process and the architecture of the web portal.

SUMMA: A Common API for Linked Data Entity Summaries

Linked Data knowledge sources such as DBpedia, Freebase, and Wikidata currently offer large amounts of factual data. As the amount of information that can be grasped by users is limited, data summaries are needed. If a summary relates to a specific entity we refer to it as entity summarization. Unfortunately, in many settings, the summaries of entities are tightly bound to user interfaces. This practice poses problems for efficient and objective comparison and evaluation. In this paper we focus on the question of how to make summaries exchangeable between multiple interfaces and multiple summarization services in order to facilitate evaluation and testing. We introduce SUMMA, an API definition that enables to decouple generation and presentation of summaries. It enables multiple consumers to retrieve summaries from multiple providers in a unified and lightweight way.

Integrating highly dynamic RESTful linked data APIs in a virtual reality environment.

We demonstrate a Virtual Reality information system that shows the applicability of REST in highly dynamic environments as well as the advantages of Linked Data for on-the-fly data integration. We integrate a motion detection sensor application to remote control an avatar in the Virtual Reality. In the Virtual Reality, information about the user is integrated and visualised. Moreover, the user can interact with the visualised information.

Scalable discovery of Linked APIs

A number of approaches bring together the principles and technologies which define Linked Data with those of RESTful services. Services and APIs are thus enriched by, and contribute to, the Web of Data. These approaches, referred to as Linked APIs, use graphic patterns as an intuitive way to describe input and output expectations. To enable agents to discover Linked APIs we propose metrics tailored for a scalable discovery system to measure the degree service descriptions match service templates formulated by an agent. The metrics are based on the used vocabularies in the service descriptions and templates as well as on the containment relation of the employed graph patterns. We introduce a cloud-based implementation of our system in a distributed environment to further address scalability. The results of our evaluation show the positive effects of a distributed computation strategy on the performance of our system.

Composition of linked data-based RESTful services

We address the problem of developing a scaleable composition framework for Linked Data-based services, that retains the advantages of the loose coupling fostered by REST.