Incompleteness-aware programming with RDF data

Scheglmann, Stefan; Groener, Gerd; Staab, Steffen; Lämmel, Ralf

doi:10.1145/2429376.2429380

Cited by 7 publications

(7 citation statements)

References 10 publications

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“…Property-based data access and its suitability for programming the Semantic Web has recently been discussed in [7,19]. Challenges and open questions concerning a property based approach are discussed in these papers.…”

Section: Related Workmentioning

confidence: 99%

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ProSWIP: Property-Based Data Access for Semantic Web Interactive Programming

Homoceanu

Wille

Balke

2013

Advanced Information Systems Engineering

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The Semantic Web has matured from a mere theoretical vision to a variety of ready-to-use linked open data sources currently available on the Web. Still, with respect to application development, the Web community is just starting to develop new paradigms in which data as the main driver of applications is promoted to first class status. Relying on properties of resources as an indicator for the type, property-based typing is such a paradigm. In this paper, we inspect the feasibility of property-based typing for accessing data from the linked open data cloud. Problems in terms of transparency and quality of the selected data were noticeable. To alleviate these problems, we developed an iterative approach that builds on human feedback.

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Section: Related Workmentioning

confidence: 99%

“…We believe that a property-based data access model as recently sketched in [6,7] is more suitable for programming with semantic data. The type information for such a programming approach is given by properties: A type is defined by a set of required properties, and every entity with at least those properties is part of that type.…”

Section: Introductionmentioning

confidence: 99%

ProSWIP: Property-Based Data Access for Semantic Web Interactive Programming

Homoceanu

Wille

Balke

2013

Advanced Information Systems Engineering

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“…The examples above describe users looking for data sources providing actors or people and their relationships. Such knowledge is also of relevance for software engineers who want to develop applications making use of specific types of Linked Data [12] or Linked Data engineers who publishing data on the cloud and wanting to interlink it with other data sources already published as Linked Data [11]. Summarized, in order to answer these questions, we need to capture the knowledge of where on the LOD cloud which kind of data is located.…”

Section: Introductionmentioning

confidence: 99%

LODatio

Gottron

Scherp

Krayer

et al. 2013

Proceedings of the Seventh International Conference on Knowledge Capture

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The Linked Open Data (LOD) cloud provides a vast amount of heterogeneous data, distributed over numerous data sources. This makes it difficult to find those data sources in the cloud which are relevant for a given information need. Existing search engines for the Semantic Web focus on instance-oriented information needs, i. e., searching for specific RDF instances or literals and exploring the search results. However, they do not address the question of finding linked data sources relevant to a schema-oriented information need, i. e., queries based on triple patterns relating to a specific combination of RDF types and/or properties. In this paper, we present the semantic search system LODatio leveraging a schema-level index for finding sources of Linked Data relevant to a schema-oriented information need. Beyond its capability to retrieve relevant data sources, LODatio actively supports the user in his schema-oriented search tasks. To this end, it provides ranked result lists of relevant data sources together with example snippets and an estimation of the result set size. Furthermore, LODatio provides support for novel features in semantic search such as recommending alternative queries in order to refine or broaden the result set.

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“…The schema structure of the graph data on the LOD cloud is of importance also in other settings: consumption of Linked Data in applications requires for a programmable interface to the LOD cloud. Such interfaces should represent the structure of certain types of data in a relatively stable fashion while at the same time being capable of handling the flexibility of Linked Data [27]. To continue the above example, an interface to Linked Data about scientists should be based on typical properties scientists exhibit on the cloud and should consider the properties that link scientist to other objects such as their publications or institutions.…”

mentioning

confidence: 99%

“…However, we also have concrete applications for using the obtained insights in mind. These possible applications range from query recommendations when searching for LOD sources [14], providing programmatic access to the LOD cloud [27], and supporting the data engineer when modeling data using LOD vocabularies [26]. We extend the analyses conducted in earlier studies in various different ways: Existing works only consider one part of the schema information and ignore the other.…”

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confidence: 99%

Analysis of schema structures in the Linked Open Data graph based on unique subject URIs, pay-level domains, and vocabulary usage

Gottron

Knauf

Scherp

2014

Distrib Parallel Databases

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The Linked Open Data (LOD) graph represents a web-scale distributed knowledge graph interlinking information about entities across various domains. A core concept is the lack of pre-defined schema which actually allows for flexibly modelling data from all kinds of domains. However, Linked Data does exhibit schema information in a twofold way: by explicitly attaching RDF types to the entities and implicitly by using domain-specific properties to describe the entities. In this paper, we present and apply different techniques for investigating the schematic information encoded in the LOD graph at different levels of granularity. We investigate different information theoretic properties of so-called Unique Subject URIs (USUs) and measure the correlation between the properties and types that can be observed for USUs on a large-scale semantic graph data set. Our analysis provides insights into the information encoded in the different schema characteristics. Two major findings are that implicit schema information is far more discriminative and that applications involving schema information based on either types or properties alone will only capture

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Incompleteness-aware programming with RDF data

Cited by 7 publications

References 10 publications

ProSWIP: Property-Based Data Access for Semantic Web Interactive Programming

ProSWIP: Property-Based Data Access for Semantic Web Interactive Programming

LODatio

Analysis of schema structures in the Linked Open Data graph based on unique subject URIs, pay-level domains, and vocabulary usage

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