Matches in Ruben’s data for { ?s <http://schema.org/abstract> ?o }
- article-jws2018-ostrich abstract "When publishing Linked Open Datasets on the Web, most attention is typically directed to their latest version. Nevertheless, useful information is present in or between previous versions. In order to exploit this historical information in dataset analysis, we can maintain history in RDF archives. Existing approaches either require much storage space, or they expose an insufficiently expressive or efficient interface with respect to querying demands. In this article, we introduce an RDF archive indexing technique that is able to store datasets with a low storage overhead, by compressing consecutive versions and adding metadata for reducing lookup times. We introduce algorithms based on this technique for efficiently evaluating queries at a certain version, between any two versions, and for versions. Using the BEAR RDF archiving benchmark, we evaluate our implementation, called OSTRICH. Results show that OSTRICH introduces a new trade-off regarding storage space, ingestion time, and querying efficiency. By processing and storing more metadata during ingestion time, it significantly lowers the average lookup time for versioning queries. OSTRICH performs better for many smaller dataset versions than for few larger dataset versions. Furthermore, it enables efficient offsets in query result streams, which facilitates random access in results. Our storage technique reduces query evaluation time for versioned queries through a preprocessing step during ingestion, which only in some cases increases storage space when compared to other approaches. This allows data owners to store and query multiple versions of their dataset efficiently, lowering the barrier to historical dataset publication and analysis.".
- QuWeDa_2023_Link_Queue_Analysis_Final.pdf abstract "Link Traversal-based Query Processing (LTQP) is an integrated querying approach that allows the query engine to start with zero knowledge of the data to query and discover data sources on the fly. The query engine starts with some seed documents and dynamically discovers new data sources by dereferencing hyperlinks in previously ingested data. Given the dynamic nature of source discovery, query processing tends to be relatively slow. Optimization techniques exist, such as exploiting existing structural information, but they depend on a deep understanding of the link queue during LTQP. To this end, we investigate the evolution of the types of link sources in the link queue and introduce metrics that describe key link queue characteristics. This paper analyses the link queue to guide future work on LTQP query optimization approaches that exploit structural information within a Solid environment. We find that queries exhibit two different execution patterns, one where the link queue is primarily empty and the other where the link queue fills faster than the engine can process. Our results show that the link queue is not functioning optimally and that our current approach to link discovery is not sufficiently selective.".
- Revisiting_Link_Prioritization_for_Efficient_Traversal_in_Structured_Decentralized_Environments-camera-ready.pdf abstract "Decentralized environments distribute personal data across numerous small, independent data sources; a necessity driven by legal and socio-economic constraints that prevent the technologically more convenient central aggregation. Link Traversal-based Query Processing (LTQP) is a query technique that respects these constraints by iteratively discovering and accessing data sources while enabling fine-grained access control. Unfortunately, current LTQP implementations are slow due to limited prior knowledge of queried data and the high volume of HTTP requests required. Prioritizing data sources likely to lead to query-relevant data can improve query result arrival times. However, while link prioritization algorithms have been studied for Linked Open Data (LOD), their performance in structured decentralized environments remains untested. Evaluating this performance is essential to establish a baseline as a reference point for improving future implementations. We formally define the R3 metric to measure prioritization performance, extend it to continuous efficiency, and account for real-world scenarios. Furthermore, we provide modular and open-source implementations of the prioritization algorithms from the literature. Finally, using the R3 metric with existing metrics from the literature, we benchmark these link prioritization algorithms in a simulated Solid environment. In this paper, we report the benchmark results, provide a thorough analysis, and lessons learned for future work. We find that existing prioritization algorithms fail to improve performance in structured decentralized environments, with no non-oracle method outperforming the look-up order produced by a FIFO queue. We conclude that prioritization algorithms have little benefit in a structured decentralized environment, and recommend that research shift to pruning irrelevant links or improving the query plan.".
- article-ldtraversal-security-short abstract "The societal and economic consequences surrounding Big Data-driven platforms have increased the call for decentralized solutions. However, retrieving and querying data in more decentralized environments requires fundamentally different approaches, whose properties are not yet well understood. Link-Traversal-based Query Processing (LTQP) is a technique for querying over decentralized data networks, in which a client-side query engine discovers data by traversing links between documents. Since decentralized environments are potentially unsafe due to their non-centrally controlled nature, there is a need for client-side LTQP query engines to be resistant against security threats aimed at the query engine’s host machine or the query initiator’s personal data. As such, we have performed an analysis of potential security vulnerabilities of LTQP. This article provides an overview of security threats in related domains, which are used as inspiration for the identification of 10 LTQP security threats. This list of security threats forms a basis for future work in which mitigations for each of these threats need to be developed and tested for their effectiveness. With this work, we start filling the unknowns for enabling query execution over decentralized environments. Aside from future work on security, wider research will be needed to uncover missing building blocks for enabling true data decentralization.".
- article-quoted-triples-index abstract "The upcoming RDF 1.2 recommendation is scheduled to introduce the concept of quoted triples, which allows statements to be made about other statements. Since quoted triples enable new forms of data access in SPARQL 1.2, in the form of quoted triple patterns, there is a need for new indexing strategies that can efficiently handle these data access patterns. As such, we explore and evaluate different in-memory indexing approaches for quoted triples. In this paper, we investigate four indexing approaches, and evaluate their performance over an artificial dataset with custom triple pattern queries. Our findings show that the so-called indexed quoted triples dictionary vastly outperforms other approaches in terms of query execution time at the cost of increased storage size and ingestion time. Our work shows that indexing quoted triples in a dictionary separate from non-quoted RDF terms achieves good performance, and can be implemented using well-known indexing techniques into existing systems. Therefore, we illustrate that the addition of quoted triples into the RDF stack can be achieved in a performant manner.".
- Article-ESWC2024-DFDP abstract "Forms are key to bidirectional communication on the Web: without them, end-users would be unable to place online orders or file support tickets. Organizations often need multiple, highly similar forms, which currently require multiple implementations. Moreover, the data is tightly coupled to the application, restricting the end-user from reusing it with other applications, or storing the data somewhere else. Organizations and end-users have a need for a technique to create forms that are more controllable, reusable, and decentralized. To address this problem, we introduce the Declarative Form Description Pipeline (DFDP) that meets these requirements. DFDP achieves controllability through end-users’ editable declarative form descriptions. Reusability for organizations is ensured through descriptions of the form fields and associated actions. Finally, by leveraging a decentralized environment like Solid, the application is decoupled from the storage, preserving end-user control over their data. In this paper, we introduce and explain how such a declarative form description can be created and used without assumptions about the viewing environment or data storage. We show how separate applications can interoperate and be interchanged by using a description that contains details for form rendering and data submission decisions using a form, policy, and rule ontology. Furthermore, we prove how this approach solves the shortcomings of traditional Web forms. Our proposed pipeline enables organizations to save time by building similar forms without starting from scratch. Similarly, end-users can save time by letting machines prefill the form with existing data. Additionally, DFDP empowers end-users to be in control of the application they use to manage their data in a data store. User study results provide insights to further improve usability by providing automatic suggestions based on field labels entered".
- WhatsInAPod abstract "The Solid vision aims to make data independent of applications through technical specifications, which detail how to publish and consume permissioned data across multiple autonomous locations called “pods". The current document-centric interpretation of Solid, wherein a pod is solely a hierarchy of Linked Data documents, cannot fully realize this envisaged independence. Applications are left to define their own APIs within the Solid Protocol, which leads to fundamental interoperability problems and the need for associated workarounds. The broader longterm vision for Solid is confounded with the concrete HTTP interface to pods today, leading to a narrower solution space to address these core issues. We examine the mismatch between the vision and the prevalent document-centric interpretation, and propose a reconciliatory graph-centric interpretation wherein a pod is fundamentally a knowledge graph. In this article, we contrast the existing and proposed interpretations in terms of how they support the Solid vision. We argue that the knowledge-centric interpretation can improve pod access through different Web APIs that act as views in a database sense. We show that our zoomed-out interpretation provides improved opportunities for storage, publication, and querying of decentralized data in more flexible and sustainable ways. These insights are crucial to reduce the dependency of Solid apps on implicit API semantics and local assumptions about the shape and organization of data and the resulting performance. The suggested broader interpretation can guide Solid through its evolution into a heterogeneous yet interoperable ecosystem that accommodates a multitude of read/write data access patterns.".