arXiv subjects

Olaf Hartig

Publications and source records attributed to Olaf Hartig.

At least 19 recordsLinked to original sources

arXiv2026

Query-Specific Pruning of RML Mappings (Extended Version)

Current approaches for knowledge graph construction with RML focus on full RDF graph materialization without considering user queries, which is inefficient in dynamic query environments where often only a specific subset of the full graph is needed to answer a given query. This paper introduces an approach to prune RML mappings such that the resulting partially-materialized graph is still sufficient to answer a given SPARQL query completely. By evaluating the approach based on a well-know RML materialization benchmark, we show that such pruning significantly reduces both the materialization time and the size of the produced graph, while also noticeably reducing querying time

cs.DB↗

arXiv2025

Poseidon: A OneGraph Engine

We present the Poseidon engine behind the Neptune Analytics graph database service. Customers interact with Poseidon using the declarative openCypher query language, which enables requests that seamlessly combine traditional querying paradigms (such as graph pattern matching, variable length paths, aggregation) with algorithm invocations and has been syntactically extended to facilitate OneGraph interoperability, such as the disambiguation between globally unique IRIs (as exposed via RDF) vs. local identifiers (as encountered in LPG data). Poseidon supports a broad range of graph workloads, from simple transactions, to top-k beam search algorithms on dynamic graphs, to whole graph analytics requiring multiple full passes over the data. For example, real-time fraud detection, like many other use cases, needs to reflect current committed state of the dynamic graph. If a users cell phone is compromised, then all newer actions by that user become immediately suspect. To address such dynamic graph use cases, Poseidon combines state-of-the-art transaction processing with novel graph data indexing, including lock-free maintenance of adjacency lists, secondary succinct indices, partitioned heaps for data tuple storage with uniform placement, and innovative statistics for cost-based query optimization. The Poseidon engine uses a logical log for durability, enabling rapid evolution of in-memory data structures. Bulk data loads achieve more than 10 million property values per second on many data sets while simple transactions can execute in under 20ms against the storage engine.

cs.DB↗

arXiv2025

An Algebraic Foundation for Knowledge Graph Construction (Extended Version)

Although they exist since more than ten years already, have attracted diverse implementations, and have been used successfully in a significant number of applications, declarative mapping languages for constructing knowledge graphs from heterogeneous types of data sources still lack a solid formal foundation. This makes it impossible to introduce implementation and optimization techniques that are provably correct and, in fact, has led to discrepancies between different implementations. Moreover, it precludes studying fundamental properties of different languages (e.g., expressive power). To address this gap, this paper introduces a language-agnostic algebra for capturing mapping definitions. As further contributions, we show that the popular mapping language RML can be translated into our algebra (by which we also provide a formal definition of the semantics of RML) and we prove several algebraic rewriting rules that can be used to optimize mapping plans based on our algebra.

cs.DB↗

arXiv2025

Towards Computer-Using Personal Agents

Computer-Using Agents (CUA) enable users to automate increasingly-complex tasks using graphical interfaces such as browsers. As many potential tasks require personal data, we propose Computer-Using Personal Agents (CUPAs) that have access to an external repository of the user's personal data. Compared with CUAs, CUPAs offer users better control of their personal data, the potential to automate more tasks involving personal data, better interoperability with external sources of data, and better capabilities to coordinate with other CUPAs in order to solve collaborative tasks involving the personal data of multiple users.

cs.HC↗

arXiv2024

Transforming Object-Centric Event Logs to Temporal Event Knowledge Graphs (Extended Version)

Event logs play a fundamental role in enabling data-driven business process analysis. Traditionally, these logs track events related to a single object, known as the case, limiting the scope of analysis. Recent advancements, such as Object-Centric Event Logs (OCEL) and Event Knowledge Graphs (EKG), capture better how events relate to multiple objects. However, attributes of objects can change over time, which was not initially considered in OCEL or EKG. While OCEL 2.0 has addressed some of these limitations, there remains a research gap concerning how attribute changes should be accommodated in EKG and how OCEL 2.0 logs can be transformed into EKG. This paper fills this gap by introducing Temporal Event Knowledge Graphs (tEKG) and defining an algorithm to convert an OCEL 2.0 log to a tEKG.

cs.DB↗

arXiv2022

Assessing the Solid Protocol in Relation to Security & Privacy Obligations

The Solid specification aims to empower data subjects by giving them direct access control over their data across multiple applications. As governments are manifesting their interest in this framework for citizen empowerment and e-government services, security and privacy represent pivotal issues to be addressed. By analyzing the relevant legislation, notably GDPR, and international standards, namely ISO/IEC 27001:2011 and 15408, we formulate the primary security and privacy requirements for such a framework. Furthermore, we survey the current Solid protocol specifications regarding how they cover the highlighted requirements, and draw attention to potential gaps between the specifications and requirements. We also point out the contribution of recent academic work presenting novel approaches to increase the security and privacy degree provided by the Solid project. This paper has a twofold contribution to improve user awareness of how Solid can help protect their data and to present possible future research lines on Solid security and privacy enhancements.

cs.CR↗

arXiv2022

LinGBM: A Performance Benchmark for Approaches to Build GraphQL Servers (Extended Version)

GraphQL is a popular new approach to build Web APIs that enable clients to retrieve exactly the data they need. Given the growing number of tools and techniques for building GraphQL servers, there is an increasing need for comparing how particular approaches or techniques affect the performance of a GraphQL server. To this end, we present LinGBM, a GraphQL performance benchmark to experimentally study the performance achieved by various approaches for creating a GraphQL server. In this article, we discuss the design considerations of the benchmark, describe its main components (data schema; query templates; performance metrics), and analyze the benchmark in terms of statistical properties that are relevant for defining concrete experiments. Thereafter, we present experimental results obtained by applying the benchmark in three different use cases, which demonstrates the broad applicability of LinGBM.

cs.DB↗

arXiv2021

Foundations of an Alternative Approach to Reification in RDF

This document defines extensions of the RDF data model and of the SPARQL query language that capture an alternative approach to represent statement-level metadata. While this alternative approach is backwards compatible with RDF reification as defined by the RDF standard, the approach aims to address usability and data management shortcomings of RDF reification. One of the great advantages of the proposed approach is that it clarifies a means to (i) understand sparse matrices, the property graph model, hypergraphs, and other data structures with an emphasis on link attributes, (ii) map such data onto RDF, and (iii) query such data using SPARQL. Further, the proposal greatly expands both the freedom that database designers enjoy when creating physical indexing schemes and query plans for graph data annotated with link attributes and the interoperability of those database solutions.

cs.DB↗

arXiv2020

The Future is Big Graphs! A Community View on Graph Processing Systems

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?

cs.DC↗

arXiv2020

FedQPL: A Language for Logical Query Plans over Heterogeneous Federations of RDF Data Sources (Extended Version)

Federations of RDF data sources provide great potential when queried for answers and insights that cannot be obtained from one data source alone. A challenge for planning the execution of queries over such a federation is that the federation may be heterogeneous in terms of the types of data access interfaces provided by the federation members. This challenge has not received much attention in the literature. This paper provides a solid formal foundation for future approaches that aim to address this challenge. Our main conceptual contribution is a formal language for representing query execution plans; additionally, we identify a fragment of this language that can be used to capture the result of selecting relevant data sources for different parts of a given query. As technical contributions, we show that this fragment is more expressive than what is supported by existing source selection approaches, which effectively highlights an inherent limitation of these approaches. Moreover, we show that the source selection problem is NP-hard and in $Σ_2^\mathrm{P}$, and we provide a comprehensive set of rewriting rules that can be used as a basis for query optimization.

cs.DB↗

arXiv2016

brTPF: Bindings-Restricted Triple Pattern Fragments (Extended Preprint)

The Triple Pattern Fragment (TPF) interface is a recent proposal for reducing server load in Web-based approaches to execute SPARQL queries over public RDF datasets. The price for less overloaded servers is a higher client-side load and a substantial increase in network load (in terms of both the number of HTTP requests and data transfer). In this paper, we propose a slightly extended interface that allows clients to attach intermediate results to triple pattern requests. The response to such a request is expected to contain triples from the underlying dataset that do not only match the given triple pattern (as in the case of TPF), but that are guaranteed to contribute in a join with the given intermediate result. Our hypothesis is that a distributed query execution using this extended interface can reduce the network load (in comparison to a pure TPF-based query execution) without reducing the overall throughput of the client-server system significantly. Our main contribution in this paper is twofold: we empirically verify the hypothesis and provide an extensive experimental comparison of our proposal and TPF.

cs.DB↗

arXiv2016

Scheduling Refresh Queries for Keeping Results from a SPARQL Endpoint Up-to-Date (Extended Version)

Many datasets change over time. As a consequence, long-running applications that cache and repeatedly use query results obtained from a SPARQL endpoint may resubmit the queries regularly to ensure up-to-dateness of the results. While this approach may be feasible if the number of such regular refresh queries is manageable, with an increasing number of applications adopting this approach, the SPARQL endpoint may become overloaded with such refresh queries. A more scalable approach would be to use a middle-ware component at which the applications register their queries and get notified with updated query results once the results have changed. Then, this middle-ware can schedule the repeated execution of the refresh queries without overloading the endpoint. In this paper, we study the problem of scheduling refresh queries for a large number of registered queries by assuming an overload-avoiding upper bound on the length of a regular time slot available for testing refresh queries. We investigate a variety of scheduling strategies and compare them experimentally in terms of time slots needed before they recognize changes and number of changes that they miss.

cs.DB↗

arXiv2016

Walking without a Map: Optimizing Response Times of Traversal-Based Linked Data Queries (Extended Version)

The emergence of Linked Data on the WWW has spawned research interest in an online execution of declarative queries over this data. A particularly interesting approach is traversal-based query execution which fetches data by traversing data links and, thus, is able to make use of up-to-date data from initially unknown data sources. The downside of this approach is the delay before the query engine completes a query execution. In this paper, we address this problem by proposing an approach to return as many elements of the result set as soon as possible. The basis of this approach is a traversal strategy that aims to fetch result-relevant data as early as possible. The challenge for such a strategy is that the query engine does not know a priori which of the data sources that will be discovered during the query execution contain result-relevant data. We introduce 16 different traversal approaches and experimentally study their impact on response times. Our experiments show that some of the approaches can achieve significant improvements over the baseline of looking up URIs on a first-come, first-served basis. Additionally, we verify the importance of these approaches by showing that typical query optimization techniques that focus solely on the process of constructing the query result cannot have any significant impact on the response times of traversal-based query executions.

cs.DB↗

arXiv2015

LDQL: A Query Language for the Web of Linked Data (Extended Version)

The Web of Linked Data is composed of tons of RDF documents interlinked to each other forming a huge repository of distributed semantic data. Effectively querying this distributed data source is an important open problem in the Semantic Web area. In this paper, we propose LDQL, a declarative language to query Linked Data on the Web. One of the novelties of LDQL is that it expresses separately (i) patterns that describe the expected query result, and (ii) Web navigation paths that select the data sources to be used for computing the result. We present a formal syntax and semantics, prove equivalence rules, and study the expressiveness of the language. In particular, we show that LDQL is strictly more expressive than the query formalisms that have been proposed previously for Linked Data on the Web. The high expressiveness allows LDQL to define queries for which a complete execution is not computationally feasible over the Web. We formally study this issue and provide a syntactic sufficient condition to avoid this problem; queries satisfying this condition are ensured to have a procedure to be effectively evaluated over the Web of Linked Data.

cs.DB↗

arXiv2015

A Context-Based Semantics for SPARQL Property Paths over the Web (Extended Version)

As of today, there exists no standard language for querying Linked Data on the Web, where navigation across distributed data sources is a key feature. A natural candidate seems to be SPARQL, which recently has been enhanced with navigational capabilities thanks to the introduction of property paths (PPs). However, the semantics of SPARQL restricts the scope of navigation via PPs to single RDF graphs. This restriction limits the applicability of PPs on the Web. To fill this gap, in this paper we provide formal foundations for evaluating PPs on the Web, thus contributing to the definition of a query language for Linked Data. In particular, we introduce a query semantics for PPs that couples navigation at the data level with navigation on the Web graph. Given this semantics we find that for some PP-based SPARQL queries a complete evaluation on the Web is not feasible. To enable systems to identify queries that can be evaluated completely, we establish a decidable syntactic property of such queries.

cs.DB↗

arXiv2014

Reconciliation of RDF* and Property Graphs

Both the notion of Property Graphs (PG) and the Resource Description Framework (RDF) are commonly used models for representing graph-shaped data. While there exist some system-specific solutions to convert data from one model to the other, these solutions are not entirely compatible with one another and none of them appears to be based on a formal foundation. In fact, for the PG model, there does not even exist a commonly agreed-upon formal definition. The aim of this document is to reconcile both models formally. To this end, the document proposes a formalization of the PG model and introduces well-defined transformations between PGs and RDF. As a result, the document provides a basis for the following two innovations: On one hand, by implementing the RDF-to-PG transformations defined in this document, PG-based systems can enable their users to load RDF data and make it accessible in a compatible, system-independent manner using, e.g., the graph traversal language Gremlin or the declarative graph query language Cypher. On the other hand, the PG-to-RDF transformation in this document enables RDF data management systems to support compatible, system-independent queries over the content of Property Graphs by using the standard RDF query language SPARQL. Additionally, this document represents a foundation for systematic research on relationships between the two models and between their query languages.

cs.DB↗

arXiv2012

Foundations of Traversal Based Query Execution over Linked Data (Extended Version)

Query execution over the Web of Linked Data has attracted much attention recently. A particularly interesting approach is link traversal based query execution which proposes to integrate the traversal of data links into the construction of query results. Hence -in contrast to traditional query execution paradigms- this approach does not assume a fixed set of relevant data sources beforehand; instead, it discovers data on the fly and, thus, enables applications to tap the full potential of the Web. While several authors study possibilities to implement the idea of link traversal based query execution and to optimize query execution in this context, no work exists that discusses the theoretical foundations of the approach in general. Our paper fills this gap. We introduce a well-defined semantics for queries that may be executed using the link traversal based approach. Based on this semantics we formally analyze properties of such queries. In particular, we study the computability of queries as well as the implications of querying a potentially infinite Web of Linked Data. Our results show that query computation in general is not guaranteed to terminate and that for any given query it is undecidable whether the execution terminates. Furthermore, we define an abstract execution model that captures the integration of link traversal into the query execution process. Based on this model we prove the soundness and completeness of link traversal based query execution and analyze an existing implementation approach..

cs.DB↗

arXiv2012

SPARQL for a Web of Linked Data: Semantics and Computability (Extended Version)

The World Wide Web currently evolves into a Web of Linked Data where content providers publish and link data as they have done with hypertext for the last 20 years. While the declarative query language SPARQL is the de facto for querying a-priory defined sets of data from the Web, no language exists for querying the Web of Linked Data itself. However, it seems natural to ask whether SPARQL is also suitable for such a purpose. In this paper we formally investigate the applicability of SPARQL as a query language for Linked Data on the Web. In particular, we study two query models: 1) a full-Web semantics where the scope of a query is the complete set of Linked Data on the Web and 2) a family of reachability-based semantics which restrict the scope to data that is reachable by traversing certain data links. For both models we discuss properties such as monotonicity and computability as well as the implications of querying a Web that is infinitely large due to data generating servers.

cs.DB↗