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Jan Hidders

Publications and source records attributed to Jan Hidders.

16 recordsLinked to original sources

sheval: An RDF data shapes evaluation tool and test-suite for recursive shapes

Two different languages have been developed to validate RDF data based on the concept of a shape: ShEx and SHACL. In each language it is possible to define a shape that refers to itself, which is called a recursive shape. While in the case of ShEx, the semantics of recursive shapes is well defined and is part of the specification, in the case of SHACL, the semantics of recursive shapes is left to the implementation of the different SHACL engines. Consequently, the different SHACL engines show different behaviours when confronted with recursive shapes. In this paper we present sheval: an evaluation framework consisting of a tool and a test suite that can be used to compare the behaviour of different shapes technologies when confronted with recursive definitions. The tool has been used to evaluate and understand the differences in the implementation of recursive shapes in ShEx and SHACL. It provides a framework for testing and comparing the behaviour of different shape engines, helping to identify inconsistencies and potential issues, and providing a basis for further research and development in the field of shape-based validation of RDF data.

cs.DB

Common Foundations for Recursive Shape Languages

As schema languages for RDF data become more mature, we are seeing efforts to extend them with recursive semantics, applying diverse ideas from logic programming and description logics. While ShEx has an official recursive semantics based on greatest fixpoints (GFP), the discussion for SHACL is ongoing and seems to be converging towards least fixpoints (LFP). A practical study we perform shows that, indeed, ShEx validators implement GFP, whereas SHACL validators are more heterogeneous. This situation creates tension between ShEx and SHACL, as their semantic commitments appear to diverge, potentially undermining interoperability and predictability. We aim to clarify this design space by comparing the main semantic options in a principled yet accessible way, hoping to engage both theoreticians and practitioners, especially those involved in developing tools and standards. We present a unifying formal semantics that treats LFP, GFP, and supported model semantics (SMS), clarifying their relationships and highlighting a duality between LFP and GFP on stratified fragments. Next, we investigate to which extent the directions taken by SHACL and ShEx are compatible. We show that, although ShEx and SHACL seem to be going in different directions, they include large fragments with identical expressive power. Moreover, there is a strong correspondence between these fragments through the aforementioned principle of duality. Finally, we present a complete picture of the data and combined complexity of ShEx and SHACL validation under LFP, GFP, and SMS, showing that SMS comes at a higher computational cost under standard complexity-theoretic assumptions.

cs.LO

On the generic information capacity of relational schemas with a single binary relation

We consider database schemas consisting of a single binary relation, with key constraints and inclusion dependencies. Over this space of 20 schemas, we completely characterize when one schema is generically dominated by another schema. Generic dominance, a classical notion for measuring information capacity, expresses that every instance of a schema can be uniquely represented in the dominating schema, through application of a deterministic, generic data transformation. Our investigation is motivated both by current interest in schema design for graph databases, as well as by intrinsic scientific interest. We also consider the ternary case, but without inclusion dependencies, and discuss how the notions change in the presence of object identifiers.

cs.DB

The KG-ER Conceptual Schema Language

We propose KG-ER, a conceptual schema language for knowledge graphs that describes the structure of knowledge graphs independently of their representation (relational databases, property graphs, RDF) while helping to capture the semantics of the information stored in a knowledge graph.

cs.DB

The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space

Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements, including the need for a concise query language and graph-aware query optimization techniques. The goal of the Linked Data Benchmark Council (LDBC) is to design a set of standard benchmarks that capture representative categories of graph data management problems, making the performance of systems comparable and facilitating competition among vendors. LDBC also conducts research on graph schemas and graph query languages. This paper introduces the LDBC organization and its work over the last decade.

cs.DB

Static Analysis of Graph Database Transformations

We investigate graph transformations, defined using Datalog-like rules based on acyclic conjunctive two-way regular path queries (acyclic C2RPQs), and we study two fundamental static analysis problems: type checking and equivalence of transformations in the presence of graph schemas. Additionally, we investigate the problem of target schema elicitation, which aims to construct a schema that closely captures all outputs of a transformation over graphs conforming to the input schema. We show all these problems are in EXPTIME by reducing them to C2RPQ containment modulo schema; we also provide matching lower bounds. We use cycle reversing to reduce query containment to the problem of unrestricted (finite or infinite) satisfiability of C2RPQs modulo a theory expressed in a description logic.

cs.DB

PG-Schema: Schemas for Property Graphs

Property graphs have reached a high level of maturity, witnessed by multiple robust graph database systems as well as the ongoing ISO standardization effort aiming at creating a new standard Graph Query Language (GQL). Yet, despite documented demand, schema support is limited both in existing systems and in the first version of the GQL Standard. It is anticipated that the second version of the GQL Standard will include a rich DDL. Aiming to inspire the development of GQL and enhance the capabilities of graph database systems, we propose PG-Schema, a simple yet powerful formalism for specifying property graph schemas. It features PG-Types with flexible type definitions supporting multi-inheritance, as well as expressive constraints based on the recently proposed PG-Keys formalism. We provide the formal syntax and semantics of PG-Schema, which meet principled design requirements grounded in contemporary property graph management scenarios, and offer a detailed comparison of its features with those of existing schema languages and graph database systems.

cs.DB

Expressiveness within Sequence Datalog

Motivated by old and new applications, we investigate Datalog as a language for sequence databases. We reconsider classical features of Datalog programs, such as negation, recursion, intermediate predicates, and relations of higher arities. We also consider new features that are useful for sequences, notably, equations between path expressions, and "packing". Our goal is to clarify the relative expressiveness of all these different features, in the context of sequences. Towards our goal, we establish a number of redundancy and primitivity results, showing that certain features can, or cannot, be expressed in terms of other features. These results paint a complete picture of the expressiveness relationships among all possible Sequence Datalog fragments that can be formed using the six features that we consider.

cs.DB

Threshold Queries in Theory and in the Wild

Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. In this paper, we present a deep theoretical analysis of threshold query evaluation and show that thresholds can be used to significantly improve the asymptotic bounds of state-of-the-art query evaluation algorithms. We also empirically show that threshold queries are significant in practice. In surprising contrast to conventional wisdom, we found important scenarios in real-world data sets in which users are interested in computing the results of queries up to a certain threshold, independent of a ranking function that orders the query results by importance.

cs.DB

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

J-Logic: a Logic for Querying JSON

We propose a logical framework, based on Datalog, to study the foundations of querying JSON data. The main feature of our approach, which we call J-Logic, is the emphasis on paths. Paths are sequences of keys and are used to access the tree structure of nested JSON objects. J-Logic also features ``packing'' as a means to generate a new key from a path or subpath. J-Logic with recursion is computationally complete, but many queries can be expressed without recursion, such as deep equality. We give a necessary condition for queries to be expressible without recursion. Most of our results focus on the deterministic nature of JSON objects as partial functions from keys to values. Predicates defined by J-Logic programs may not properly describe objects, however. Nevertheless we show that every object-to-object transformation in J-Logic can be defined using only objects in intermediate results. Moreover we show that it is decidable whether a positive, nonrecursive J-Logic program always returns an object when given objects as inputs. Regarding packing, we show that packing is unnecessary if the output does not require new keys. Finally, we show the decidability of query containment for positive, nonrecursive J-Logic programs.

cs.DB

Finding AND-OR Hierarchies in Workflow Nets

This paper presents the notion of AND-OR reduction, which reduces a WF net to a smaller net by iteratively contracting certain well-formed subnets into single nodes until no more such contractions are possible. This reduction can reveal the hierarchical structure of a WF net, and since it preserves certain semantical properties such as soundness, it can help with analysing and understanding why a WF net is sound or not. The reduction can also be used to verify if a WF net is an AND-OR net. This class of WF nets was introduced in earlier work, and arguably describes nets that follow good hierarchical design principles. It is shown that the AND-OR reduction is confluent up to isomorphism, which means that despite the inherent non-determinism that comes from the choice of subnets that are contracted, the final result of the reduction is always the same up to the choice of the identity of the nodes. Based on this result, a polynomial-time algorithm is presented that computes this unique result of the AND-OR reduction. Finally, it is shown how this algorithm can be used to verify if a WF net is an AND-OR net.

cs.LO

External memory bisimulation reduction of big graphs

In this paper, we present, to our knowledge, the first known I/O efficient solutions for computing the k-bisimulation partition of a massive directed graph, and performing maintenance of such a partition upon updates to the underlying graph. Ubiquitous in the theory and application of graph data, bisimulation is a robust notion of node equivalence which intuitively groups together nodes in a graph which share fundamental structural features. k-bisimulation is the standard variant of bisimulation where the topological features of nodes are only considered within a local neighborhood of radius $k\geqslant 0$. The I/O cost of our partition construction algorithm is bounded by $O(k\cdot \mathit{sort}(|\et|) + k\cdot scan(|\nt|) + \mathit{sort}(|\nt|))$, while our maintenance algorithms are bounded by $O(k\cdot \mathit{sort}(|\et|) + k\cdot \mathit{sort}(|\nt|))$. The space complexity bounds are $O(|\nt|+|\et|)$ and $O(k\cdot|\nt|+k\cdot|\et|)$, resp. Here, $|\et|$ and $|\nt|$ are the number of disk pages occupied by the input graph's edge set and node set, resp., and $\mathit{sort}(n)$ and $\mathit{scan}(n)$ are the cost of sorting and scanning, resp., a file occupying $n$ pages in external memory. Empirical analysis on a variety of massive real-world and synthetic graph datasets shows that our algorithms perform efficiently in practice, scaling gracefully as graphs grow in size.

cs.DB

On Generating *-Sound Nets with Substitution

We present a method for hierarchically generating sound workflow nets by substitution of nets with multiple inputs and outputs. We show that this method is correct and generalizes the class of nets generated by other hierarchical approaches. The method involves a new notion of soundness which is preserved by the generalized type of substitution that is presented in this paper. We show that this notion is better suited than *-soundness for use with the presented type of generalized substitution, since {*}-soundness is not preserved by it. It is moreover shown that it is in some sense the optimal notion of soundness for the purpose of generating sound nets by the presented type of substitution.

cs.FL

SERIMI - Resource Description Similarity, RDF Instance Matching and Interlinking

The interlinking of datasets published in the Linked Data Cloud is a challenging problem and a key factor for the success of the Semantic Web. Manual rule-based methods are the most effective solution for the problem, but they require skilled human data publishers going through a laborious, error prone and time-consuming process for manually describing rules mapping instances between two datasets. Thus, an automatic approach for solving this problem is more than welcome. In this paper, we propose a novel interlinking method, SERIMI, for solving this problem automatically. SERIMI matches instances between a source and a target datasets, without prior knowledge of the data, domain or schema of these datasets. Experiments conducted with benchmark collections demonstrate that our approach considerably outperforms state-of-the-art automatic approaches for solving the interlinking problem on the Linked Data Cloud.

cs.DB

Instance-Independent View Serializability for Semistructured Databases

Semistructured databases require tailor-made concurrency control mechanisms since traditional solutions for the relational model have been shown to be inadequate. Such mechanisms need to take full advantage of the hierarchical structure of semistructured data, for instance allowing concurrent updates of subtrees of, or even individual elements in, XML documents. We present an approach for concurrency control which is document-independent in the sense that two schedules of semistructured transactions are considered equivalent if they are equivalent on all possible documents. We prove that it is decidable in polynomial time whether two given schedules in this framework are equivalent. This also solves the view serializability for semistructured schedules polynomially in the size of the schedule and exponentially in the number of transactions.

cs.DB