Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Generalisation Through Negation and Predicate Invention

The ability to generalise from a small number of examples is a fundamental challenge in machine learning. To tackle this challenge, we introduce an inductive logic programming (ILP) approach that combines negation and predicate invention. Combining these two features allows an ILP system to generalise better by learning rules with universally quantified body-only variables. We implement our idea in NOPI, which can learn normal logic programs with predicate invention, including Datalog programs with stratified negation. Our experimental results on multiple domains show that our approach can improve predictive accuracies and learning times.Comment: Under peer-revie

Datalog Unchained

International audienceThis is the companion paper of a talk in the Gems of PODS series, that reviews the development, starting at PODS 1988, of a family of Datalog-like languages with procedural, forward chaining semantics, providing an alternative to the classical declarative, model-theoretic semantics. These languages also provide a unified formalism that can express important classes of queries including fixpoint, while, and all computable queries. They can also incorporate in a natural fashion updates and nondeterminism. Datalog variants with forward chaining semantics have been adopted in a variety of settings, including active databases, production systems, distributed data exchange, and data-driven reactive systems

Temporal datalog with existential quantification

Existential rules, also known as tuple-generating dependencies (TGDs) or Datalog± rules, are heavily studied in the communities of Knowledge Representation and Reasoning, Semantic Web, and Databases, due to their rich modelling capabilities. In this paper we consider TGDs in the temporal setting, by introducing and studying DatalogMTL∃—an extension of metric temporal Datalog (DatalogMTL) obtained by allowing for existential rules in programs. We show that DatalogMTL∃ is undecidable even in the restricted cases of guarded and weakly-acyclic programs. To address this issue we introduce uniform semantics which, on the one hand, is well-suited for modelling temporal knowledge as it prevents from unintended value invention and, on the other hand, provides decidability of reasoning; in particular, it becomes 2-ExpSpace-complete for weakly-acyclic programs but remains undecidable for guarded programs. We provide an implementation for the decidable case and demonstrate its practical feasibility. Thus we obtain an expressive, yet decidable, rule-language and a system which is suitable for complex temporal reasoning with existential rules

Datalog Queries Distributing over Components

We investigate the class D of queries that distribute over components. These are the queries that can be evaluated by taking the union of the query results over the connected components of the database instance. We show that it is undecidable whether a (positive) Datalog program distributes over components. Additionally, we show that connected Datalog ¬ (the fragment of Datalog ¬ where all rules are connected) provides an effective syntax for Datalog ¬ programs that distribute over components under the stratified as well as under the well-founded semantics. As a corollary, we obtain a simple proof for one of the main results in previous work [19], namely, that the classic win-move query is in F2 (a particular class of coordination-free queries)

Fictitious Commodities: A Theory of Intellectual Property Inspired by Karl Polanyi’s “Great Transformation”

The puzzle this Article addresses is this: how can it be explained that intellectual property (IP) laws and IP rights (IPRs) have continuously grown in number and expanded in scope, territorial reach, and duration, while at the same time have been contested, much more so than other branches of property law? This Article offers an explanation for this peculiar dynamic by applying insights and concepts of Karl Polanyi’s book “The Great Transformation” to IP. It reconstructs and then applies core Polanyian concepts of commodification (infra, II), fictitious commodities (infra, III), and countermovements (infra, IV) to the three main areas of IP, namely copyrights, patents, and trademarks, as they have evolved and are currently regulated in international and selected national laws. The analysis reveals that the history of IP can be told in terms of Polanyi’s famous “double movement”: efforts to commodify virtually every reproducible input/output face equally persistent opposition, which points out the disruption that IPRs inflict upon communication and competition. Whereas IPRs dis-embed informational artefacts from the uninterrupted flow of societal exchange and subject them to prior authorization requirements, IP countermovements call for their re-embedding, i.e. their usability irrespective of authorization. From a normative perspective, a Polanyian perspective on IP suggests that IP law and policy should ensure that market-based transactions coexist with non-market modes of accessing and sharing information so that authors, inventors, and other entrepreneurs have as many options as possibl