The Irrefutable History of You: Distributed Ledgers and Semantics for Ubiquitous Personal Ratings

A recurring theme in the science-fiction series Black Mirror is the consequence for society of an over-focus on social networking. The episode Nosedive imagines a future in which every public interaction a person has is rated by the other parties, and every aspect of ones life depends on the overall rating computed from these. In this paper, we show how such a scenario is already technically possible using existing technologies such as distributed ledgers, and discuss means by which the negative possibilities may be ameliorated using semantic approaches

Expressing OWL axioms by English sentences: dubious in theory, feasible in practice

With OWL (Web Ontology Language) established as a standard for encoding ontologies on the Semantic Web, interest has begun to focus on the task of verbalising OWL code in controlled English (or other natural language). Current approaches to this task assume that axioms in OWL can be mapped to sentences in English. We examine three potential problems with this approach (concerning logical sophistication, information structure, and size), and show that although these could in theory lead to insuperable difficulties, in practice they seldom arise, because ontology developers use OWL in ways that favour a transparent mapping. This result is evidenced by an analysis of patterns from a corpus of over 600,000 axioms in about 200 ontologies

LinkChains: Exploring the space of decentralised trustworthy Linked Data

Distributed ledger platforms based on blockchains provide a fully distributed form of data storage which can guarantee data integrity. Certain use cases, such as medical applications, can benefit from guarantees that the results of arbitrary queries against a Linked Dataset faithfully represent its contents as originally published, without tampering or data corruption. We describe potential approaches to the storage and querying of Linked Data with varying degrees of decentralisation and guarantees of integrity, using distributed ledgers, and discuss their a priori differences in performance, storage limitations and reliability, setting out a programme for future empirical research

Automatic grounding of vague geographic ontology in data

In constructing an ontological theory of a domain such as geography, it is important not only to take account of the vagueness and ambiguity which is inherent in many of the relevant concepts, but also to be able to relate the high-level definitions of the theory to actual sets of data of varying kinds. Any attempt to ignore or remove vagueness and ambiguity risks errors and conflict in the ontological theory with the knowledge of different domain experts, while an inability to ground the theory in real data limits its practical use. We present here a means of structuring such a theory to handle these issues in a principled manner, which lends itself to concrete implementation. We illustrate with reference to several examples from the domain of hydrography

“Hidden semantics”: what can we learn from the names in an ontology?

Despite their flat, semantics-free structure, ontology identifiers are often given names or labels corresponding to natural language words or phrases which are very dense with information as to their intended referents. We argue that by taking advantage of this information density, NLG systems applied to ontologies can guide the choice and construction of sentences to express useful ontological information, solely through the verbalisations of identifier names, and that by doing so, they can replace the extremely fussy and repetitive texts produced by ontology verbalisers with shorter and simpler texts which are clearer and easier for human readers to understand. We specify which axioms in an ontology are “defining axioms” for linguistically-complex identifiers and analyse a large corpus of OWL ontologies to identify common patterns among all defining axioms. By generating texts from ontologies, and selectively including or omitting these defining axioms, we show by surveys that human readers are typically capable of inferring information implicitly encoded in identifier phrases, and that texts which do not make such “obvious” information explicit are preferred by readers and yet communicate the same information as the longer texts in which such information is spelled out explicitly

Linked Data Indexing of Distributed Ledgers

Searching for information in distributed ledgers is currently not an easy task, as information relating to an entity may be scattered throughout the ledger with no index. As distributed ledger technologies become more established, they will increasingly be used to represent real world transactions involving many parties and the search requirements will grow. An index providing the ability to search using domain specific terms across multiple ledgers will greatly enhance to power, usability and scope of these systems. We have implemented a semantic index to the Ethereum blockchain platform, to expose distributed ledger data as Linked Data. As well as indexing block- and transaction-level data according to the BLONDiE ontology, we have mapped smart contracts to the Minimal Service Model ontology, to take the first steps towards connecting smart contracts with Semantic Web Services

LinkChains: Trusted Personal Linked Data

Centralisation of data is increasingly widely considered to be an important societal problem. The ability to manage personal data, especially, in accordance with good principles for decentralised data systems is vital in response. We present our vision for the trusted decentralised personal data Web in the form of the LinkChains architecture

Towards the Temporal Streaming of Graph Data on Distributed Ledgers

We present our work-in-progress on handling temporal RDF graph data using the Ethereum distributed ledger. The motivation for this work are scenarios where multiple distributed consumers of streamed data may need or wish to verify that data has not been tampered with since it was generated – for example, if the data describes something which can be or has been sold, such as domestically-generated electricity. We describe a system in which temporal annotations, and information suitable to validate a given dataset, are stored on a distributed ledger, alongside the results of fixed SPARQL queries executed at the time of data storage. The model adopted implements a graph-based form of temporal RDF, in which time intervals are represented by named graphs corresponding to ledger entries. We conclude by discussing evaluation, what remains to be implemented, and future directions

Online Learning and Experimentation via Interactive Learning Resources

Recent trends in online learning like Massive Open Online Courses (MOOCs) and Open Educational Resources (OERs) are changing the landscape in the education sector by allowing learners to self-regulate their learning and providing them with an abundant amount of free learning materials. This paper presents FORGE, a new European initiative for online learning and experimentation via interactive learning resources. FORGE provides learners and educators with access to world- class facilities and high quality learning materials, thus enabling them to carry out experiments on e.g. new Internet protocols. In turn, this supports constructivist and self-regulated learning approaches, through the use of interactive learning resources, such as eBooks

The FAIR TRADE Framework for Assessing Decentralised Data Solutions

Decentralised data solutions bring their own sets of capabilities, requirements and issues not necessarily present in centralised solutions. In order to compare the properties of different approaches or tools for management of decentralised data, it is important to have a common evaluation framework. We present a set of dimensions relevant to data management in decentralised contexts and use them to define principles extending the FAIR framework, initially developed for open research data. By characterising a range of different data solutions or approaches by how TRusted, Autonomous, Distributed and dEcentralised, in addition to how Findable, Accessible, Interoperable and Reusable, they are, we show that our FAIR TRADE framework is useful for describing and evaluating the management of decentralised data solutions, and aim to contribute to the development of best practice in a developing field