Numerous indexing databases keep track of the number of publications, citations, etc. in order to maintain the progress of science and individual. However, the choice of journals and articles varies among these indexing databases, hence the number of citations and h-index varies. There is no common platform exists that can provide a single count for the number of publications, citations, h-index, etc. To overcome this limitation, we have proposed a weighted unified informetrics, named "conflate". The proposed system takes into account the input from multiple indexing databases and generates a single output. Here, we have used the data from Scopus and WoS to generate a conflate dataset. Further, a comparative analysis of conflate has been performed with Scopus and WoS at three levels: author, organization, and journal. Finally, a mapping is proposed between research publications and distributed ledger technology in order to provide a transparent and distributed view to its stakeholders.
ABSTRACT The formalization of the REA2 ontology presented in this paper offers a minimal set of operationalized semantics for a single white-box model relevant to all business stakeholders independent of their role or involvement in economic activities. This paper's theoretical innovations are the use of MERODE to model increment and decrement semantics as fundamental stand-alone concepts that simultaneously affect economic resources, event, agents, and the semantics of the stock-flow, participation, and ownership associations and the formalization of the REA axioms as executable finite state machines. MERODE's possibilities for model execution through fast prototyping allowed validation through the modeling of an archetypical exchange scenario. Both innovations contribute to the reliability of a generic semantic model for finance and logistics in both the traditional, as well as the sharing, economy, thus promoting traceability and accountability in value networks and supply chains supported by both centralized and decentralized ledger technologies.
Juan Cano-Benito, Andrea Cimmino, Raúl García‐Castro
Blockchain has become a pervasive technology in a wide number of sectors like industry, research, and academy. With the emergence of blockchain, new solutions with this technology to existing problems were devised, leading to the introduction of smart contracts. Smart contracts are similar to traditional contracts with the benefits provided by blockchain, such as immutability, privacy, and decentralisation. These contracts are usually defined based on a specific domain, and this domain knowledge can be represented through an ontology. Researches have explored the benefits of using domain ontologies with smart contracts, such as code generation, discovering other contracts in the network, or interaction with other contracts. Notwithstanding, the representation of smart contract languages themselves has not been studied. In this paper, we present an ontology for a well-known smart contract language, Solidity, defining all entities needed to cover the whole language and aligning it to other standardised ontologies such as EthOn, in a way to improve the knowledge of the ontology developed. Furthermore, the ontology has also been validated with already deployed contracts in the Ethereum blockchain. Thus, Solidity will be able to benefit from the advantages provided by ontologies, such as interoperability and the use of semantic web technologies.
Christian Cachin, Angelo De, Pedro Moreno-Sánchez, Björn Tackmann · 5 authors
The advent of Bitcoin paved the way for a plethora of blockchain systems supporting diverse applications beyond cryptocurrencies. Although in-depth studies of the consensus protocols as well as the privacy of blockchain transactions are available, there is no formal model of the transaction semantics that a blockchain is supposed to guarantee.
Kevin Wittek, Dominik Krakau, Neslihan Wittek, James H. Lawton · 5 authors
Proof of Existence as a blockchain service has first been published in 2013 as a public notary service on the Bitcoin network and can be used to verify the existence of a particular file in a specific point of time without sharing the file or its content itself. This service is also available on the Ethereum based bloxberg network, a decentralized research infrastructure that is governed, operated and developed by an international consortium of research facilities. Since it is desirable to integrate the creation of this proof tightly into the research workflow, namely the acquisition and processing of research data, we show a simple to integrate MATLAB extension based solution with the concept being applicable to other programming languages and environments as well.
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies. \nToday, we count more than 10,000 datasets made available online following Semantic Web standards. \nA major and yet unsolved challenge that research faces today is to perform scalable analysis of large-scale knowledge graphs in order to facilitate applications in various domains including life sciences, publishing, and the internet of things. \nThe main objective of this thesis is to lay foundations for efficient algorithms performing analytics, i.e. exploration, quality assessment, and querying over semantic knowledge graphs at a scale that has not been possible before. \nFirst, we propose a novel approach for statistical calculations of large RDF datasets, which scales out to clusters of machines. \nIn particular, we describe the first distributed in-memory approach for computing 32 different statistical criteria for RDF datasets using Apache Spark. \nMany applications such as data integration, search, and interlinking, may take full advantage of the data when having a priori statistical information about its internal structure and coverage. \nHowever, such applications may suffer from low quality and not being able to leverage the full advantage of the data when the size of data goes beyond the capacity of the resources available. \nThus, we introduce a distributed approach of quality assessment of large RDF datasets. \nIt is the first distributed, in-memory approach for computing different quality metrics for large RDF datasets using Apache Spark. We also provide a quality assessment pattern that can be used to generate new scalable metrics that can be applied to big data. \nBased on the knowledge of the internal statistics of a dataset and its quality, users typically want to query and retrieve large amounts of information. \nAs a result, it has become difficult to efficiently process these large RDF datasets. \nIndeed, these processes require, both efficient storage strategies and query-processing engines, to be able to scale in terms of data size. \nTherefore, we propose a scalable approach to evaluate SPARQL queries over distributed RDF datasets by translating SPARQL queries into Spark executable code. \nWe conducted several empirical evaluations to assess the scalability, effectiveness, and efficiency of our proposed approaches. \nMore importantly, various use cases i.e. Ethereum analysis, Mining Big Data Logs, and Scalable Integration of POIs, have been developed and leverages by our approach. \nThe empirical evaluations and concrete applications provide evidence that our methodology and techniques proposed during this thesis help to effectively analyze and process large-scale RDF datasets. \nAll the proposed approaches during this thesis are integrated into the larger SANSA framework.
There are thousands of projects worldwide based primarily on blockchain technology. These have a large number of users and hundreds of use cases. One of the most popular is the use of cryptocurrencies and their benefits against money without intrinsic value (fiat money) and centralized financial solutions. However, although thousands of new transactions are carried out daily in different platforms, uniform and standardized information does not exist to be able to manage the large amount of data that is generated and exchanged between users through transactions and the generation of new blocks. This research reports the development of BLONDiE, an ontology that allows the semantic representation of knowledge to describe the native structure and related information of the three most relevant blockchain projects to date: Bitcoin, Ethereum and in the recent 1.0 version extends its definitions to include Hyperledger, specifically the Hyperledger Fabric infrastructure. Its use allows having common data formats of different platforms for further processing, such as the execution of semantic queries.
Sepehr Sharifi, Alireza Parvizimosaed, Daniel Amyot, Luigi Logrippo · 5 authors
Legal contracts specify the terms and conditions (in essence, requirements) that apply to business transactions. Smart contracts are software systems that monitor and control the execution of contracts to ensure compliance. This paper proposes a formal specification language for contracts, called Symboleo, where contracts consist of collections of obligations and powers that define the legal contract's compliant executions. The formal semantics of Symboleo is based on an extension of an ontology for Law and is described in terms of logical axioms on statecharts that describe the lifetimes of contracts, obligations and powers. Our proposal includes a preliminary evaluation through the specification of a real life-inspired Sale-of-Goods contract, with a prototype execution engine. We envision this language to enable formally verifying contracts to detect requirements-level issues and to generate executable smart contracts (e.g., on blockchain technology).
Ignacio Huitzil, Alvaro Fuentemilla, Fernando Bobillo
This paper proposes a novel extension of blockchain systems with fuzzy ontologies. The main advantage is to let the users have flexible restrictions, represented using fuzzy sets, and to develop smart contracts where there is a partial agreement among the involved parts. We propose a general architecture based on four fuzzy ontologies and a process to develop and run the smart contracts, based on a reduction to a well-known fuzzy ontology reasoning task (Best Satisfiability Degree). We also investigate different operators to compute Pareto-optimal solutions and implement our approach in the Ethereum blockchain.
Solutions based on distributed ledgers require sophisticated tools for data modelling and integration that can be overcome using semantic and Linked Data technologies. One example is copyright management, where we attempt to adapt the Copyright Ontology so it can be used to build applications that benefit from both worlds, rich information modelling and reasoning together with immutable and accountable information storage that provides trust and confidence on the modelled rights statements. This approach has been applied in the context of an application for the management of social media re-use for journalistic purposes.
This paper is a progress report on our recent work on two applications that use Linked Data and Distributed Ledger technologies and aim to transform the Greek public sector into a decentralized, trusted, intelligent and linked organization. The first application is a re-engineering of Diavgeia, the Greek government portal for open and transparent public administration. The second application is Nomothesia, a new portal that we have built, which makes Greek legislation available on the Web as linked data to enable its effective use by citizens, legal professionals and software developers who would like to build new applications that utilize Greek legislation. The presented applications have been implemented without funding from any source and are available for free to any part of the Greek public sector that may want to use them. An important goal of this paper is to present the lessons learned from this effort.
Maribel Acosta, Tim Berners‐Lee, Stefan Dietze, Anastasia Dimou · 9 authors
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.
Krishnendu Chatterjee, Amir Kafshdar Goharshady, Arash Pourdamghani
In today's cryptocurrencies, Hashcash proof of work is the most commonly-adopted approach to mining. In Hashcash, when a miner decides to add a block to the chain, she has to solve the difficult computational puzzle of inverting a hash function. While Hashcash has been successfully adopted in both Bitcoin and Ethereum, it has attracted significant and harsh criticism due to its massive waste of electricity, its carbon footprint and environmental effects, and the inherent lack of usefulness in inverting a hash function. Various other mining protocols have been suggested, including proof of stake, in which a miner's chance of adding the next block is proportional to her current balance. However, such protocols lead to a higher entry cost for new miners who might not still have any stake in the cryptocurrency, and can in the worst case lead to an oligopoly, where the rich have complete control over mining. \n \nIn this paper, we propose Hybrid Mining: a new mining protocol that combines solving real-world useful problems with Hashcash. Our protocol allows new miners to join the network by taking part in Hashcash mining without having to own an initial stake. It also allows nodes of the network to submit hard computational problems whose solutions are of interest in the real world, e.g.~protein folding problems. Then, miners can choose to compete in solving these problems, in lieu of Hashcash, for adding a new block. Hence, Hybrid Mining incentivizes miners to solve useful problems, such as hard computational problems arising in biology, in a distributed manner. It also gives researchers in other areas an easy-to-use tool to outsource their hard computations to the blockchain network, which has enormous computational power, by paying a reward to the miner who solves the problem for them. Moreover, our protocol provides strong security guarantees and is at least as resilient to double spending as Bitcoin.
Each manufacturer, supplier, and retailer has its own chain of collaborating stakeholders to meet their customer demands. Many perspectives can be taken like food safety, security, and sustainability, which may each lead to separate solutions that are not necessarily interoperable with each other. Data can only be shared within the context of those solutions and only with extra effort, and thus costs, across these solutions. To address this solution, this paper proposes a methodological approach for specification of data that can be shared with rapid deployment by for instance a blockchain based - or a peer-to-peer infrastructure. The methodological approach is based on basic informatics principles like the Turing machine and ontologies.
We present an approach to verify off-chained information using Linked Data, Smart Contracts, and RDF graph hashes stored on a Distributed Ledger. We use the notion of a Linked Pedigree, i.e. a decentralised dataset for storing hyperlinked information, as modelling foundation. We evaluate our approach by comparing different ways to build the Smart Contract. We develop a cost model and show, based on our implementation, that for managing multiple Linked Pedigree instances, a single larger Smart Contract is superior to multiple smaller Smart Contracts for supply chains shorter than 50 participants.
We study the problem of building non-interactive proof systems modularly by linking small specialized SNARKs in a lightweight manner. Our motivation is both theoretical and practical. On the theoretical side, modular SNARK designs would be flexible and reusable. Also, previous works (e.g., Geppetto) consider They have been successfully employed in previous works.(cite prev papers ). These approaches, however, tend to be ad-hoc and to reinventing the wheel. We propose to fill this gap. In practice, specialized SNARKs have the potential to be more efficient than general-purpose schemes, on which most existing works have focused. If a computation naturally presents different components (e.g. one arithmetic circuit and one boolean circuit), a general-purpose scheme would homogenize them to a single representation with a subsequent cost in performance. Through a modular approach one could instead exploit the nuances of a computation and choose the best gadget for each component. Our contribution is LegoSNARK, a toolbox (or framework) for commit-and-prove zkSNARKs (CP-SNARKs) that includes: 1) General composition tools: build new CP-SNARKs from proof gadgets for basic relationssimply. Formalize notion of cc-SNARK. 2) A lifting tool: a compiler to add commit-and-prove capabilities to a broad class of existing zkSNARKsefficiently. This makes them interoperable (linkable) within the same computation. For example, one QAP-based scheme can be used prove one component; another GKR-based scheme can be used to prove another. 3) A collection of succinct proof gadgets for a variety of relations. Additionally, through our framework and gadgets, we are able to obtain new succinct proof systems. Notably: -- LegoGro16, a commit-and-prove version of Groth16 zkSNARK, that operates over data committed with a classical Pedersen vector commitment, and that achieves a 5000× speedup in proving time. -- LegoUAC, a pairing-based SNARK for arithmetic circuits that has a universal, circuit-independent, CRS, and proving time linear in the number of circuit gates (vs. the recent scheme of Groth et al. (CRYPTO'18) with quadratic CRS and quasilinear proving time). -- LegoMM, a CP-SNARK for matrix multiplication that achieves optimal proving complexity.
Blockchain, or distributed ledger technology, has been an increasingly common topic in technical circles over the past several years. You may have read one of the thousands of articles documenting ...
Paula Peña, Rocío Aznar, Rosa Montañés, Rafael Alonso
The project presented has been financed by Government of Aragon and is part of the ''Open Data'' initiative promoted by that organization. Given the amount of unstructured information related to the Government of Aragon currently published on the Internet, with slightly or no standardization and decentralized, it emerges the need to gather it systematically to be offered to all interested collectives from a single access point in a public and structured way. Within this context, ''Aragon Open Data'' project aims to collect, organize, store and maintain updated, Administration''s web information by means of human language and semantic technologies. Firstly, crawling is performed over websites in order to retrieve textual data over which Natural Language Processing (NLP) and ontology-based techniques are applied. Thereafter, results are stored into NoSQL databases, allowing future open access and simple data exploitation. NLP techniques used in the project involve named-entities recognition and classification (NERC) and texts semantic classification and summarization.
Miguel Tavares, André Guerreiro, Carlos Coutinho, Filipe Veiga · 5 authors
Businesses and organizations have for long been trying to tackle the most prominent issues regarding identity management and systems. Traditionally, the proof of trust concerning the identification of a citizen, a customer or a participant in any business or transaction consisted always in a physical evidence (e.g., a signature, fingerprint, photo or other) whose value would rely on a trusted third-party such as a notary or attorney that confirmed the veracity of that physical evidence. More recent approaches include novel types of evidence such as digital certificates, but still these have no value unless they are issued and signed by a trusted centralized third-party that confirms the authenticity of the certificate. These are then often used by businesses to identify and trace their parties and stakeholders, in a process known as "Know Your Customer" (KYC). This process is often slow and requires costly human intervention. This paper presents WalliD, a decentralized approach of a secure protocol to handle customer identification using Blockchain. The paper then shows a proof of concept workflow implementation of this protocol developed using an Ethereum Wallet.