SOLIOT—Decentralized Data Control and Interactions for Iot
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Validating RDF Data Using Shapes
83 Validating RDF data using Shapes a Jose Emilio Labra Gayo a University of Oviedo, Spain Abstract RDF forms the keystone of the Semantic Web as it enables a simple and powerful knowledge representation graph based data model that can also facilitate integration between heterogeneous sources of information. RDF based applications are usually accompanied with SPARQL stores which enable to efficiently manage and query RDF data. In spite of its well known benefits, the adoption of RDF in practice by web programmers is still lacking and SPARQL stores are usually deployed without proper documentation and quality assurance. However, the producers of RDF data usually know the implicit schema of the data they are generating, but they don't do it traditionally. In the last years, two technologies have been developed to describe and validate RDF content using the term shape: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL). We will present a motivation for their appearance and compare them, as well as some applications and tools that have been developed. Keywords RDF, ShEx, SHACL, Validating, Data quality, Semantic web 1. Introduction In the tutorial we will present an overview of both RDF is a flexible knowledge and describe some challenges and future work [4] representation language based of graphs which has been successfully adopted in semantic web 2. Acknowledgements applications. In this tutorial we will describe two languages that have recently been proposed for This work has been partially funded by the RDF validation: Shape Expressions (ShEx) and Spanish Ministry of Economy, Industry and Shapes Constraint Language (SHACL).ShEx was Competitiveness, project: TIN2017-88877-R proposed as a concise and intuitive language for describing RDF data in 2014 [1]. -
Base64 Character Encoding and Decoding Modeling
Base64 Character Encoding and Decoding Modeling Isnar Sumartono1, Andysah Putera Utama Siahaan2, Arpan3 Faculty of Computer Science,Universitas Pembangunan Panca Budi Jl. Jend. Gatot Subroto Km. 4,5 Sei Sikambing, 20122, Medan, Sumatera Utara, Indonesia Abstract: Security is crucial to maintaining the confidentiality of the information. Secure information is the information should not be known to the unreliable person, especially information concerning the state and the government. This information is often transmitted using a public network. If the data is not secured in advance, would be easily intercepted and the contents of the information known by the people who stole it. The method used to secure data is to use a cryptographic system by changing plaintext into ciphertext. Base64 algorithm is one of the encryption processes that is ideal for use in data transmission. Ciphertext obtained is the arrangement of the characters that have been tabulated. These tables have been designed to facilitate the delivery of data during transmission. By applying this algorithm, errors would be avoided, and security would also be ensured. Keywords: Base64, Security, Cryptography, Encoding I. INTRODUCTION Security and confidentiality is one important aspect of an information system [9][10]. The information sent is expected to be well received only by those who have the right. Information will be useless if at the time of transmission intercepted or hijacked by an unauthorized person [7]. The public network is one that is prone to be intercepted or hijacked [1][2]. From time to time the data transmission technology has developed so rapidly. Security is necessary for an organization or company as to maintain the integrity of the data and information on the company. -
V a Lida T in G R D F Da
Series ISSN: 2160-4711 LABRA GAYO • ET AL GAYO LABRA Series Editors: Ying Ding, Indiana University Paul Groth, Elsevier Labs Validating RDF Data Jose Emilio Labra Gayo, University of Oviedo Eric Prud’hommeaux, W3C/MIT and Micelio Iovka Boneva, University of Lille Dimitris Kontokostas, University of Leipzig VALIDATING RDF DATA This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications. RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange. The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models. At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints. -
The Opencitations Data Model
The OpenCitations Data Model Marilena Daquino1;2[0000−0002−1113−7550], Silvio Peroni1;2[0000−0003−0530−4305], David Shotton2;3[0000−0001−5506−523X], Giovanni Colavizza4[0000−0002−9806−084X], Behnam Ghavimi5[0000−0002−4627−5371], Anne Lauscher6[0000−0001−8590−9827], Philipp Mayr5[0000−0002−6656−1658], Matteo Romanello7[0000−0002−7406−6286], and Philipp Zumstein8[0000−0002−6485−9434]? 1 Digital Humanities Advanced research Centre (/DH.arc), Department of Classical Philology and Italian Studies, University of Bologna fmarilena.daquino2,[email protected] 2 Research Centre for Open Scholarly Metadata, Department of Classical Philology and Italian Studies, University of Bologna 3 Oxford e-Research Centre, University of Oxford [email protected] 4 Institute for Logic, Language and Computation (ILLC), University of Amsterdam [email protected] 5 Department of Knowledge Technologies for the Social Sciences, GESIS - Leibniz-Institute for the Social Sciences [email protected], [email protected] 6 Data and Web Science Group, University of Mannheim [email protected] 7 cole Polytechnique Fdrale de Lausanne [email protected] 8 Mannheim University Library, University of Mannheim [email protected] Abstract. A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with differ- ent nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data sup- plier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. -
GATEKEEPER Platform Overview
GATEKEEPER – Platform overview Table of contents ABSTRACT .........................................................................................................................................................4 1 ARCHITECTURE DEFINITION PRINCIPLES ................................................................................... 5 1.1 WEB OF THINGS ................................................................................................................................................................. 5 1.1.1 Principles for Gatekeeper data ....................................................................................................................... 6 1.1.2 Gatekeeper Web of Thing based architecture .................................................................................... 7 1.1.3 Role of WoT Thing Description ....................................................................................................................... 9 1.1.4 Role of FHIR and relation with Thing Description ............................................................................ 15 1.2 GATEKEEPER PLATFORM STAKEHOLDERS ........................................................................................................ 16 1.3 SECURITY AND PRIVACY CONSIDERATIONS ....................................................................................................... 17 1.3.1 Infrastructure security ..........................................................................................................................................18 -
Using Shape Expressions (Shex) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repositorio Institucional de la Universidad de Oviedo Using Shape Expressions (ShEx) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S. Stupp3, Jose Emilio Labra Gayo4, Daniel Mietchen5, Eric Prud’hommeaux6, and Andra Waagmeester7 1 Yale University, New Haven, CT, USA [email protected] 2 Johns Hopkins University, Baltimore, MD, USA [email protected] 3 The Scripps Research Institute, San Diego, CA, USA [email protected] 4 University of Oviedo, Oviedo, Spain [email protected] 5 Data Science Institute, University of Virginia, Charlottesville, VA, USA [email protected] 6 World Wide Web Consortium (W3C), MIT, Cambridge, MA, USA [email protected] 7 Micelio, Antwerpen, Belgium [email protected] Abstract. We discuss Shape Expressions (ShEx), a concise, formal, modeling and validation language for RDF structures. For instance, a Shape Expression could prescribe that subjects in a given RDF graph that fall into the shape “Paper” are expected to have a section called “Abstract”, and any ShEx implementation can confirm whether that is indeed the case for all such subjects within a given graph or subgraph. There are currently five actively maintained ShEx implementations. We discuss how we use the JavaScript, Scala and Python implementa- tions in RDF data validation workflows in distinct, applied contexts. We present examples of how ShEx can be used to model and validate data from two different sources, the domain-specific Fast Healthcare Interop- erability Resources (FHIR) and the domain-generic Wikidata knowledge base, which is the linked database built and maintained by the Wikimedia Foundation as a sister project to Wikipedia. -
Shape Designer for Shex and SHACL Constraints Iovka Boneva, Jérémie Dusart, Daniel Fernández Alvarez, Jose Emilio Labra Gayo
Shape Designer for ShEx and SHACL Constraints Iovka Boneva, Jérémie Dusart, Daniel Fernández Alvarez, Jose Emilio Labra Gayo To cite this version: Iovka Boneva, Jérémie Dusart, Daniel Fernández Alvarez, Jose Emilio Labra Gayo. Shape Designer for ShEx and SHACL Constraints. ISWC 2019 - 18th International Semantic Web Conference, Oct 2019, Auckland, New Zealand. 2019. hal-02268667 HAL Id: hal-02268667 https://hal.archives-ouvertes.fr/hal-02268667 Submitted on 30 Sep 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Shape Designer for ShEx and SHACL Constraints∗ Iovka Boneva1, J´er´emieDusart2, Daniel Fern´andez Alvarez´ 3, and Jose Emilio Labra Gayo3 1 Univ. Lille, CNRS, Centrale Lille, Inria, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France 2 Inria, France 3 University of Oviedo, Spain Abstract. We present Shape Designer, a graphical tool for building SHACL or ShEx constraints for an existing RDF dataset. Shape Designer allows to automatically extract complex constraints that are satisfied by the data. Its integrated shape editor and validator allow expert users to combine and modify these constraints in order to build an arbitrarily complex ShEx or SHACL schema. -
The Base16, Base32, and Base64 Data Encodings
Network Working Group S. Josefsson Request for Comments: 4648 SJD Obsoletes: 3548 October 2006 Category: Standards Track The Base16, Base32, and Base64 Data Encodings Status of This Memo This document specifies an Internet standards track protocol for the Internet community, and requests discussion and suggestions for improvements. Please refer to the current edition of the “Internet Official Protocol Standards” (STD 1) for the standardization state and status of this protocol. Distribution of this memo is unlimited. Copyright Notice Copyright © The Internet Society (2006). All Rights Reserved. Abstract This document describes the commonly used base 64, base 32, and base 16 encoding schemes. It also discusses the use of line-feeds in encoded data, use of padding in encoded data, use of non-alphabet characters in encoded data, use of different encoding alphabets, and canonical encodings. RFC 4648 Base-N Encodings October 2006 Table of Contents 1 Introduction...............................................................................................................................................................3 2 Conventions Used in This Document..................................................................................................................... 4 3 Implementation Discrepancies................................................................................................................................ 5 3.1 Line Feeds in Encoded Data.................................................................................................................................5 -
IDOL RSS Connector (CFS)
HPE RSS Connector Software Version: 10.11.0 RSS Connector (CFS) Release Notes Document Release Date: November 2015 Software Release Date: November 2015 RSS Connector (CFS) Release Notes Legal Notices Warranty The only warranties for Hewlett Packard Enterprise Development LP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HPE shall not be liable for technical or editorial errors or omissions contained herein. The information contained herein is subject to change without notice. Restricted Rights Legend Confidential computer software. Valid license from HPE required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. Copyright Notice © Copyright 2015 Hewlett Packard Enterprise Development LP Trademark Notices Adobe™ is a trademark of Adobe Systems Incorporated. Microsoft® and Windows® are U.S. registered trademarks of Microsoft Corporation. UNIX® is a registered trademark of The Open Group. This product includes an interface of the 'zlib' general purpose compression library, which is Copyright © 1995-2002 Jean-loup Gailly and Mark Adler. Documentation Updates HPE Big Data Support provides prompt and accurate support to help you quickly and effectively resolve any issue you may encounter while using HPE Big Data products. Support services include access to the Customer Support Site (CSS) for online answers, expertise-based service by HPE Big Data support engineers, and software maintenance to ensure you have the most up-to-date technology. -
Confidentiality Technique to Enhance Security of Data in Public Cloud Storage Using Data Obfuscation
ISSN (Print) : 0974-6846 Indian Journal of Science and Technology, Vol 8(24), DOI: 10.17485/ijst/2015/v8i24/80032, September 2015 ISSN (Online) : 0974-5645 Confidentiality Technique to Enhance Security of Data in Public Cloud Storage using Data Obfuscation S. Monikandan1* and L. Arockiam2 1Department of MCA, Christhu Raj College, Panjappur, Tiruchirappalli – 620012, Tamil Nadu, India; [email protected] 2Departmentof Computer Science, St. Joseph’s College (Autonomous), Tiruchirappalli – 620102, Tamil Nadu, India; [email protected] Abstract Security of data stored in the cloud is most important challenge in public cloud environment. Users are outsourced their data to cloud for efficient, reliable and flexible storage. Due the security issues, data are disclosed by Cloud Service Providers (CSP) and others users of cloud. To protect the data from unauthorized disclosure, this paper proposes a confidentiality technique as a Security Service Algorithm (SSA), named MONcryptto secure the data in cloud storage. This proposed confidentiality technique is based on data obfuscation technique. The MONcrypt SSA is availed from Security as a Service (SEaaS). Users could use this security service from SEaaS to secure their data at any time. Simulations were conducted in cloud environment (Amazon EC2) for analysis the security of proposed MONcrypt SSA. A security analysis tool is used for measure the security of proposed and existing obfuscation techniques. MONcrypt compares with existing obfuscation techniques like Base32, Base64 and Hexadecimal Encoding. The proposed technique provides better performance and good security when compared with existing obfuscation techniques. Unlike the existing technique, MONcrypt reduces the sizeKeywords: of data being uploaded to the cloud storage. -
Chapter 4: Inter-Process Communications
95-702 Distributed Systems Chapter 4: Inter-process Communications 95-702 Distributed Systems Information System Management 1 Objectives • Understand the purpose of middleware. • Understand how external data representations contribute to interoperability. • Understand how external data representations contribute to speed. • Understand marshalling/unmarshalling • Understand CORBA’s CDR • Understand Java’s serialization • Understand XML and JSON • Understand how remote object references may be represented. • A UDP based request response protocol • Failure models • Discussion questions 95-702 Distributed Systems Information System Management 2 Middleware layers Applications, services RMI and RPC request-reply protocol Middleware This layers chapter marshalling and external data representation UDP and TCP Middleware provides a higher level programming abstraction for the development of distributed systems. (Coulouris text). 95-702 Distributed Systems Information System Management 3 Moving values around on a network Passing values over a network may be problematic. Why? If both sides are the same (homogenous), no problem. But if the two sides differ in the way they represent data then we are faced with interoperability problems: 1. Big-endian, little-endian byte ordering may differ 2. Floating point representation may differ 3. Character encodings (ASCII, UTF-8, Unicode, EBCDIC) may differ as well. So, we must either: Have both sides agree on an external representation or transmit in the sender’s format along with an indication of the format -
XEP-0116: Encrypted Session Negotiation
XEP-0116: Encrypted Session Negotiation Ian Paterson Peter Saint-Andre mailto:ian:paterson@clientside:co:uk mailto:xsf@stpeter:im xmpp:ian@zoofy:com xmpp:peter@jabber:org http://stpeter:im/ Dave Smith mailto:dizzyd@jabber:org xmpp:dizzyd@jabber:org 2007-05-30 Version 0.16 Status Type Short Name Deferred Standards Track TO BE ASSIGNED This document specifies an XMPP protocol extension for negotiating an end-to-end encrypted session. Legal Copyright This XMPP Extension Protocol is copyright © 1999 – 2020 by the XMPP Standards Foundation (XSF). Permissions Permission is hereby granted, free of charge, to any person obtaining a copy of this specification (the ”Specification”), to make use of the Specification without restriction, including without limitation the rights to implement the Specification in a software program, deploy the Specification in a network service, and copy, modify, merge, publish, translate, distribute, sublicense, or sell copies of the Specifi- cation, and to permit persons to whom the Specification is furnished to do so, subject to the condition that the foregoing copyright notice and this permission notice shall be included in all copies or sub- stantial portions of the Specification. Unless separate permission is granted, modified works that are redistributed shall not contain misleading information regarding the authors, title, number, or pub- lisher of the Specification, and shall not claim endorsement of the modified works by the authors, any organization or project to which the authors belong, or the XMPP Standards Foundation. Warranty ## NOTE WELL: This Specification is provided on an ”AS IS” BASIS, WITHOUT WARRANTIES OR CONDI- TIONS OF ANY KIND, express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE.