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What is Linked Data? The Semantic Web is a Web of Data — of dates and titles and part numbers and chemical properties and any other data one might conceive of. The collection of Semantic Web technologies (RDF, OWL, SKOS, SPARQL, etc.) provides an environment where application can query that data, draw inferences using vocabularies, etc. However, to make the Web of Data a reality, it is important to have the huge amount of data on the Web available in a standard format, reachable and manageable by Semantic Web tools. Furthermore, not only does the Semantic Web need access to data, but relationships among data should be made available, too, to create a Web of Data (as opposed to a sheer collection of datasets). To achieve and create Linked Data, technologies should be available for a common format (RDF), to make either conversion or on-the-fly access to existing databases (relational, XML, HTML, etc). What is Linked Data Used For? Examples Learn More Current Status of Specifications Related:  teaching: Linked Data

» Linked Data for the Uninitiated (Part 1) | DOCUMENTING CAPPADOCIA This two-part post is my follow-up to LAWDI 2012, officially known as the first Linked Ancient World Data Institute. It brought together a multi-disciplinary group of digital scholars at NYU’s Institute for the Study of the Ancient World (ISAW) whose interests incorporate the Ancient Medierranean and Near East. This essay is cross-posted on the GC Digital Fellows blog The Linked Data Cloud as of September 2011. In preparation for LAWDI 2012, I wrote a post called “Linked Data: A Theory,” pondering the concepts behind Linked Data, but it was clear to me from the beginning that I needed a more sturdy vocabulary and concrete skills in order to put these ideas into practice. Linked Data is a philosophy applied to web development. Linked Data is often incorporated into conversations about Open Access, a crucial movement intended to counteract academia’s traditional exclusionary practices by making scholarship freely available to the public. Open Data How the Web Operates

Linked Data Basics for Techies - OpenOrg Intended Audience This is intended to be a crash course for a techie/programmer who needs to learn the basics ASAP. It is not intended as an introduction for managers or policy makers (I suggest looking at Tim Berners-Lee's TED talks if you want the executive summary). It's primarily aimed at people who're tasked with creating RDF and don't have time to faff around. It will also be useful to people who want to work with RDF data. Please Feedback-- especially if something doesn't make sense!!!! If you are new to RDF/Linked Data then you can help me! I put a fair bit of effort into writing this, but I am too familar with the field! If you are learning for the first time and something in this guide isn't explained very well, please drop me a line so I can improve it. Warning Some things in this guide are deliberately over-simplified. Alternatives If you don't like my way of explaining things, then there's other introductions out there; (suggest more!) Structure Merging URI vs URL a

SPARQL 1.1 Protocol 4.1 Security There are at least two possible sources of denial-of-service attacks against SPARQL protocol services. First, under-constrained queries can result in very large numbers of results, which may require large expenditures of computing resources to process, assemble, or return. Another possible source are queries containing very complex — either because of resource size, the number of resources to be retrieved, or a combination of size and number — RDF Dataset descriptions, which the service may be unable to assemble without significant expenditure of resources, including bandwidth, CPU, or secondary storage. Since a SPARQL protocol service may make HTTP requests of other origin servers on behalf of its clients, it may be used as a vector of attacks against other sites or services. SPARQL protocol services may remove, insert, and change underlying data via the update operation. Different IRIs may have the same appearance.

The Linking Open Data cloud diagram Taxonomy and Recirculation The taxonomy’s main job is to help users explore the site, and it can only do that if the tags and categories are used consistently. We wanted a system that was easy for editors to manage, with clear guidelines for how to apply tags and categories to posts. When we looked at the original taxonomy on The Toast, we found, well, the exact opposite of what we wanted. The Old Toast: Like your closet, but with more piles of random stuff Peeking inside The Toast uncovered a big ol’ stew of tags. The complete tags list, as you can imagine, was a hot mess. Some tags were topical: disabilitythe great outdoorstravel Some grouped posts into recurring series: two monks inventing thingstexts fromwatching downton abbey with an historian Some were funny: opinions i formed when i was thirteen with no life experienceat least one of you is going to tell me that elementary is better but that’s just because you like lucy liulicorice is disgusting The New Toast: Your closet after a visit to the Container Store

Seeing Standards Poster of visualization (PDF, 36in x 108in) Metadata standard glossary, poster form (PDF, 36in x 41in) Metadata standard glossary, pamphlet form (PDF) The sheer number of metadata standards in the cultural heritage sector is overwhelming, and their inter-relationships further complicate the situation. This visual map of the metadata landscape is intended to assist planners with the selection and implementation of metadata standards. Each of the 105 standards listed here is evaluated on its strength of application to defined categories in each of four axes: community, domain, function, and purpose. The standards represented here are among those most heavily used or publicized in the cultural heritage community, though certainly not all standards that might be relevant are included. Content: Jenn Riley Design: Devin Becker Work funded by the Indiana University Libraries White Professional Development Award Copyright 2009-2010 Jenn Riley

Linked Data: Evolving the Web into a Global Data Space Read These Seven Books, and You’ll be a Better Writer Donald Miller I used to play golf but I wasn’t very good. I rented a DVD, though, that taught me a better way to swing, and after watching it a few times and spending an hour or so practicing, I knocked ten strokes off my game. I can’t believe how much time I wasted when a simple DVD saved me years of frustration. • The War of Art by Steven Pressfield: This book is aimed at writers, but it’s also applicable to anybody who does creative work. Pressfield leaves out all the mushy romantic talk about the writing life, talk I don’t find helpful. • On Writing Well by William Zinsser: Zinsser may be the best practical writing coach out there. • Bird by Bird by Anne Lamott: Before becoming a literary superstar, Anne Lamott taught writing, and Bird by Bird is the best of her advice, broken up into chapters. Save the Cat by Blake Snyder: Snyder’s book is specifically for screenwriters, and yet I recommend the book for writers of any kind, and teachers and preachers as well.

Linked Open Data Find now everything about Europeana Linked Open Data- data.europeana. eu on: Linked Open Data is a way of publishing structured data that allows metadata to be connected and enriched, so that different representations of the same content can be found, and links made between related resources. Linked Open Data - What is it? from Europeana on Vimeo (also in French, German, Italian and Spanish).

The data roadmap for IBM’s first CDO | IBM Big Data & Analytics Hub This year, at the 2016 Spring CDO Summit, IBM Chief Data Officer Inderpal Bhandari gave a forward looking presentation about his plans for IBM’s data strategy. Among the topics covered were a general data strategy applicable to many CDOs, a description of cognitive technology, and more specific details about how he will personally move forward in his new role. While a full replay of the presentation is available, a brief recap is also provided below. Inderpal pointed to five activities that are important for a data strategy plan. Sequential Developing a clear data strategy. Concurrent Building deep data and analytics partnerships with business units. “In terms of nurturing talent, the open source angle is critical.” Cognitive systems are also an important consideration, and Inderpal reviewed their four main attributes: Their primary value is expertise. Inderpal finished his presentation by speaking a bit more specifically about his plans for the data strategy at IBM.

Une nouvelle norme pour le thésaurus (1) : Pourquoi une nouvelle no... sameAs Protege Ontology Library OWL ontologies Information on how to open OWL files from the Protege-OWL editor is available on the main Protege Web site. See the Creating and Loading Projects section of the Getting Started with Protege-OWL Web page. AIM@SHAPE Ontologies: Ontologies pertaining to digital shapes. Frame-based ontologies In the context of this page, the phrase "frame-based ontologies" loosely refers to ontologies that were developed using the Protege-Frames editor. Biological Processes: A knowledge model of biological processes and functions that is graphical, for human comprehension, and machine-interpretable, to allow reasoning. Other ontology formats Dublin Core: Representation of Dublin Core metadata in Protege.