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Excel and Semantic web | Graph DB | RDF triplestore

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g4 survey open data vis. 2015 Voyager InfoVis. 186 VanDenBesselaar et al RISIS. IRCDL 2017 paper 7. DSpace is a turnkey institutional repository application. Chapter 4: Interaction with Linked Data. 4.1 Introduction In the previous chapter we described how linked data could be made available, for example, via a data dump or SPARQL endpoint.

Chapter 4: Interaction with Linked Data

The emphasis was on providing data in a form readable by machines such as RDF/XML or Turtle.

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Alternative Tabular to RDF converters · timrdf/csv2rdf4lod-automation Wiki. Csv2rdf4lod-automation is licensed under the [Apache License, Version 2.0]( csv2rdf4lod is a tool by some folks in the Tetherless World Constellation at RPI.

Alternative Tabular to RDF converters · timrdf/csv2rdf4lod-automation Wiki

It is currently being used as part of the infrastructure for their Linking Open Government Data and Linking Open Biomedical Data projects. Tim Lebo wrote it with some invaluable design guidance from Greg Williams. DataGraft: One-Stop-Shop for Open Data Management. Review Comment: This manuscript was submitted as 'Tools and Systems Report' and should be reviewed along the following dimensions: (1) Quality, importance, and impact of the described tool or system (convincing evidence must be provided). (2) Clarity, illustration, and readability of the describing paper, which shall convey to the reader both the capabilities and the limitations of the tool.

DataGraft: One-Stop-Shop for Open Data Management

I would like to thank the authors for clear answers to almost all of my questions and concerns! For me only two points remain. I believe these should be easy to address by the authors in a minor revision: - I was unable to find the definitions of terms like ‘cleaning’ and ‘preparing’, etc. in the revised paper.

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Turning a spreadsheet into a faceted search engine with Cloudant. Turning your structured data into a faceted search engine is easy with Cloudant Search.

Turning a spreadsheet into a faceted search engine with Cloudant

Build scalable, highly available search tools for your data to give your users the best experience. Whether you’ve realized it or not, you probably used a faceted search engine recently. When you do a search on a web site, and you have the option to refine the search results using a few pre-defined categories, you’re doing faceted search. From retail to housing to travel, faceted search is the gold standard for quickly and intuitively narrowing down an overwhelming set of choices down to something manageable. Documentation - Cambridge Semantics.

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Logd.tw.rpi. Mapping data to pages using an upload tool for MS Excel files - semantic-mediawiki.org. OpenLink Virtuoso. DataGraft: Data-as-a-Service for Open Data. Introduction to the Semantic Web and Linked Data. Andreu Sulé, sule@ub.eduLecturer in the Department of Library and Information Science and Audiovisual Communication at the University of Barcelona Laia Lapeyra, laialapeyra@gmail.comStudent in the Bachelor’s Degree in Information and Documentation at the University of Barcelona Andreu Sulé is the coordinator of a line of research on the implementation of Semantic Web technologies (RDF, RDF Schema, SKOS and OWL) in digital collections in libraries, archives and museums in Catalonia and the rest of Spain.

Introduction to the Semantic Web and Linked Data

His personal web page is Lecturer at the Faculty of Library and Information Science of the University of Barcelona from 1998, his subject of interest are Organization of Information, Metadata, Encoding Standards, Vocabulary Control, Semantic Web and Design of Retrieval Systems. A Quick Guide on How to Prevail in the Graph Database Arena. Introduction There are endless discussions on the databases arena about which DBMS is best suited for operational or data warehousing analytics, which one is the most efficient for online transaction processing, or which one is suitable for semantic integration.

A Quick Guide on How to Prevail in the Graph Database Arena

Recently graph databases are growing in popularity, especially in the enterprise space, and perhaps that adds more headache on those vendors that try to differentiate from competition and on those clients that are completely uncertain how to embrace this database technology. The Hype Around Graph Databases And Why It Matters. Organizations are struggling with a fundamental challenge – there’s far more data than they can handle.

The Hype Around Graph Databases And Why It Matters

Sure, there’s a shared vision to analyze structured and unstructured data in support of better decision making but is this a reality for most companies? The big data tidal wave is transforming the database management industry, employee skill sets, and business strategy as organizations race to unlock meaningful connections between disparate sources of data. Graph Databases are rapidly gaining traction in the market as an effective method for deciphering meaning but many people outside the space are unsure of what exactly this entails. Generally speaking, graph databases store data in a graph structure where entities are connected through relationships to adjacent elements. Introducing a Graph-based Semantic Layer in Enterprises. Things, not Strings Entity-centric views on enterprise information and all kinds of data sources provide means to get a more meaningful picture about all sorts of business objects.

Introducing a Graph-based Semantic Layer in Enterprises

This method of information processing is as relevant to customers, citizens, or patients as it is to knowledge workers like lawyers, doctors, or researchers. People actually do not search for documents, but rather for facts and other chunks of information to bundle them up to provide answers to concrete questions. Strings, or names for things are not the same as the things they refer to. Still, those two aspects of an entity get mixed up regularly to nurture the Babylonian language confusion. Its Time to Unleash the Semantic Layer. This post first appeared on the i Think blog.

Its Time to Unleash the Semantic Layer

What is the semantic layer you ask? The semantic layer is the underpinning of modern business intelligence platforms. Vendors with robust semantic capabilities command more than 50% of a $14 billion plus market: Source: Gartner Worldwide BI Market Share *(SAS - not sure if they offer a semantic layer in the classical sense - please let me know in the comments) Trillion Triple Semantic Database. The Semantic Web is an idea of World Wide Web inventor Tim Berners-Lee where the web captures the semantics, or meaning, of data, and where machines are enabled to interact with that meta data.

Trillion Triple Semantic Database

Berners-Lee observes that although search engines index much of the Web's content, keywords only provide an indirect association of the meaning that human actors are seeking. He foresees a number of ways in which developers and authors, singly or in collaborations, can use self-descriptions and other techniques so that context-understanding programs can selectively find what users want. Introducing a Graph-based Semantic Layer in Enterprises. Things, not Strings Entity-centric views on enterprise information and all kinds of data sources provide means to get a more meaningful picture about all sorts of business objects. This method of information processing is as relevant to customers, citizens, or patients as it is to knowledge workers like lawyers, doctors, or researchers. People actually do not search for documents, but rather for facts and other chunks of information to bundle them up to provide answers to concrete questions.

Strings, or names for things are not the same as the things they refer to. Still, those two aspects of an entity get mixed up regularly to nurture the Babylonian language confusion. Sheet2RDF: a datasheet to RDF acquisition and transformation system. Sheet2RDF is a platform for acquisition and transformation of datasheets into RDF, developed by the ART Research Group at the University of Rome Tor Vergata Sheet2rdf is built on top of our flagship platform for automatic knowledge acquisition and triplification CODA, and is specifically targeted towards the acquisition and processing of information from datasheets, in order to generate RDF content modeled according to any target RDF vocabulary.

The platform supports Microsoft Excel, Apache OpenOffice and LibreOffice spreadsheets (through Apache POI and jOpenDocument), as well as CSV, TSV and other delimited formats (through Commons CSV). Convert Excel to RDF. Semantic Web - Wikipedia. The Semantic Web is an extension of the Web through standards by the World Wide Web Consortium (W3C).[1] The standards promote common data formats and exchange protocols on the Web, most fundamentally the Resource Description Framework (RDF). According to the W3C, "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries".[2] The term was coined by Tim Berners-Lee for a web of data that can be processed by machines.[3] While its critics have questioned its feasibility, proponents argue that applications in industry, biology and human sciences research have already proven the validity of the original concept.[4] Maybe later |Close.