Linked education: interlinking educational resources and the web of data

Research on interoperability of technology-enhanced learning (TEL) repositories throughout the last decade has led to a fragmented landscape of competing approaches, such as metadata schemas and interface mechanisms. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de-facto standard for sharing data on the Web and offers a large potential to solve interoperability issues in the field of TEL. In this paper, we describe a general approach to exploit the wealth of already existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. This approach has been implemented in the context of the mEducator project where data from a number of open TEL data repositories has been integrated, exposed and enriched by following Linked Data principles

Linking Data Across Universities: An Integrated Video Lectures Dataset

This paper presents our work and experience interlinking educational information across universities through the use of Linked Data principles and technologies. More specifically this paper is focused on selecting, extracting, structuring and interlinking information of video lectures produced by 27 different educational institutions. For this purpose, selected information from several websites and YouTube channels have been scraped and structured according to well-known vocabularies, like FOAF 1, or the W3C Ontology for Media Resources 2. To integrate this information, the extracted videos have been categorized under a common classification space, the taxonomy defined by the Open Directory Project 3. An evaluation of this categorization process has been conducted obtaining a 98% degree of coverage and 89% degree of correctness. As a result of this process a new Linked Data dataset has been released containing more than 14,000 video lectures from 27 different institutions and categorized under a common classification scheme

Addressing India’s water challenge 2050: the virtual water trade option

The Government of India, on directions from the Supreme Court in 2002 and advice from the National Water Development Agency (NWDA), proposed an estimated US$120 billion National River Linking Project (NRLP) which envisages linking 37 Himalayan and Peninsular rivers (Figure 1; NCIWRD 1999). Doing this will form a gigantic South Asian water grid which will annually handle 178×109 m3/yr of interbasin water transfer; build 12,500 km of canals; generate 34 gigawatts of hydropower; add 35 million hectares (Mha) to India’s irrigated areas; and generate inland navigation benefits (IWMI 2003; NWDA 2006; Gupta and van der Zaag 2007)

Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

Going against the flow: A critical analysis of virtual water trade in the context of India's National River Linking Programme

Virtual water trade has been promoted as a tool to address national and regional water scarcity. In the context of international (food) trade, this concept has been applied with a view to optimize the flow of commodities considering the water endowments of nations. The concept states that water-rich countries should produce and export water intensive commodities (which indirectly carry embedded water needed for producing them) to water-scarce countries, thereby enabling the water-scarce countries to divert their precious water resources to alternative, higher productivity uses.\ud While progress has been made on quantifying virtual water flows between countries, there exists little information on virtual water trade within large countries like India. This report quantifies and critically analyzes inter-state virtual water flows in India in the context of a large inter-basin transfer plan of the Government of India.\ud Our analysis shows that the existing pattern of inter-state virtual water trade is exacerbating scarcities in already water scarce states and that rather than being dictated by water endowments, virtual water flows are influenced by other factors such as "per capita gross cropped area" and "access to secured markets". We therefore argue that in order to have a comprehensive understanding of virtual water trade, non-water factors of production need to be taken into consideration

Seshat: The Global History Databank

The vast amount of knowledge about past human societies has not been systematically organized and, therefore, remains inaccessible for empirically testing theories about cultural evolution and historical dynamics. For example, what evolutionary mechanisms were involved in the transition from the small-scale, uncentralized societies, in which humans lived 10,000 years ago, to the large-scale societies with an extensive division of labor, great differentials in wealth and power, and elaborate governance structures of today? Why do modern states sometimes fail to meet the basic needs of their populations? Why do economies decline, or fail to grow? In this article, we describe the structure and uses of a massive databank of historical and archaeological information, Seshat: The Global History Databank. The data that we are currently entering in Seshat will allow us and others to test theories explaining how modern societies evolved from ancestral ones, and why modern societies vary so much in their capacity to satisfy their members’ basic human needsPeer reviewedFinal Published versio

Interlinking With Models for Predicting Weather and Climate Change

Meteorology has employed automatic computing machines since the early days of electronic computers. From the 1950s on, a large body of models used for “in silico” experiments (numerical simulation) has been built up, together with an international infrastructure of measuring, modeling, and testing. These outstanding developments— unique in science—led not only to an increasing standardization in developing and applying models but also to deepening the interlinking between modeling and generating evidence. The article explores needs and strategies for evaluating scientific results based on mass data output devices

TOWARDS DEMAND DRIVEN PUBLISHING: APPROCHES TO THE PRIORITISATION OF DIGITISATION OF NATURAL HISTORY COLLECTIONS DATA

Natural history collections represent a vast repository of biodiversity data of international significance. There is an imperative to capture the data through digitisation projects in order to expose the data to new and established users of biodiversity data. On the basis of review of current state of digitization of natural history collections, a demand driven approach is advocated through the use of metadata to promote and increase access to natural history collection data