Translation resources and translator disempowerment

Language resources used for machine translation are created by human translators. These translators have legal rights with regard to copyright ownership of translated texts and databases of parallel bilingual texts, but may not be in a position to assert these rights due to employment practices widespread in the translation industry. This paper examines these employment practices in detail, and looks at the legal situation for ownership of translation resources. It also considers the situation from the standpoint of current owners of resources

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

AGROVOC: The linked data concept hub for food and agriculture

Newly acquired, aggregated and shared data are essential for innovation in food and agriculture to improve the discoverability of research. Since the early 1980′s, the Food and Agriculture Organization of the United Nations (FAO) has coordinated AGROVOC, a valuable tool for data to be classified homogeneously, facilitating interoperability and reuse. AGROVOC is a multilingual and controlled vocabulary designed to cover concepts and terminology under FAO's areas of interest. It is the largest Linked Open Data set about agriculture available for public use and its highest impact is through facilitating the access and visibility of data across domains and languages. This chapter has the aim of describing the current status of one of the most popular thesaurus in all FAO’s areas of interest, and how it has become the Linked Data Concept Hub for food and agriculture, through new procedures put in plac

FAIR Metadata Standards for Low Carbon Energy Research—A Review of Practices and How to Advance

The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders

Using RDF to Describe and Link Social Science Data to Related Resources on the Web

Kramer S, Leahey A, Southall H, Vompras J, Wackerow J. Using RDF to Describe and Link Social Science Data to Related Resources on the Web. DDI Working Paper Series. Dagstuhl, Germany: DDI Alliance; 2012.This document focuses on how best to relate Resource Description Framework (RDF)-described datasets to other related resources and objects (publications, geographies, organizations, people, etc.) in the Semantic Web. This includes a description of what would be needed to make these types of relationships most useful, including which RDF vocabularies should be used, potential link predicates, and possible data sources. RDF provides a good model for describing social science data because it supports formal semantics that provide a dependable basis for reasoning about the meaning of an RDF expression. In particular, it supports defined notions of entailment which provide a basis for defining reliable rules of inference in RDF data. Our findings are discussed in the context of social science data and more specifically, how to leverage existing metadata models to use alongside linked data. We provide a case for leveraging the Data Documentation Initiative (DDI) to enable semantic linking of social science data to other data and related resources on the Web. This document is organized into five use cases, which we consider in turn. Use cases include: linking related publications to data, linking data about people and organizations to research data, linking geography, linking to related studies, and linking data to licenses. We briefly discuss emerging or known issues surrounding the potential use of linked data within each of the defined use cases. Following these, we list more topics that could develop into additional use cases. Appendix A lists elements from the DDI-Codebook and DDI-Lifecycle specifications that are relevant to each use case

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Cross-Platform Text Mining and Natural Language Processing Interoperability - Proceedings of the LREC2016 conference

No abstract available

Cross-Platform Text Mining and Natural Language Processing Interoperability - Proceedings of the LREC2016 conference

No abstract available