Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
4
result(s) for
"Williams, John Alden translator"
Sort by:
The Egyptian Peasant
Egypt has changed enormously in the last half century, and nowhere more so than in the villages of the Nile Valley. Electrification, radio, and television have brought the larger world into the houses. Government schools have increased educational horizons for the children. Opportunities to work in other areas of the Arab world have been extended to peasants as well as to young artisans from the towns. Urbanization has brought many families to live in the belts of substandard housing around the major cities. But the conservative and traditional world of unremitting labor that characterizes the lives of the Egyptian peasants, or fellaheen, also survives, and nowhere has it been better described than in this classic account by Father Henry Habib Ayrout, an Egyptian Jesuit sociologist who dedicated most of his life to creating a network of free schools for rural children at a time when there were very few. First published in French in 1938, the book went through several revisions by the author before being translated and published in English in 1963. The often poetic yet factual and deeply empathetic description Father Ayrout left of fellah life is still reliable and still poignant; a measure by which the progress of the countryside must always be gauged.
eBook
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science
Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph‐based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these “knowledge graphs” (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open‐access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open‐source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object‐oriented classification and graph‐oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.
Journal Article
Progress toward a universal biomedical data translator
Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well‐being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline‐specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph‐based “Translator” system capable of integrating existing biomedical data sets and “translating” those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system’s architecture, performance, and quality of results. We apply Translator to several real‐world use cases developed in collaboration with subject‐matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state‐of‐the‐art, biomedical graph‐based question‐answering systems.
Journal Article