Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Seniors | Class of \u2712

PLEASE NOTE: Where applicable, the audio has been removed from this file due to copyrighted material. The garments shown here represent the Senior Class of \u2712. The garments were created in response to the following design challenges: Concepts in Color Collection: design a collection based on an individual concept with a focus on color and texture. Senior Thesis Collection: create a collection that reflects the essence and philosophies of your personal vision

Five Design Challenges

PLEASE NOTE: Where applicable, the audio has been removed from this file due to copyrighted material. The garments shown here represent the Classes of \u2713, \u2712 and \u2711 . The garments were created in response to the following five design challenges: Sophomores, Class of \u2713: Re-Innovative Design: explore the properties of recycled materials other than fabric while creating a wearable piece. Print Design Project create a garment that makes optimal use of printed fabric designed by a RISD Textiles student. Juniors, Class of \u2712: Knitwear Design: explore the properties of knits and design cut-and-sew and machine-knit garments. Tailoring Project: interpret traditional tailoring techniques to create a look with a jacket. Seniors, Class of \u2711: Cocktail Collection: design a collection of contemporary cocktail apparel in collaboration with the current RISD Museum exhibition Cocktail Culture: Ritual and Invention in American Fashion, 1920-1980

Five Design Challenges

PLEASE NOTE: Where applicable, the audio has been removed from this file due to copyrighted material. The garments shown here represent the Classes of \u2712, \u2711 and \u2710 . The garments were created in response to the following five design challenges: Sophomores, Class of \u2712: Re-Innovative Design: explore the properties of recycled materials other than fabric while creating a wearable piece. Print Design Project create a garment that makes optimal use of an assigned printed fabric. Juniors, Class of \u2710: Knitwear Design: explore the properties of knits and design cut-and-sew and machine-knit garments. Tailoring Project: interpret traditional tailoring techniques to create a look with a jacket. Seniors, Class of \u2709: Coat Collection: design a collection with a coat as the key piece

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press