”Tænke? Abstrakt? Red sig, hvem der kan!”

Nærværende tekst undersøger spørgsmålet om, hvorvidt og hvordan abstraktioner har en plads i det praktiske og professionelle arbejde. Vi argumenterer for, abstraktioner er uomgængelige, og at vi altid allerede er i gang med at bruge abstraktioner, begreber og kategorier, når vi handler. Samtidig beskriver vi brugen af en særlig type abstraktioner, de såkaldt ”lokkende abstraktioner”, som vi hævder, er animerende for praksis. Første del af teksten, ”Abstraktioner i praksis”, tager udgangspunkt i forholdet mellem det filosofiske og begrebslige over for det praktiske. Denne del knytter an til den tyske filosof G.W.F. Hegels klassiske lille tekst ”Hvem tænker abstrakt?” Spørgsmålet om det abstrakte bringes i kontakt med professionernes diskussioner af forholdet mellem teori og praksis, ligesom det sættes ind i en idéhistorisk ramme. Anden del af teksten, ”Praktiske abstraktioner”, tager udgangspunkt i den belgiske videnskabsteoretiker Isabelle Stengers og hendes behandling af abstraktioner og det, de gør for os i både hverdagslige og videnskabelige erkendelsesprocesser. Denne del af teksten formulerer, hvad man skal forstå ved lokkende abstraktioner, og bringer i særlig grad disse i diskussion med det herskende professionelle vidensideal om anvendelighed

”Tænke? Abstrakt? Red sig, hvem der kan!”: om abstraktion og professioner

Nærværende tekst undersøger spørgsmålet om, hvorvidt og hvordan abstraktioner har en plads i det praktiske og professionelle arbejde. Vi argumenterer for, abstraktioner er uomgængelige, og at vi altid allerede er i gang med at bruge abstraktioner, begreber og kategorier, når vi handler. Samtidig beskriver vi brugen af en særlig type abstraktioner, de såkaldt ”lokkende abstraktioner”, som vi hævder, er animerende for praksis. Første del af teksten, ”Abstraktioner i praksis”, tager udgangspunkt i forholdet mellem det filosofiske og begrebslige over for det praktiske. Denne del knytter an til den tyske filosof G.W.F. Hegels klassiske lille tekst ”Hvem tænker abstrakt?” Spørgsmålet om det abstrakte bringes i kontakt med professionernes diskussioner af forholdet mellem teori og praksis, ligesom det sættes ind i en idéhistorisk ramme. Anden del af teksten, ”Praktiske abstraktioner”, tager udgangspunkt i den belgiske videnskabsteoretiker Isabelle Stengers og hendes behandling af abstraktioner og det, de gør for os i både hverdagslige og videnskabelige erkendelsesprocesser. Denne del af teksten formulerer, hvad man skal forstå ved lokkende abstraktioner, og bringer i særlig grad disse i diskussion med det herskende professionelle vidensideal om anvendelighed

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

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