preVIEW: from a fast prototype towards a sustainable semantic search system for central access to COVID-19 preprints

The current COVID-19 pandemic emphasizes the use of so-called preprints - a type of publication that is not subject to peer review. Due to its global relevance, there is an immense number of COVID-19-related preprints every day. To help researchers find relevant information, we have developed the semantic search engine preVIEW, it integrates preprints from currently seven different preprint servers. For semantic indexing, we implemented various text mining components to tag, for example, diseases or SARS-CoV-2 specific proteins. While the service initially served as a prototype developed together with users, we present a re-engineering towards a sustainable semantic search system, which was inevitable due to the continuously growing number of preprint publications. This enables easy reuse of the components and allows rapid adaptation of the service to further user needs

Medizinbibliothekarische Bibliografie 2017

The Medical Librarian’s Bibliography 2017 lists all articles from GMS Medizin – Bibliothek – Information and selected publications relevant to medical librarians from following journals: ABI Technik, Bibliothek Forschung und Praxis, Bibliotheksdienst, B.I.T. online, BuB: Forum Bibliothek und Information, Information – Wissenschaft & Praxis, Journal of EAHIL: European Association for Health Information and Libraries, Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare, o-bib. Das offene Bibliotheksjournal, Zeitschrift für Bibliothekswesen & Bibliographie

How specificity and presentation of data affect our rational decision-making ability, oriented to a pharmaceutical perspective.

This dissertation aims to show the influence of factors on our perception and consequent evaluation of data, respectively our assessment of situations. Furthermore, it deals with the question to what extent rationally abstracted processes are common in the medical-pharmaceutical field. Overall, this dissertation indicates that limited evidence of abstracted approaches in the medical-pharmaceutical context can be found. Furthermore it is shown that drug evaluations, in particular the risk evaluation( even in itself) , are subject to strong subjective factors that distort the results.Ziel dieser Arbeit ist es, den Einfluss von Faktoren auf unsere Wahrnehmung und die daraus resultierende Bewertung von Daten und Situationen aufzuzeigen. Ergänzend, inwieweit rationale abstrahierte Prozesse im medizinisch-pharmazeutischen Bereich üblich sind. Insgesamt zeigt die Dissertation, dass abstrahierende Ansätze im medizinisch-pharmazeutischen Kontext nur in begrenztem Umfang zu finden sind. Außerdem wird gezeigt, dass Arzneimittelbewertungen, insbesondere die Risikobewertung (auch an sich), starken subjektiven Faktoren unterliegen, die die Ergebnisse verzerren

User-centered semantic dataset retrieval

Finding relevant research data is an increasingly important but time-consuming task in daily research practice. Several studies report on difficulties in dataset search, e.g., scholars retrieve only partial pertinent data, and important information can not be displayed in the user interface. Overcoming these problems has motivated a number of research efforts in computer science, such as text mining and semantic search. In particular, the emergence of the Semantic Web opens a variety of novel research perspectives. Motivated by these challenges, the overall aim of this work is to analyze the current obstacles in dataset search and to propose and develop a novel semantic dataset search. The studied domain is biodiversity research, a domain that explores the diversity of life, habitats and ecosystems. This thesis has three main contributions: (1) We evaluate the current situation in dataset search in a user study, and we compare a semantic search with a classical keyword search to explore the suitability of semantic web technologies for dataset search. (2) We generate a question corpus and develop an information model to figure out on what scientific topics scholars in biodiversity research are interested in. Moreover, we also analyze the gap between current metadata and scholarly search interests, and we explore whether metadata and user interests match. (3) We propose and develop an improved dataset search based on three components: (A) a text mining pipeline, enriching metadata and queries with semantic categories and URIs, (B) a retrieval component with a semantic index over categories and URIs and (C) a user interface that enables a search within categories and a search including further hierarchical relations. Following user centered design principles, we ensure user involvement in various user studies during the development process

Information between Data and Knowledge: Information Science and its Neighbors from Data Science to Digital Humanities

Digital humanities as well as data science as neighboring fields pose new challenges and opportunities for information science. The recent focus on data in the context of big data and deep learning brings along new tasks for information scientist for example in research data management. At the same time, information behavior changes in the light of the increasing digital availability of information in academia as well as in everyday life. In this volume, contributions from various fields like information behavior and information literacy, information retrieval, digital humanities, knowledge representation, emerging technologies, and information infrastructure showcase the development of information science research in recent years. Topics as diverse as social media analytics, fake news on Facebook, collaborative search practices, open educational resources or recent developments in research data management are some of the highlights of this volume. For more than 30 years, the International Symposium of Information Science has been the venue for bringing together information scientists from the German speaking countries. In addition to the regular scientific contributions, six of the best competitors for the prize for the best information science master thesis present their work

LIVIVO – the Vertical Search Engine for Life Sciences

The explosive growth of literature and data in the life sciences challenges researchers to keep track of current advancements in their disciplines. Novel approaches in the life science like the One Health paradigm require integrated methodologies in order to link and connect heterogeneous information from databases and literature resources. Current publications in the life sciences are increasingly characterized by the employment of trans-disciplinary methodologies comprising molecular and cell biology, genetics, genomic, epigenomic, transcriptional and proteomic high throughput technologies with data from humans, plants, and animals. The literature search engine LIVIVO empowers retrieval functionality by incorporating various literature resources from medicine, health, environment, agriculture and nutrition. LIVIVO is developed in-house by ZB MED – Information Centre for Life Sciences. It provides a user-friendly and usability-tested search interface with a corpus of 55 Million citations derived from 50 databases. Standardized application programming interfaces are available for data export and high throughput retrieval. The search functions allow for semantic retrieval with filtering options based on life science entities. The service oriented architecture of LIVIVO uses four different implementation layers to deliver search services. A Knowledge Environment is developed by ZB MED to deal with the heterogeneity of data as an integrative approach to model, store, and link semantic concepts within literature resources and databases. Future work will focus on the exploitation of life science ontologies and on the employment of NLP technologies in order to improve query expansion, filters in faceted search, and concept based relevancy rankings in LIVIVO