Global patterns of fern species diversity:An evaluation of fern data in GBIF

Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility(GBIF)are not appropriate for those ecological and biogeographic studies that require high sampling completeness,because species lists derived from GBIF are generally very incomplete,Suissa et al.(2021)generated fern species lists based on data with GBIF for 100 km×100 km grid cells across the world,and used the data to determine fern diversity hotspots and species richness-climate relationships.We conduct an evaluation on the completeness of fern species lists derived from GBIF at the grid-cell scale and at a larger spatial scale,and determine whether fern data derived from GBIF are appropriate for studies on the relations of species composition and richness with climatic variables.We show that species sampling completeness of GBIF is low(<40%)for most of the grid cells examined,and such low sampling completeness can substantially bias the investigation of geographic and ecological patterns of species diversity and the identification of diversity hotspots.We conclude that fern species lists derived from GBIF are generally very incomplete across a wide range of spatial scales,and are not appropriate for studies that require data derived from species lists in high completeness.We present a map showing global patterns of fern species diversity based on complete or nearly complete regional fern species lists.

What Does Information Science Offer for Data Science Research?:A Review of Data and Information Ethics Literature

This paper reviews literature pertaining to the development of data science as a discipline,current issues with data bias and ethics,and the role that the discipline of information science may play in addressing these concerns.Information science research and researchers have much to offer for data science,owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines.Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades.This review article serves as a reference for the history,current progress,and potential future directions of data ethics research within the corpus of information science literature.

Role of big data in reducing the bias of a cohort study

Validity in research is referred to the closeness of the observed results to the truth or the degree to which an inference drawn from a study.1 Guarantee and pursuit of validity is always a challenge through the whole course of a research.What blocks research to reach validity？-Bias.Generally speaking,the more complicate the study is,the larger the bias and the lower the validity are.The cohort study,especially for a prospective cohort study,is a kind of epidemiological study which can provide strong evidences for medical practices and policy-making.