The current coronavirus disease 2019 (COVID-19) pandemic is making fundamental changes to our life, our society, and our thinking. The substantial influx of information on disease updates, case analysis, suggestions, and recordings leads one to contemplate what information professionals and information scientists can contribute to shorten the pandemic, improve human lives, and build a more impactful profession. This viewpoint examines concepts related to misinformation and discusses the responsibilities of information scientists, especially in the context of independent thinking. It suggests that research on and education in information science could help to develop independent thinking and train independent thinkers.
The research on knowledge diffusion in the field of intellectual property is growing based on the current research techniques, but it is mostly focused on some of the subfields, such as patent documents and technology transfer. What is lacking in the literature is a comprehensive profile of the discipline. The paper uses bibliometric methods and visualization technologies to conduct a profiling analysis of Web of Science journal articles in the field of intellectual property from the three aspects of authorship network, geographical diffusion of collaboration, and subject cluster. Facilitated by visualization software and programming scripts, the paper presents the highly active scholars in the field through author co-citation analysis (ACA) and document co-citation analysis (DCA), the diffusion networks of collaboration through dynamic geographical graphs, and the five main clusters of disciplinary subjects, namely, Innovation, Judicature, Legislation, Information, and Market.
During the coronavirus global pandemic crisis, we have received information from authentic and inauthentic sources. Fake news, continuous rumors, and prejudiced opinions from digital platforms and social media have the capacity to disrupt social harmony, to stall personal development, and to undermine trust on all levels of human interaction. Despite the wide plurality of perspectives, the diversity of contents, the variety of voices, and the many often-conflicting reasons for publishing, our interactions with information on digital devices are progressively shaping such situations and affecting decisions on all levels. We look at the limitations of existing designs and guidelines in the current paradigm, and we ask to what extent researchers and developers can focus and contribute, through their innovations, to the reduction of uncertainty and cases of misdirection, how they can mitigate tensions between information and humans, and how they can contribute to the maintenance and enhancement of worthy human values. Human-engaged computing (HEC) calls for innate user capacities to be enhanced rather than displaced by digital technologies so that the human factor in interactions is fully exploited and truly efficient symbiotic relationships between humans and devices can be achieved. Under the framework of HEC, we propose 12 research agendas from the theoretical, principled, and practical aspects, in order to develop future synergized interactions between humans and information. The present crisis presents us with a good opportunity to reflect on the need to empower humans in relation to the tools they use and to consider the next paradigm shift for designing information interaction.
Information release is an important way for governments to deal with public health emergencies, and plays an irreplaceable role in promoting epidemic prevention and control, enhancing public awareness of the epidemic situation and mobilizing social resources. Focusing on the coronavirus disease 2019 (COVID-19) epidemic in China, this investigation chose 133 information release accounts of the Chinese government and relevant departments at the national, provincial, and municipal levels, including Ministries of the State Council, Departments of Hubei Province Government, and Bureaus of Wuhan Government, covering their portals, apps, Weibos, and WeChats. Then, the characteristics such as scale, agility, frequency, originality, and impact of different levels, departments, and channels of the information releases by the Chinese government on the COVID-19 epidemic were analyzed. Finally, the overall situation was concluded by radar map analysis. It was found that the information release on the COVID-19 epidemic was coordinated effectively at different levels, departments, and channels, as evidenced by the complementarity between channels, the synergy between the national and local governments, and the coordination between departments, which guaranteed the rapid success of the epidemic prevention and control process in China. This investigation could be a reference for epidemic prevention and control for governments and international organizations, such as the World Health Organization (WHO), during public health emergencies, e.g. the COVID-19 pandemic.
The COVID-19 outbreak is a global pandemic declared by the World Health Organization, with rapidly increasing cases in most countries. A wide range of research is urgently needed for understanding the COVID-19 pandemic, such as transmissibility, geographic spreading, risk factors for infections, and economic impacts. Reliable data archive and sharing are essential to jump-start innovative research to combat COVID-19. This research is a collaborative and innovative effort in building such an archive, including the collection of various data resources relevant to COVID-19 research, such as daily cases, social media, population mobility, health facilities, climate, socioeconomic data, research articles, policy and regulation, and global news. Due to the heterogeneity between data sources, our effort also includes processing and integrating different datasets based on GIS (Geographic Information System) base maps to make them relatable and comparable. To keep the data files permanent, we published all open data to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/2019ncov), an online data management and sharing platform with a permanent Digital Object Identifier number for each dataset. Finally, preliminary studies are conducted based on the shared COVID-19 datasets and revealed different spatial transmission patterns among mainland China, Italy, and the United States.
The novel coronavirus disease (COVID-19) has caused a pandemic and global health crisis. Although normal operation and services in many libraries have been greatly disrupted, academic libraries in the United States were reportedly responding to challenges by pivoting to new ways to meet the users’ needs. This observational study was designed to investigate the status, services, and resources disclosed via websites of academic medical/health sciences libraries (MHSLs) in the United States and document how they adapted and continued to provide support to help fight the health crisis and the resulting “infodemic” through various means. A complete list of members was obtained from the website of the Association of Academic Health Sciences Libraries (AAHSL). The U.S.-based AAHSL member institutions were included in this study. Each American academic MHSL website and its associated webpages were browsed; web contents were categorized and analyzed based on four research questions proposed by this study. A descriptive analysis was conducted to summarize all findings. A total of 157 AAHSL member institutions were included in the study. These libraries spread all over the United States, and 90% of them announced closures of library buildings and facilities. A significant number of MHSLs quickly adapted to the evolving situation and transitioned their services and instruction to the online environment. The COVID-19 information sources adopted by MHSLs included the following ranked by frequency from high to low: The U.S. government agencies such as Centers for Disease Control and Prevention and National Library of Medicine, the World Health Organization, publishing communities, professional journals, organizations, local institutions, government agencies, and news channels. In addition, MHSLs undertook a series of actions to support academic communities and local healthcare professionals including resource curation, clinical care support, education, and outreach to the public. Through library guides, MHSLs provided comprehensive and customized search queries to help researchers locate the latest and relevant publications to COVID-19, curated multiple data resources and data exploration, and visualization tools, and selected the latest biomedical and health evidence in a wide range of topics. Other featured resources and services were associated with ethical issues (i.e., racism and prejudice), educational and entertainment information (e.g., virtual tours of parks), and personal experience documentation. This observational study is the most recent investigation and documentation on the status, services, and resources of the academic MHSLs in the United States during the initial U.S. outbreak of the COVID-19 pandemic. Although the current health crisis is taking a heavy toll on libraries nationwide, MHSLs are still managing to play a vital role in supporting the academic communities, healthcare facilities, and the general public and fighting against the pandemic and the resulting information crisis.
Academic collections, such as COVID-19 Open Research Dataset (CORD-19), contain a large number of scholarly articles regarding COVID-19 and other related viruses. These articles represent the latest development in combating COVID-19 pandemic in various disciplines. However, it is difficult for laypeople to access these articles due to the term mismatch problem caused by their limited medical knowledge. In this article, we present an effort of helping laypeople to access the CORD-19 collection by translating and expanding laypeople's keywords to their corresponding medical terminology using the National Library of Medicine's Consumer Health Vocabulary. We then developed a retrieval system called Search engine for Laypeople to access the COVID-19 literature (SLAC) using open-source software. Utilizing Centers for Disease Control and Prevention's FAQ questions as the basis for developing common questions that laypeople could be interested in, we performed a set of experiments for testing the SLAC system and the translation and expansion (T&E) process. Our experiment results demonstrate that the T&E process indeed helped to overcome the term mismatch problem and mapped laypeople terms to the medical terms in the academic articles. But we also found that not all laypeople's search topics are meaningful to search on the CORD-19 collection. This indicates the scope and the limitation of enabling laypeople to search on academic article collection for obtaining high-quality information.
As the availability of data is increasing everyday, the need to reflect on how to make these data meaningful and impactful becomes vital. Current data paradigms have provided data life cycles that often focus on data acumen and data stewardship approaches. In an effort to examine the convergence, tensions, and harmonies of these two approaches, a group of researchers participated in an interactive panel session at the Association of Information Science and Technology Annual meeting in 2019. The panel presenters described their various research activities in which they confront the challenges of the computational and social perspectives of the data continuum. This paper provides a summary of this interactive panel.
Information behavior, as a part of human behavior, has many aspects, including a cognitive aspect. Cognitive biases, one of the important issues in psychology and cognitive science, can play a critical role in people’s behaviors and their information behavior. This article discusses the potential relationships between some concepts of human information behavior and cognitive biases. The qualitative research included semistructured face-to-face interviews with 25 postgraduate students who were at the writing-up stage of their research. The participants were selected using a purposeful sampling process. Interviews were analyzed using the coding technique of classic grounded theory. The research framework was the Eisenberg and Berkowitz information behavior model. The relationships that are discussed in this article include those between the principle of least effort on the one hand and availability bias and ambiguity aversion on the other; value-sensitive design and reactance; willingness to return and availability bias; library anxiety and ambiguity aversion, status quo bias, and stereotypical bias; information avoidance and selective perception, confirmation bias, stereotypical bias, and conservatism bias; information overload and information bias; and finally, filtering and attentional bias.