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In December 2020, the second edition of the Handbook for Scientometrics: Science and Technology Development Indicators will be published. Over the six years since the release of the first edition, interest in scientometrics and its practical application has noticeably grown in Russia, and Russian centers for scientometrics have appeared. The introduction for the new edition is of interest itself. The Russian version is published with the kind permission of the copyright holder, Clarivate Analytics.

This paper presents an analysis of the Overton policy document database, describing the makeup of materials indexed and the nature in which they cite academic literature. We report on various aspects of the data, including growth, geographic spread, language representation, the range of policy source types included, and the availability of citation links in documents. Longitudinal analysis over established journal category schemes is used to reveal the scale and disciplinary focus of citations and determine the feasibility of developing field-normalized citation indicators. To corroborate the data indexed, we also examine how well self-reported funding outcomes collected by UK funders correspond to data indexed in the Overton database. Finally, to test the data in an experimental setting, we assess whether peer-review assessment of impact as measured by the UK Research Excellence Framework (REF) 2014 correlates with derived policy citation metrics. Our findings show that for some research topics, such as health, economics, social care, and the environment, Overton contains a core set of policy documents with sufficient citation linkage to academic literature to support various citation analyses that may be informative in research evaluation, impact assessment, and policy review.

Many academic analyses of good practice in the use of bibliometric data address only technical aspects and fail to account for and appreciate user requirements, expectations, and actual practice. Bibliometric indicators are rarely the only evidence put before any user group. In the present state of knowledge, it is more important to consider how quantitative evaluation can be made simple, transparent, and readily understood than it is to focus unduly on precision, accuracy, or scholarly notions of purity. We discuss how the interpretation of ‘performance’ from a presentation using accurate but summary bibliometrics can change when iterative deconstruction and visualization of the same dataset is applied. From the perspective of a research manager with limited resources, investment decisions can easily go awry at governmental, funding program, and institutional levels. By exploring select real-life data samples we also show how the specific composition of each dataset can influence interpretive outcomes.

OpenVIVO is a free and open-hosted semantic web platform that anyone can join and that gathers and shares open data about scholarship in the world. OpenVIVO, based on the VIVO open-source platform, provides transparent access to data about the scholarly work of its participants. OpenVIVO demonstrates the use of persistent identifiers, the automatic real-time ingest of scholarly ecosystem metadata, the use of VIVO-ISF and related ontologies, the attribution of work, and the publication and reuse of data—all critical components of presenting, preserving, and tracking scholarship. The system was created by a cross-institutional team over the course of 3 months. The team created and used RDF models for research organizations in the world based on Digital Science GRID data, for academic journals based on data from CrossRef and the US National Library of Medicine, and created a new model for attribution of scholarly work. All models, data, and software are available in open repositories.

Background Social media promotion is increasingly adopted by organizers of industry and academic events; however, the success of social media strategies is rarely questioned or the real impact scientifically analyzed. Objective We propose a framework that defines and analyses the impact, outreach, and effectiveness of social media for event promotion and research dissemination to participants of a scientific event as well as to the virtual audience through the Web. Methods Online communication channels Twitter, Facebook, Flickr, and a Liveblog were trialed and their impact measured on outreach during five phases of an eHealth conference: the setup, active and last-minute promotion phases before the conference, the actual event, and after the conference. Results Planned outreach through online channels and social media before and during the event reached an audience several magnitudes larger in size than would have been possible using traditional means. In the particular case of eHealth 2011, the outreach using traditional means would have been 74 attendees plus 23 extra as sold proceedings and the number of downloaded articles from the online proceedings (4107 until October 2013). The audience for the conference reached via online channels and social media was estimated at more than 5300 in total during the event. The role of Twitter for promotion before the event was complemented by an increased usage of the website and Facebook during the event followed by a sharp increase of views of posters on Flickr after the event. Conclusions Although our case study is focused on a particular audience around eHealth 2011, our framework provides a template for redefining “audience” and outreach of events, merging traditional physical and virtual communities and providing an outline on how these could be successfully reached in clearly defined event phases.

Much attention has been focused on Twitter because it serves as a central hub for the publishing, dissemination, and discovery of online media. This is true for both traditional news outlets and user generated content, both of which can vary widely in their journalistic and scientific quality. The recent Swine Flu pandemic of 2009 highlighted this aspect perfectly, global events that created a large online buzz, with some dubious medical facts leaking into public opinion. This paper presents an investigation into how online resources relating to Swine Flu were discussed on Twitter, with a focus on identifying and analyzing the popularity of trusted information sources (e.g. from quality news outlets and official health agencies). Our findings indicate that reputable sources are more popular than untrusted ones, but that information with poor scientific merit can still leak into to the network and potentially cause harm.

International audience; Popularity and spread of online social networking in recent years has given a great momentum to the study of dynamics and patterns of social interactions. However, these studies have often been confined to the online world, neglecting its interdependencies with the offline world. This is mainly due to the lack of real data that spans across this divide. The Live Social Semantics application is a novel platform that dissolves this divide, by collecting and integrating data about people from (a) their online social networks and tagging activities from popular social networking sites, (b) their publications and co-authorship networks from semantic repositories, and (c) their real-world face-to-face contacts with other attendees collected via a network of wearable active sensors. This paper investigates the data collected by this application during its deployment at three major conferences, where it was used by more than 400 people. Our analyses show the robustness of the patterns of contacts at various conferences, and the influence of various personal properties (e.g. seniority, conference attendance) on social networking patterns.

This paper describes an Open Linked Data back- linking service, a generic architecture component to support the discovery of useful links between items across highly connected data sets. Using Public Sector Information (PSI) currently available as Linked Data, we demonstrate that contemporary publishing practices do not adequately support the ability to navigate or automatically traverse between resources published by different vendors, or the capacity to discover information relevant to a particular URI. Although some useful services in this area have been developed, such as large triple indexes of published data, and the collection of sameAs relationships between individuals, we believe that an important component is missing: a mechanism to discover the backlinks to relevant resources that cannot be found by direct URI resolution. We present the implementation of such a component, integrating data from various PSI sources.