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The purpose of this paper is to critically analyze the influence of the algorithm used on scholarly search engines (Garfield’s algorithm) and propose metrics to improve it so that science could be based on a more democratic way.

This paper used a snow-ball approach to collect data that allowed identifying the history and the logic behind the Garfield’s algorithm. It follows on excerpting the foundation of existing algorithm and databases of major scholarly search engine. It concluded proposing new metrics so as to surpass restraints and to democratize the scientific discourse.

This paper finds that the studied algorithm currently biases the scientific discourse toward a narrow perspective, while it should take into consideration several researchers’ characteristics. It proposes the substitution of the h-index by the number of times the scholar’s most cited work has been cited. Finally, it proposes that works in languages different than English should be included.

The broad comprehension of any phenomena should be based on multiple perspectives; therefore, the inclusion of diverse metrics will extend the scientific discourse.

The improvement of the existing algorithm will increase the chances of contact among different cultures, which stimulate rapid progress on the development of knowledge.

The value of this paper resides in demonstrating that the algorithm used in scholarly search engines biases the development of science. If updated as proposed here, science will be unbiased and bias aware.

The purpose of this paper is to explore commonalities and differences between projects and processes, and between project management (PjM) and process management (PcM), with a view to challenge this dichotomic typology, clarify the gray areas in between and propose better ways to classify and manage different endeavors.

The research compares different tools and techniques used in both fields, explores the respective literatures and uses various examples to bring out similarities and differences.

The current paradigms engender a number of organizational endeavors, which are actually complex processes being managed as projects, using the PjM body of knowledge. Because each instantiation takes a somewhat different form, it is treated as a one-of-a-kind undertaking; whereby many of the opportunities for learning and continuous improvement associated with PcM are lost. A reframing and typology is proposed to clarify the central notions involved.

The proposed model has not been tested empirically and the authors could not agree on all aspects of the paper, though existing differences are more about degrees, nuances and wording than about the basic findings of the paper.

The research makes the case that two research and practice communities that are evolving independently have much to gain by adopting a unified model and integrating their respective bodies of knowledge. Practitioners would thus access resources that are better adapted to the management challenges they are facing and gain a sustainable source of strategic advantage.

The paper challenges long-established paradigms between two distinct research streams. A new typology and classification criteria are proposed.

Attempts to deal with the issue of how we can educate the next generation of leaders for the information needs of the future.

Uses a case study: the thinking behind the new information science program at Cornell University.

Advocates a broad view of information science. In a rapidly changing world, leadership will come from flexible thinking based on a broad understanding of technology and the social sciences. In the American terminology, information science should be considered a liberal art, not a profession. An education in information science provides an excellent foundation for a career in libraries, publishing or information services, but there are many more career opportunities for somebody with this education.

Most recent initiatives in information science have come from professional schools of librarianship. By starting from a liberal arts viewpoint, universities may be meeting the needs of a very wide audience.

Seven years after the release of Google Scholar in 2004, it was enhanced by a new module, the Google Scholar Author Citation Tracker (GSACT), currently a small subset of the complete Google Scholar (GS) database. The aim of this paper is to focus on this enhancement.

The paper discusses the Google Scholar Author Citation Tracker, its features, potential benefits and problems.

GSACT allows registered users to create and edit their scientific profiles and some bibliometric indicators, such as the h‐index, total citation counts, and the i10 index. These metrics are provided for the entire academic career of authors and for the most recent five‐year period. The new module also offers some long overdue essential options, such as sorting result lists of the documents by their publication year, title, and the citations received

The paper shows that, at present, GSACT may be too little, too late. However, with an extension of the current clean‐up project it could possibly become a really scholarly resource in the long run.

The present study aims to investigate how textual features, depth of citation treatment, reasons for citation, and relationships between citers and citees predict author‐rated citation importance.

A total of 49 biology and 50 psychology authors assessed the importance, reason for citation, and relationship to the cited author for each cited reference in his or her own recently published empirical article. Participants performed their evaluations on individualized web‐based surveys.

The paper finds that certain textual features, such as citation frequency, citation length, and citation location, as well as author‐stated reasons for citation predicted ratings of importance, but the strength of the relationship often depended on citation features in the article as a whole. The relationship between objective citation features and author‐rated importance also tended to be weaker for self‐citations.

The study sample included authors of relatively long empirical articles with a minimum of 35 cited references. There were relatively few disciplinary differences, which suggests that citation behavior in psychology may be similar to that in natural science disciplines. Future studies should involve authors from other disciplines employing diverse referencing patterns in articles of varying lengths and types.

Findings of the study have enabled a comprehensive, profound level of understanding of citation behaviors of biology and psychology authors. It uncovered a number of unique characteristics in authors' citation evaluations, such as article‐level context effects and rule‐ versus affective‐based judgments. The paper suggests possible implications for developing retrieval algorithms based on automatically predicted importance of cited references.

This sequel to the earlier testing and evaluation of the five‐year Journal Impact Factor (JIF‐5) in the enhanced version of the Journal Citation Reports (JCR) (released in January and July 2009 for the 2007 and 2008 journal collections, respectively) seeks to assess and compare the impact on the ranking of journals by two other performance indicators.

Both the Eigenfactor Score (EFS) and the Article Influence Score (AIS) use a five‐year target window in the algorithm to quantify the scholarly impact at the overall journal level and at the article level, respectively.

The paper examines how the rank positions of 52 library and information science journals change when the set of journals are ranked by the Eigenfactor metrics in relation to the JIF‐5 indicator.

The principle behind Google's PageRank is where a web page or site got ranked in the search results based not merely on the number of incoming links, but also on the status/prestige of the linking sites based on the PageRank scores of those linking sites. This is a recursively calculated permanent value until the next year's edition.

The purpose of this paper is to provide an overview of new citation‐enhanced databases and to identify issues to be considered when they are used as a data source for performing citation analysis.

The paper reports the limitations of Thomson Scientific's citation indexes and reviews the characteristics of the citation‐enhanced databases Chemical Abstracts, Google Scholar and Scopus.

The study suggests that citation‐enhanced databases need to be examined carefully, with regard to both their potentialities and their limitations for citation analysis.

The paper presents a valuable overview of new citation‐enhanced databases in the context of research evaluation.

In the twenty-first century, technology and information are continuously being changed and rapidly updated. Many new innovations and discoveries emerge daily. This study aims to identify significant pioneers and milestones in academic research through utilizing bibliometric methods and heterogeneous data, including textbook citations, citations of theses and dissertations, and journal citations.

This study proposes several methods and formulas for recommending Nobel prizes candidates. Through utilizing bibliometric methods and heterogeneous data, including textbook citations, citations of theses and dissertations, and journal article citations, this research facilitates the collection of numerous significant research results. The authors propose several new, useful formulae, including a pioneer paper impact factor, a popular classical paper impact factor, a ranking factor of specific fields, a groundbreaking author impact factor, and a frequently cited author impact factor.

This study utilizes historical information on the Nobel Prize to examine, revise, and verify existing methods for recommending and predicting candidates, in order to enhance the accuracy and availability of the approach presented by this study. The experimental results show that the approach designed in this study had a rate of successful prediction exceeding 50 percent. The major reason for producing reasonable results is that the milestone paper and pioneer paper are filtered first, and then the important candidate authors from the most pioneer paper are filtered. Therefore, the results indicated the feasibility of the methods developed by this study.

The purpose of the Nobel Prize is to reward original research findings or inventions that significantly and positively influence human life. However, due to budget limitations, only five fields are included in the academic domains for which Nobel prizes are awarded. The authors develop one useful new way to identify milestone papers and authors. Young students can choose, read and learn from these milestone papers. The pioneer authors identified by this research could be the recommended candidate list for some academic awards.

The purpose of this paper is to review empirical studies on process mining in order to understand its use by organizations. The paper further aims to outline future research opportunities.

The authors propose a classification model that combines core conceptual elements of process mining with prior models from technology classification from the enterprise resource planning and business intelligence field. The model incorporates an organizational usage, a system-orientation and service nature, adding a focus on physical services. The application is based on a systematic literature review of 144 research papers.

The results show that, thus far, the literature has been chiefly concerned with realization of single business process management systems in single organizations. The authors conclude that cross-system or cross-organizational process mining is underrepresented in the ISR, as is the analysis of physical services.

Process mining researchers have paid little attention to utilizing complex use cases and mining mixed physical-digital services. Practitioners should work closely with academics to overcome these knowledge gaps. Only then will process mining be on the cusp of becoming a technology that allows new insights into customer processes by supplying business operations with valuable and detailed information.

Despite the scientific interest in process mining, particularly scant attention has been given by researchers to investigating its use in relatively complex scenarios, e.g., cross-system and cross-organizational process mining. Furthermore, coverage on the use of process mining from a service perspective is limited, which fails to reflect the marketing and business context of most contemporary organizations, wherein the importance of such scenarios is widely acknowledged. The small number of studies encountered may be due to a lack of knowledge about the potential of such scenarios as well as successful examples, a situation the authors seek to remedy with this study.