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Corpus-based studies have offered the domain definition inference for test developers. Yet, corpus-based studies on temporal fluency measures (e.g., speech rate) have been limited, especially in the context of academic lecture settings. This made it difficult for test developers to sample representative fluency features to create authentic listening passages. To address this issue, the Fluency Corpus of Academic English Lectures (FCAEL) was created to offer insight into the thresholds for temporal fluency features in academic lecture settings. The current study compared the corpus data to the academic lecture passages in the Test of English as a Foreign Language Internet-based test (TOEFL iBT) and International English Language Testing System (IELTS) to examine the domain definition inference of these tests. In total, 14 temporal fluency measures were examined. A bootstrapped one-way multivariate analysis of variance (MANOVA), followed by a series of bootstrapped analyses of variances (ANOVAs), independent t -test, and Tukey tests showed some support for the tests, although many limitations were also found. The study suggests the 25th–75th percentile of FCAEL as tentative thresholds for each temporal fluency feature. The proposal may be useful for test developers to create and revise test materials. Coding schemes, analysis codes, and raw corpus data are available on the project's Open Science Framework page, exemplifying how Open Science can provide benefits beyond the academic community. [ABSTRACT FROM AUTHOR]

Diasporic Indian languages in Malaysia are unique and distinguishable from their native variants. Past studies have indicated that dominant languages tend to overpower minority languages in multilingual communities, hence causing languages to shift. The aims of this study are to identify the language choices of Malaysian Tamils and to what extent does English influence their shift from their native language. The respondents were 30 Malaysian Indians. The findings of the study revealed that in the family domain, there was an alarming shift to English when participants spoke to their children (93%) and their spouses (63%) as opposed to the older generations. Meanwhile, in the friendship domain, 76% of the participants preferred using English when they had to speak to other Malaysian Tamils. As for strangers, there was a 50–50 distribution between English and Malay between these participants. These findings seem to show that most families shifted from their native language to English among children in the family domain, education domain and friendship domain. Therefore, it is possible to note that factors such as imperialism, economic status and relevance of usage in language domains are the driving factors behind the shift of Tamil to English in Malaysia. [ABSTRACT FROM AUTHOR]

This paper examines Jewish dietary laws (kashruth) as a knowledge domain, focusing on the ways tacit knowledge has impacted the development and continued use of this dietary ontology. Building from this case study, a framework is proposed for categorizing tacit expressions and assessing their impact on knowledge organization practices. This framework establishes three tacit categories based on two communicative variables -- self-disclosure and verbal omission -- and emphasizes the methodological value of a domain-analytic approach for identifying tacit traces within explicit language. [ABSTRACT FROM AUTHOR]

In an era characterized by the ubiquity of the internet, the proliferation of online services, and the increasing frequency of cyber threats, the detection of look-alike domains has become a critical component of cybersecurity. The current paper presents an approach for the detection of look-alike domains, leveraging the power of open-source intelligence (OSINT) tools. It included gathering and analyzing a wide range of publicly available data sources, including permutations, WHOIS records, IP information, website content, Geo IP, similarity percentage, name server, and mail server records, and building a comprehensive profile of domains under investigation. Through the application of online search engines, patterns and features that distinguish legitimate domains from their deceptive counterparts were established. The analysis demonstrated that OSINT tools provided significant information about the sample domains and successfully detected 1598 registered look-alike domains among 10 sample domains using dnstwist, while OpenSquat identified 103 squatting domains, 960 active phishing websites, and 53 domains with suspicious certificates across five sample websites. The research contributes to the enhancement of cybersecurity practices by providing a cost-effective and scalable solution for identifying look-alike domains, which can serve as precursors to various online threats, including phishing attacks, malware distribution, and fraud.

Abstract The current work highlights the evolution in knowledge management for sustainable entrepreneurship research by analyzing the key trends and major concepts. Additionally, the knowledge structures of such research themes were analyzed and mapped. Moreover, this paper seeks to present a research agenda concerning the study subject. It employed an integrated bibliometric approach and systematic review of knowledge management and sustainable entrepreneurship research by conducting two main procedures, namely domain analysis (i.e., key trends and evolution) and knowledge structures analysis (i.e., intellectual, social, and conceptual structure). A total of 233 documents were obtained from Scopus and Web of Science datasets and analyzed using both R 4.1.2 and VOSviewer software. The findings demonstrated that the contributors (i.e., the authors, nations, journals, and institutions) produced a discernible evolution in the body of knowledge on the themes of knowledge management and sustainable business within the designated period. Furthermore, science mapping approaches deeply grasp the social, conceptual, and intellectual structures of such research themes. This current work is considered one of the first attempts to systematically review, analyze, and visualize the scientific productions on knowledge management and sustainable entrepreneurship. The findings of the current work also offer a solid understanding and insights into the potential directions for the research agenda in these disciplines.

Abstract Collaborative innovation addresses intricate, multifaceted problems of a systemic nature involving a multitude of actors with diverse and often unknown expectations. To facilitate this collaboration, innovation spaces—such as Makerspaces, Hackerspaces, Fablabs, among others—have emerged as arenas where networks of actors interconnect and solidify. Understanding the diverse nature of these innovation spaces poses a challenge, particularly in distinguishing their specific characteristics and assessing how each contributes to fostering innovative networks. This article aims to address the question: how can we classify innovation spaces based on the innovation networks they constitute? To tackle this query, we initially conducted an in-depth exploration of various innovation spaces through web content analysis, scrutinizing their individual value propositions. Subsequently, employing innovation network theory alongside domain analysis methodology, we proposed a taxonomy designed to classify the distinct types of innovation spaces under scrutiny. Our taxonomy reveals three types of spaces—learn-and-explore, partner-and impact, and transitory—as well as convergent and divergent spaces, showing the diversity and complexity of networks they constitute. The findings also show that while the majority of innovation spaces unite diverse actors to drive collaboration and innovation, many resulting networks have a medium level of formality and are project-centric. These networks tend to be synthetic in nature, seeking to apply existing knowledge, and represent exploration networks wherein the adaptability and diversity of initiatives foster learning, the acquisition of new knowledge, and the development of fresh capacities through interactions.

The current work highlights the evolution in knowledge management for sustainable entrepreneurship research by analyzing the key trends and major concepts. Additionally, the knowledge structures of such research themes were analyzed and mapped. Moreover, this paper seeks to present a research agenda concerning the study subject. It employed an integrated bibliometric approach and systematic review of knowledge management and sustainable entrepreneurship research by conducting two main procedures, namely domain analysis (i.e., key trends and evolution) and knowledge structures analysis (i.e., intellectual, social, and conceptual structure). A total of 233 documents were obtained from Scopus and Web of Science datasets and analyzed using both R 4.1.2 and VOSviewer software. The findings demonstrated that the contributors (i.e., the authors, nations, journals, and institutions) produced a discernible evolution in the body of knowledge on the themes of knowledge management and sustainable business within the designated period. Furthermore, science mapping approaches deeply grasp the social, conceptual, and intellectual structures of such research themes. This current work is considered one of the first attempts to systematically review, analyze, and visualize the scientific productions on knowledge management and sustainable entrepreneurship. The findings of the current work also offer a solid understanding and insights into the potential directions for the research agenda in these disciplines. [ABSTRACT FROM AUTHOR]

Collaborative innovation addresses intricate, multifaceted problems of a systemic nature involving a multitude of actors with diverse and often unknown expectations. To facilitate this collaboration, innovation spaces—such as Makerspaces, Hackerspaces, Fablabs, among others—have emerged as arenas where networks of actors interconnect and solidify. Understanding the diverse nature of these innovation spaces poses a challenge, particularly in distinguishing their specific characteristics and assessing how each contributes to fostering innovative networks. This article aims to address the question: how can we classify innovation spaces based on the innovation networks they constitute? To tackle this query, we initially conducted an in-depth exploration of various innovation spaces through web content analysis, scrutinizing their individual value propositions. Subsequently, employing innovation network theory alongside domain analysis methodology, we proposed a taxonomy designed to classify the distinct types of innovation spaces under scrutiny. Our taxonomy reveals three types of spaces—learn-and-explore, partner-and impact, and transitory—as well as convergent and divergent spaces, showing the diversity and complexity of networks they constitute. The findings also show that while the majority of innovation spaces unite diverse actors to drive collaboration and innovation, many resulting networks have a medium level of formality and are project-centric. These networks tend to be synthetic in nature, seeking to apply existing knowledge, and represent exploration networks wherein the adaptability and diversity of initiatives foster learning, the acquisition of new knowledge, and the development of fresh capacities through interactions. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ibero-Americana de Ciência da Informação is the property of Revista Ibero-Americana de Ciencia da Informacao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cooperativism, since its emergence, has promulgated a way of bringing together producers of various objects or social orders in a type of company that supports the community and the common good of the society it serves. This phenomenon constitutes an emerging research issue in interdisciplinary topics in science. This research is based on the application of theoretical methods and documentary analysis to locate theoretical references on the management of cooperative companies as a theme in the socialization of scientific knowledge. A domain analysis of the topic management of cooperative businesses was carried out to visualize the main journals and authors that address scientific results related to the topic. The Open Access Observatory developed by the University of Pinar del Río was used as a source of information, which compiles academic information from the Directory of Open Access Journals and facilitates the representation of the information from different parameters. Bibliometric indicators were applied to visualize the most distinctive institutions, authors and countries, it is evident that the topic is poorly socialized in the scientific community, with instability in scientific production existing in the period analyzed (2003-2022). The present research revealed the need to extend the study to other sources of information, with emphasis on the English language. In addition, it allowed to analyze the behavior of publications on the subject, available in open access, specifically those that are framed in the application of topics related to Economic Sciences. [ABSTRACT FROM AUTHOR]

Amino acid permeases (AAPs) play important roles in transporting amino acids in plant species, leading to increased low-nitrogen tolerance, grain yield, or protein content. However, very few AAPs have been characterized in soybean (Glycine max). In this study, we scanned the soybean reference genome and identified a total of 36 AAP genes (named GmAAP). The GmAAPs were phylogenetically divided into three evolutionary clades, with the genes in the same clades sharing similar gene structures and domain organization. We also showed that seventeen GmAAP genes on ten chromosomes were in collinearity, likely due to whole-genome duplication. Further analysis revealed a variety of cis-acting regulatory elements (such as hormone response elements (ABRE, ERE, GARE, P-box, and TGA-element), stress response elements (LTR, MBS, MYB-related components, TC-rich repeats, TCA-element, and WUN-motif), the tissue expression element (GCN4-motif), and the circadian regulatory element (circadian) present in the 2 kb region of the GmAAP promoter region, demonstrating functional diversity and expression specificity. RNA-Seq data and quantitative real-time PCR identified five GmAAPs showing differential expression under nitrogen limitation, including GmAAP3, GmAAP5, and GmAAP8 showing downregulation while GmAAP14, GmAAP29 showed upregulation, suggesting their involvement in low-nitrogen stress response. These results provide comprehensive information on soybean AAP genes in nitrogen stress, and provide putative candidates with possible roles in enhancing amino acid delivery to seeds for yield improvement. [ABSTRACT FROM AUTHOR]

This research introduces the Wiki3DRank, a model combining real-time extracted quantitative data from Wikidata and Wikipedia to obtain a ranking of knowledge objects through a quantitative value that measures the relevance of one object compared to others in a specific domain. The model is based on the distribution of knowledge objects in a vector space, whose components are based on three main variables: the number of statements on Wikidata about an item, the number of articles in different Wikipedia editions, and the length in number of words of these articles. These variables are associated with the level of description of the Wikidata items, the dissemination of the referred knowledge objects in Wikipedia editions in different languages, and the degree of editorial elaboration of the corresponding Wikipedia articles. To demonstrate the viability of the model, a series of use cases across various domains are analysed: books, movies, cathedrals, earthquakes, rivers, and chemical elements. From the results obtained, it is possible to conclude that Wiki3DRank is a tool that allows measure the relevance of knowledge objects in the context of a knowledge domain. The operation of an open-source tool that enables the online calculation of Wiki3DRank is presented. The results suggest that the proposed model can be applied to different contexts and domains and that it`s ease to expand it by adding elements of weighting and extending the model with new components based on other characteristics of the encyclopaedic data of the knowledge objects, while the base vector calculation system is maintained. [ABSTRACT FROM AUTHOR]

This research introduces the Wiki3DRank, a model combining real-time extracted quantitative data from Wikidata and Wikipedia to obtain a ranking of knowledge objects through a quantitative value that measures the relevance of one object compared to others in a specific domain. The model is based on the distribution of knowledge objects in a vector space, whose components are based on three main variables: the number of statements on Wikidata about an item, the number of articles in different Wikipedia editions, and the length in number of words of these articles. These variables are associated with the level of description of the Wikidata items, the dissemination of the referred knowledge objects in Wikipedia editions in different languages, and the degree of editorial elaboration of the corresponding Wikipedia articles. To demonstrate the viability of the model, a series of use cases across various domains are analysed: books, movies, cathedrals, earthquakes, rivers, and chemical elements. From the results obtained, it is possible to conclude that Wiki3DRank is a tool that allows measure the relevance of knowledge objects in the context of a knowledge domain. The operation of an open-source tool that enables the online calculation of Wiki3DRank is presented. The results suggest that the proposed model can be applied to different contexts and domains and that it`s ease to expand it by adding elements of weighting and extending the model with new components based on other characteristics of the encyclopaedic data of the knowledge objects, while the base vector calculation system is maintained. [ABSTRACT FROM AUTHOR]

Union Territory of Jammu and Kashmir is a multilingual area where languages belonging to different language families are found. Apart from major languages like Kashmiri, Dogri, there are multitude of minority languages like Shina, Burushaski, Balti, Hindko, Punjabi, Pahari, Pashtu, Gojri, etc. Gurezi Shina is a lesser-known variety of Shina language being spoken by inhabitants of Gurez, a remote northern valley in the Union Territory of Jammu and Kashmir. The Shina Language belongs to the Dardic sub-group of Indio-Aryan language family. This language is primarily spoken in Gilgit-Baltistan, Pakistan, Dah Hanu, Gurez and Dras in India. The alternate names of the language are Shinaki and Sina. The linguistic repertoire of the native speakers of Gurezi Shina mainly comprises of languages like Shina, Kashmiri, Urdu and English. This paper focuses on the domain analysis that is the domains where Shina is used and the domains where other languages are used. By looking at language use in different domains one can get an idea whether there are any particular linguistic preferences for different domains and different interlocutors. The data for the present study was elicited through a well-designed questionnaire. [ABSTRACT FROM AUTHOR]

This paper delves into the complexities and theoretical underpinnings of knowledge organization systems (KOS), focusing on domain analysis and facet analysis as methodologies, such as improving the Library of Congress Subject Headings (LCSH). The study repeats a former critique of the LCSH and argues for the incorporation of facet and domain analysis to enhance its utility and academic rigor. Facet analysis, although well-established, is critiqued for its rationalist philosophy and lack of empirical grounding. Domain analysis is presented as a complementary approach that addresses these gaps by considering empirical, historical, philosophical, and pragmatic issues. To any given system, the paper emphasizes that KO systems are not neutral; they reflect underlying theoretical paradigms that must be understood for effective classification. The study concludes by advocating for interdisciplinary research and broader cooperation among knowledge organization professionals, philosophers, and subject specialists to develop more robust and academically rigorous KOS. [ABSTRACT FROM AUTHOR]

This article explores the language-proficiency levels required in traditional upper-division university courses in Latin. It introduces a research framework to Classics called "domain analysis" and analyzes upper-division Latin at one university to determine the target functional outcomes for students in lower-division courses. The article finds that traditional upper-division Latin requires philological skills that are not described under widely used descriptions of language proficiency, but that these courses also require a reading proficiency corresponding to "advanced high" in the American Council on the Teaching of Foreign Languages Proficiency Guidelines , as well as a limited degree of listening and pronunciation ability. A lower-division curriculum that integrates active Latin techniques with those drawn from multiliteracies and grammar-translation pedagogies may be best suited to achieving these proficiencies. [ABSTRACT FROM AUTHOR]

In daily life, English is increasingly used in various scenarios, and the technology of translation using machines and others is gradually maturing, but there are still cases of inaccurate translation. To enhance translation's accuracy, this study optimizes the method of fuzzy semantic selection, and then optimizes the method of domain analysis combined with neural networks to improve the accuracy of machine translation in different domains. The accuracy of the optimized neural network tends to be stable when the number of iterations is 15, the accuracy is 0.96, the accuracy of the traditional neural network is 0.91, and RNN is 0.82. Compared with the benchmark system, the bilingual mapping model has increased by 0.67% in the news field and 0.56% in the education field. The precision, recall and F value of machine translation are 93%, 86% and 0.8 respectively. The comprehensive experimental results show that the selection method based on fuzzy semantics, combined with the domain analysis method of network neural, can remarkably enhance the accuracy. [ABSTRACT FROM AUTHOR]

This paper tries to examine the domain and link analysis, webpage ranking, web trafficking and engagement, audience demography and also WIFs through a webometric study of Top 10 space organizations in the world. Identify the domains of the website; analyze the number of webpages, inlinks, self-links and calculate the simple/external/self-link impact factor of the space organizations. A key method to webometric studies (WIFs) we trying to use the google search engine that allow to calculations to be made of the total number of web pages of the site And total number of external backlinks of the site. The required data were collected in December 2022 using the google search engine for retrieving the number of web pages, Inlinks and Selflinks to the website. After analysis, we observed that NASA, ISRO, UKSA, and KARI is the most popular organization among them. [ABSTRACT FROM AUTHOR]

This article introduces the field of terminology, which often considers the Austrian engineer Eugen Wüster as its founder in the 1930s, although important principles go back in time, in particular to 18th and 19th century botanists, zoologists and chemists. The contributions of Wüster are presented, as well as the alternative theories, with their criticism of Wüster’s position, which came to influence the field after 1990. The article further suggests that domain-analytic studies based on epistemological studies of knowledge domains seems to have been overlooked. The relations between terminology and knowledge organization are addressed, and closer cooperation between the two fields is called for. [ABSTRACT FROM AUTHOR]

Constructing a bibliographic dataset is fundamental for domain analysis in bibliometric research. However, irrelevant documents(so-called "impurities") in the initial domain dataset are inevitable and difficult to identify, requiring considerable human efforts to eliminate. To solve this problem, we propose a weak-supervised noise reduction approach based on the Positive-Unlabeled Learning (PU-Learning) algorithm to clean the initial bibliographic dataset automatically. The basic idea is to use a batch of "absolutely positive sample sets" already available in the dataset to obtain a collection of "reliable negative sample sets," based on which a training set can be constructed for the downstream supervised classification. This paper conducted a comparative experiment using the Artificial Intelligence (AI) domain of the US National Technical Reports Library (NTIS) report as an example. We compared schemes with different variables to explore the influence of various technical aspects on the final noise reduction performance. Our approach achieved significant improvements compared with the similarity-based unsupervised baseline; the recall rose from 0.3742 to 0.8103, and the precision rose from 0.6621 to 0.7383. We found that the impact of document representation algorithms is crucial while classification strategies and s_ratio in PU-Learning are not. Our approach needs no manual annotation data and thus can provide powerful help for bibliometric researchers to construct high-quality bibliographic datasets. [ABSTRACT FROM AUTHOR]

The websites of the Library and Information Networks are one of the main sources of information in academic, management and other research fields. This type of network creates a cooperative bonding between various types of the subject area in the field of research. As we know library consortia and library resource sharing is one activity that promotes Network connectivity and communication between various areas of the subject field. In terms of research, Library and Information Network websites can give the existence and relevance of the achievements of individuals, research groups, institutions and various departments. This study tries to examine the 9 websites of Library and Information Networks in India. Various Data of the library network websites belong to the web meta information, page quality & structure, performance & accessibility score, SEO score, internal links, external links and metrics time limitation, domain analysis, traffic & engagement and also web ranking in India and Global & Alexa Rank. As we calculate WIFs find that ERNET and NKN are good position compare to others. After the analysis note that INFLIBNET, NICNET, ERNET, ADINET, and NKN is the most popular network in India among them. [ABSTRACT FROM AUTHOR]

Data modeling supported by ontologies favors the organization of knowledge and the use of inference machines to obtain new knowledge about data and support expert decision-making. However, it is necessary to discuss the techniques to promote inferences and explore the semantics between the data. The research problem is to verify how the use of semantic technologies would represent an advantageous alternative, in relation to the state of the art, to analyze, systematize and organize the information of a domain, accelerating a decisionmaking process. It presents the concepts behind the development of an artifact that employs semantic technologies and a domain ontology to integrate data from Building Information Modeling projects and other tabular data external to the project to automate Leadership in Energy certification tasks and Environmental Design. To demonstrate the artifact, data is semantically annotated and a knowledge graph is generated in Resource Description Framework format. Once integrated into the graph, inferences are applied to evaluate the certification criteria through queries. The results suggest that the application of these technologies promotes semantic extension, facilitates integration with other knowledge bases, and conceptually organizes data to better retrieve information and generate new knowledge. [ABSTRACT FROM AUTHOR]

This paper considers the scientific production domain of research productivity fellows in Information Science, in Brazil, as an object of analysis on transversality in production and Knowledge Organization. Data is collected from a database containing all productivity fellows of Information Science and their scientific production (1974-2020). The Chen's (2017) methodology is used to characterize the Information Science domain, constituting a corpus of 63 articles on the topic, distributed between 1996 and 2020. Results identify comprehensive contributions on concepts, theories and methodologies used by the productivity fellows. The period from 2011 to 2020 was the most productive (89% of the total number of articles), with significant growth observed from 2017 onwards. The production was published in 26 journals, of which four account for 46% of the articles. The clusters of thematic co-occurrence and authors referenced by the PQs suggest the sense of transversality from the perspective of KO systems, classification, information retrieval, as well as their relationships with Concept Theory and archival diplomacy, as an active nucleus research in focus. It is observed that subjects that are not exclusive to a specific discipline or area of knowledge are fully accepted in this production, crossing them, and starting to enrich them. [ABSTRACT FROM AUTHOR]

This article discusses the aspects and points of contact between discourse analysis and knowledge organization, perceiving how Michel Pêcheux's discourse analyses can contribute to domain analyses. Discourse analysis (DA) deals with the theoretical-methodological development of social and scientific movements that took place in France from the 1960s onwards; this paper seeks to discuss aspects of discourse analysis and the possibilities of its use in the universe of knowledge organization (KO). Little work is done structurally and transversally when it comes to discourse itself, especially when the words "discourse" and "analysis" appear in the titles, abstracts, keywords etc. of chapters, books and journals that have KO in their scope. That is mainly due to those works are recent and that belong to fields far from those which have traditionally dealt with discourse. Therefore, viewing discourse as a theoretical contribution to KO means a new framework should be understood in the scope of the analyses carried out regarding the construction of systems, approaches, and studies, precisely because it sees in the terms not only what concerns their concepts, as is the traditional route in KO, but also the ideology, and understands the construction of meaning as something historical as well as social. So, there is a major contribution for domain analyses based in Pêcheux's discourse theory. [ABSTRACT FROM AUTHOR]

Amino acid permeases (AAPs) play important roles in transporting amino acids in plant species, leading to increased low-nitrogen tolerance, grain yield, or protein content. However, very few AAPs have been characterized in soybean (Glycine max). In this study, we scanned the soybean reference genome and identified a total of 36 AAP genes (named GmAAP). The GmAAPs were phylogenetically divided into three evolutionary clades, with the genes in the same clades sharing similar gene structures and domain organization. We also showed that seventeen GmAAP genes on ten chromosomes were in collinearity, likely due to whole-genome duplication. Further analysis revealed a variety of cis-acting regulatory elements (such as hormone response elements (ABRE, ERE, GARE, P-box, and TGA-element), stress response elements (LTR, MBS, MYB-related components, TC-rich repeats, TCA-element, and WUN-motif), the tissue expression element (GCN4-motif), and the circadian regulatory element (circadian) present in the 2 kb region of the GmAAP promoter region, demonstrating functional diversity and expression specificity. RNA-Seq data and quantitative real-time PCR identified five GmAAPs showing differential expression under nitrogen limitation, including GmAAP3, GmAAP5, and GmAAP8 showing downregulation while GmAAP14, GmAAP29 showed upregulation, suggesting their involvement in low-nitrogen stress response. These results provide comprehensive information on soybean AAP genes in nitrogen stress, and provide putative candidates with possible roles in enhancing amino acid delivery to seeds for yield improvement.

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Building reusable software is always a challenge, even when well-established approaches are applied. Software Product Line (SPL) development is one these approaches, which allows domain modeling be a way of dealing with common and variable aspects of reality. However, domain engineering itself can be complex, many times depending on the domain scope and/or its associated functionality. In this paper, our proposal to SPL development is structured as a leveled reference model built upon standardized semantic resources. This model and its associated process are exemplified through several cases from the field, drawing influencing factors subjectively assessed. Our experiences show that systematically enriching domain engineering may improve SPL development in the practice.

Copyright of Ciência da Informação is the property of Instituto Brasileiro de Informacao em Ciencia e Tecnologia (IBICT) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study was inspired by the theoretical approaches of Beghtol, Buckland, Kleinberg, and Hjørland to discuss knowledge representation on Climate Change and COVID-19 in the context of Agenda 2030. This exploratory research was based on bibliometric methods through VOSviewer and CitNetexplorer tools to analyze the terms Climate Change and COVID-19, in the databases Scopus, Web of Science, and Dimensions, in the period 2019-2020. Approaches 7 and 8 of domain analysis were used to discuss the knowledge of disciplinarity and to identify the emergence of domains. Data collected from Brazil National Council for Scientific and Technological Development, in the Lattes Platform and Directory of Research Groups, were added for analysis purposes. The conclusion pointed out that Climate Change and COVID-19 can be considered emerging domains, suggesting a possible post-disciplinary model. The 2030 Agenda reinforces the importance of international cooperation and a commitment to exchange information on scientific communities and other communities that discuss sustainable solutions to global problems such as Climate Change and COVID-19. [ABSTRACT FROM AUTHOR]

One challenge for those reading methodological debates in low consensus fields is determining the outcome when participants do not share standards. When parties to a debate do not agree on the standards to be used in assessing their arguments (i.e., quality), it may be useful to ask first if parties' contributions meet their own expectations (i.e., integrity). Most protocols for review of qualitative research specify some form of quality assessment. These protocols normally require some test of internal coherence. Coherence is also relevant when describing the match between a rebuttal and the argument it answers. In 2019, Nursing Inquiry published a critique and rebuttal of the methods used by the Joanna Briggs Institute. In this essay, we attempted to use the Joanna Briggs Institute's own quality assessment standards to assess their rebuttal of this fundamental critique. We found it possible to use the Joanna Briggs Institute's own quality assessment standards to assess this rebuttal, and we found that JBI's rebuttal did not meet their own standards. [ABSTRACT FROM AUTHOR]

This research aims to analyze the contribution of univariate and relational citation analysis methods, applied to patents, for the identification and characterization of scientific-technological domains, in documents indexed in the Derwent Innovation Index database. The adopted method was patentometrics associated with bibliometrics, using joint analysis of the relational bibliometric citation methods: co-citation and bibliographic coupling. The corpus of the study is composed of 144 patent families. Through the bibliographic coupling, 5 theme clusters and researchers with well-defined thematic domains were observed. Employing co-citation, 23 clusters were identified, characterizing the epistemic domains related to technological currents in which stem cell inventors operate. Such results allowed us to prospect the scientific-technological scenario in this theme, which can illustrate some institutions' innovation potentials and explain who the actors at the forefront of such research are. It is proposed that applying this methodology allies to topic modeling techniques. [ABSTRACT FROM AUTHOR]