Large Scientific Databases Research Articles

How effective are non-pharmacological interventions for family caregivers? A systematic review with meta-analyses

Informal caregiving is associated with mental disorders and reduced quality of life. The aim of this systematic review was to summarize the results of methodologically high-quality intervention studies on the effectiveness of non-pharmacological interventions on patient-relevant outcomes for family caregivers in Germany. We searched three large scientific literature databases for intervention studies with a control group and a low or moderate risk of bias on the effectiveness of non-pharmacological interventions for family caregivers in Germany. Among 4,376 publications reviewed, 10 intervention studies with good methodological quality were identified. These investigated multi-component interventions or cognitive behavioral therapy for family caregivers of people with dementia (8 studies), stroke (1 study) and with general care dependency (1 study). The control groups received information material as a minimal intervention or usual standard care. Meta-analyses showed a statistically significant slight reduction in depressive symptoms 3-6 months after the start of the study as a result of cognitive behavioral therapy (standardized mean difference -0.27; 95% confidence interval -0.44 - -0.10), but this no longer reached statistical significance after 9-12 months (-0.21; -0.51 - 0.09). Multi-component interventions showed no changes in depressive symptoms either after 3-6 or after 9-12 months (-0.18; -0.40 - 0.03 and -0.14; -0.47 - 0.14, respectively). In contrast, the mental component of quality of life of family caregivers improved statistically significantly in the multi-component intervention groups compared to the control groups: slightly after 3-6 months (0.28; 0.01 - 0.56) and moderately after 9-12 months (0.45; 0.09 - 0.82). The interventions had no effect on the physical component of quality of life. The reduction of depressive symptoms by behavioral therapy interventions for family caregivers appears to be only slight and not sustainable. The mental component of quality of life of people affected may be improved in the longer term by multi-component interventions. Current scientifically examined interventions for informal caregivers do not appear to have a sufficient and sustainable effect. Greater effects could possibly be achieved through more elaborate behavioral approaches, but also structural preventive measures.

Unresolved issues of comorbid pathology in minors with urogenital inflammation

A holistic approach to the problem of copious and prolonged menstruation during puberty allows adequately predicting the situation and clearly determining the direction of therapeutic and diagnostic measures. This model of protection of reproductive health of minors is based on interdisciplinary interaction. Problematic interdisciplinary issues of modern medicine include the norm and pathology of microbiocenosis of the vulva and vagina and recurrence of abnormal uterine bleeding in minors. Based on the study of modern literature data, the relationship between disorders of genital microbiocenosis and reproductive disorders in minors is analyzed. The results of scientific research, including 19 Russian and 12 foreign studies, which are presented in large scientific databases, such as eLibrary, CyberLeninka, Science Direct, Scopus, and Google Scholar, have been analyzed. It has been shown that vaginitis remains the most common disease in minors. The importance of doctor’s timely actions in the field of predicting the development of vaginitis and its timely prevention in childhood is emphasized. Dysbiotic disorders of the vaginal microbiota are one of the leading triggers of menstrual cycle formation disorders, including recurrence of abnormal uterine bleeding. The latter requires monitoring and preventive measures. The method of hemostasis must be selected individually, depending on the severity of bleeding and the characteristics of the clinical course. Combined infectious pathology is characterized by a persistent course and the interaction of mechanisms of persistence of the infectious process and justifies the need to take into account all aspects of clinical manifestations and apply a personalized approach to the complex therapy of these conditions at the interdisciplinary level.

Effect of Pre-Season Training on Physiological and Biochemical Indices in Basketball Players-A Systematic Review.

The pre-season period in basketball includes all the physiological attributes that the players need to work on and develop, in order to sustain a full season workload. The monitoring of the effectiveness of pre-season training is based on a variety of biochemical and physiological indices; however, it is still unclear how pre-season training affects those markers. Therefore, this study aimed to analyze the effects of pre-season training on biochemical and physiological markers. A search was performed in five large scientific databases (Pubmed (Medline), Scopus, Science-Direct, Sport-Discus (EBSCO), Semantic Scholar) and produced 7081 results, which after removing duplicates and applying inclusion and exclusion criteria, resulted in 28 published scientific articles being included in this review. The most important findings suggested that the majority of the studies used a 6- or an 8-week pre-season training protocol, because these protocols have shown significant positive effects over the years. In addition, the plyometric training protocols that were used by many studies have been found to be beneficial for basketball athletes for many physiological parameters. Furthermore, the evaluation of biochemical markers can be a very useful tool in monitoring and managing fatigue, which is an essential part of modifying the training process, in order to maximize performance.

Review on Adverse effects or side effects of Remdisivir

In March 2020, the World Health Organization declared the spread of SARS-CoV-2 a global pandemic. To date, coronavirus disease-2019 (COVID-19) has spread to over 200 countries, leading to over 1.6 million cases and over 99,000 deaths. Given that there is neither a vaccine nor proven treatment for COVID-19, there is currently an urgent need for effective pharmacotherapy. To address the need for an effective treatment of SARS-CoV-2 during the worldwide pandemic, this systematic review of intravenous (IV) remdesivir was performed. Remdesivir, an anti-viral prodrug originally developed to treat Ebola virus disease, has shown broad spectrum activity against the Coronavirus family. A recent case report reported improvement of clinical symptoms with remdesivir in a patient with COVID-19. After conducting a systematic search of 18 clinical trial registries and three large scientific databases, we identified 86 potentially eligible items. Following removal of duplicates (n = 21), eligible studies were reviewed independently by two authors. After the first round of screening, inter-rater agreement was 98.5% (κ = 0.925). After the second round of full-text screening, inter-rater agreement was 100%. A total of seven ongoing and recruiting clinical trials of remdesivir (100–200 milligrams, intravenous [IV]) were included. We identified the following primary outcomes: patients discharged (n = 2); time to clinical status improvement (n = 2); improved O2 saturation (n = 2); body temperature normalization (n = 2); and clinical status (n = 1). Secondary outcomes in all identified studies included documentation of adverse events. Phase 3 trials are expected to be completed between April 2020–2023. Therefore, despite supportive data from in vitro and in vivo studies, the clinical effectiveness of IV remdesivir for treatment of COVID-19 and potential side effects remain incompletely defined in the human population. But the remdesivir is also harmful for the people because of it can have some side effects such as mentioned in the following information. There are so many type of disease started form the treatment of COVID-19 with the Remdesivir that also mentioned in the following review paper.

Longitudinal Physiological and Fitness Evaluations in Elite Ice Hockey: A Systematic Review.

Chiarlitti, NA, Crozier, M, Insogna, JA, Reid, RER, and Delisle-Houde, P. Longitudinal physiological and fitness evaluations in elite ice hockey: A systematic review. J Strength Cond Res 35(10): 2963-2979, 2021-Ice hockey has greatly evolved since the last review article was published more than 25 years ago. Although players still combine anaerobic and aerobic conditioning, the pace of the game has greatly increased. Players are faster, stronger, and more agile than their predecessors; however, an important emphasis is now placed on maximizing player performance for the play-offs. For the coaching staff, strength and conditioning coaches, and players, an emphasis on mitigating fitness and physiologic losses throughout the season would be beneficial, given the intimate relationship they share with on-ice performance. This systematic review of the literature outlines the current knowledge concerning longitudinal changes in relation to fitness, body composition, and physiologic parameters across an elite hockey season. The search of 4 large scientific databases (i.e., Embase, PubMed, SPORTDiscus, and Web of Science) yielded 4,049 items, which, after removing duplicates and applying inclusion and exclusion criteria, resulted in 23 published scientific articles to be included in this review. The wide span of literature (1956-2020) made inferences difficult giving the degree to which the game of ice hockey has changed; however, more recent research points to an aerobic deconditioning pattern and increased fatigue throughout the season in a specific group of elite hockey players (i.e., university athletes) while showing that ice hockey can lead to many possible histological adaptations. Ultimately, tracking, identifying, and developing methods to mitigate potential negative longitudinal changes will be imperative to influencing individual and team performance in the later parts of the season.

The knowledge map of energy security

Much efforts have been made in the area of energy security in recent years, but due to its wide scope, it is necessary to review relevant knowledge activities and to analyze the state of knowledge of the field of energy security measurement. The purpose of this article is to present a comprehensive map of knowledge in the field of energy security. For this reason, many documents and articles have been collected during the period 2002–2019 using 7 large and reputable scientific databases as well as 53 different journals, 90% white Q1 quality. There is employed meta-synthesis, scientometrics and network analysis. In the initial survey stage where 1290 articles were found, after analyzing the content using meta-synthesis, 240 scientific articles related to energy security were identified. Then, the following 14 key questions were addressed such as the main conceptual models, processes, and concept structures (concept map). The VOSviewer and Gephi software are also used to explain the conceptual structure (concept map), hot map, co-occurrence map between keywords and their categorization. After Energy Security (and its subsets), the issues of Renewable Energy Security and Energy Supply Security stand in top ranks. The most cited article in this area is the 2006 “Ensuring energy security” article by Yergin on Energy Security. As many as 58 people have published at least two articles, Sovacool with fifteen articles is on the top author with the most published articles in this field. During the evaluation of the articles, 34 conceptual models and 104 quantitative and qualitative methods were found, which illustrate the wide scope of energy security. By examining the coherent vocabulary map in the field of energy security, it can be said that the most important dimensions of energy security include technology, trade, acceptability, productivity, diversity, equity, availability, governance and efficiency.

Four years of fake news: A quantitative analysis of the scientific literature

Since 2016, “fake news” has been the main buzzword for online misinformation and disinformation. This term has been widely used and discussed by scholars, leading to hundreds of publications in a few years. This report provides a quantitative analysis of the scientific literature on this topic by using frequency analysis of metadata and automated lexical analysis of 2,368 scientific documents retrieved from Scopus, a large scientific database, mentioning “fake news” in the title or abstract.
 Findings show that until 2016 the number of documents mentioning the term was less than 10 per year, suddenly rising from 2017 and steadily increasing in the following years. Among the most prolific countries are the U.S. and European countries such as the U.K., but also many non-Western countries such as India and China. Computer science and social sciences are the disciplinary fields with the largest number of documents published. Three main thematic areas emerged: computational methodologies for fake news detection, the social and individual dimension of fake news, and fake news in the public and political sphere. There are 10 documents with more than 200 citations, and two papers with a record number of citations.

Managing complexity in maritime business: understanding the smart changes of globalization

PurposeThis study aims to review and try to understand the importance of complexity management for maritime business to gain competitiveness in global business environment. The purpose of the study is to discuss and evaluate managing change and requirements of understanding the complexity management.Design/methodology/approachTo find peer-reviewed journal publications, a large scientific database used by searching Web of Science and Scopus as the most relevant abstract and citation databases that provide peer-reviewed literature data for many different academic disciplines and selected papers evaluated from the maritime business context.FindingsAs a conceptual paper, the contribution of the study is to offer practical/required management applications with the help of six proposes for making better management decisions to confront future challenges to catch organizational competitiveness and success. With adaptation of complexity management, maritime stakeholders able to create an important core competency.Research limitations/implicationsThe research has some limitations and further research into this area should be extended. This study is designed as a first step to provide an insight to the field and to understand the main views of the subject. Subsequently, complexity management in maritime business is a slightly deficient area of research, which offers remarkable research opportunities. First, it would be fruitful to collect qualitative data to examine the current issues and changing business environment of the maritime business. Second, it would be helpful develop quantitative models to offer practical solutions from the maritime stakeholders’ point of view according to loading/discharging/transportation requirements. Future studies should deepen the subject with the help of simulation models of operations or agent based applications of stakeholder problems or vessel/ship-owner management implementations to understand changing circumstances of new business environment for the sake of managing complexity.Practical implicationsAs the core point of view in strategic management; “achieving and sustaining” competitive advantage in organizations always takes an important place in organizational survival. With the help mentioned proposes stakeholders of the system could understand the ways of dealing with the complexities of new business world which enhances organizational competitiveness.Social implicationsMaritime business could be defined as a social ecosystem which has it is own dynamics and customs. Socio-eco systems, like all complex systems, show unique non-linear dynamics in space and time which could be tough to define via classical quantitative methods. Organizations co-exist and co-evolve with their environment. It is possible that organizations effect their environment and gain some control over it while at the same time affected from environment and should steer the new trends.Originality/valueThe originality of the study lies in highlighting the importance of change management as a handler of complexity management for maritime business. The contribution of the paper is to indicate expected opportunities and challenges of smart changes for relevant readiness of maritime business for better management decisions, benefiting maritime business stakeholders by simultaneously enhancing effectiveness to confront future demands to achieve organizational competitiveness. With the help of proper complexity management lenses organizations could able to create their source of competitive advantage that represents capacity to align and enable required functions under tough contextual environment.

Science literacy in action: understanding scientific data presented in a citizen science platform by non-expert adults

ABSTRACT Citizen science is transforming the ways scientific knowledge is created, in that citizens participate in active scientific research, and large scientific databases can be accessed online. However, data availability does not guarantee public use or the relevance of these resources. This paper addresses the ways in which non-expert adults involved in a citizen science initiative, perceive, understand and use its scientific information. Participants responded to an online questionnaire presenting air quality data from ‘Sensing the Air’ citizen science platform, followed by interpretation questions (n = 123). The results showed that 70% of participants were able to interpret the data presented in various visual representations. No differences were found between gender, age or education level. However, respondents with tertiary scientific education obtained higher average scores. Among users who had previous experience with the project, overall scores were higher, and differences based on respondents scientific education were fewer. This may suggest that while scientific education is important in providing skills for data interpretation, it is not the only way to acquire these skills. This study highlights the ability of non-experts to understand and apply scientific data in daily situations and the potential of citizen science to develop scientific skills, competencies and public understanding of science.

Remdesivir for the Treatment of COVID-19: A Systematic Review of the Literature.

In March 2020, the World Health Organization declared the spread of SARS-CoV-2 a global pandemic. To date, coronavirus disease-2019 (COVID-19) has spread to over 200 countries, leading to over 1.6 million cases and over 99,000 deaths. Given that there is neither a vaccine nor proven treatment for COVID-19, there is currently an urgent need for effective pharmacotherapy. To address the need for an effective treatment of SARS-CoV-2 during the worldwide pandemic, this systematic review of intravenous (IV) remdesivir was performed. Remdesivir, an anti-viral prodrug originally developed to treat Ebola virus disease, has shown broad spectrum activity against the Coronavirus family. A recent case report reported improvement of clinical symptoms with remdesivir in a patient with COVID-19. After conducting a systematic search of 18 clinical trial registries and three large scientific databases, we identified 86 potentially eligible items. Following removal of duplicates (n = 21), eligible studies were reviewed independently by two authors. After the first round of screening, inter-rater agreement was 98.5% (κ = 0.925). After the second round of full-text screening, inter-rater agreement was 100%. A total of seven ongoing and recruiting clinical trials of remdesivir (100–200 milligrams, intravenous [IV]) were included. We identified the following primary outcomes: patients discharged (n = 2); time to clinical status improvement (n = 2); improved O2 saturation (n = 2); body temperature normalization (n = 2); and clinical status (n = 1). Secondary outcomes in all identified studies included documentation of adverse events. Phase 3 trials are expected to be completed between April 2020–2023. Therefore, despite supportive data from in vitro and in vivo studies, the clinical effectiveness of IV remdesivir for treatment of COVID-19 and potential side effects remain incompletely defined in the human population.

Modelling healthcare access for migrants and refugees in Europe: identifying the major health issues

Abstract The Mig-HealthCare systematically searched to identify the key health areas of refugee/migrant health in order to facilitate interventions that help access to care services for migrants and refugees. The literature review was carried out in March 2018 using 3 large scientific databases using a combination of search terms following the PRISMA methodology and a standard set of items used to report on systematic reviews. Based on the predefined inclusion and exclusion criteria, a total of 118 publications were used for data extraction. It is important to note, that in almost all of the sources identified, the following cross-cutting factors were described as influencing access to healthcare: Continuity of Information, how it relates to policy, how it differs between health services and across-borders. Furthermore, the organizational coordination among social and health care providers in the host country determinates the successful access to healthcare of migrants/refugees.Language & Communication takes into consideration both the healthcare service and its provision of translators and cultural mediators, and the host country language proficiency of the migrant/refugee.Organizational improvement of access and delivery of health care services for migrants and refugees in addition to Cultural Competence of the healthcare providers meaning the ability to maximize their sensitivity in the service of care to culturally diverse groups.Health literacy understood as the motivation and competences of the migrant population to access, understand, appraise, and apply health information. Additionally, the health issues of particular importance for migrants/refugees as emerged from the systematic review, including mental health, maternal/child health, health promotion, NCDs and chronic diseases, Oral/|Dental health, and Vaccinations should be included in planning future needs and healthcare access.

User centered design of a citizen science air-quality monitoring project

ABSTRACTTechnological developments, social networking and the emergence of sensory micro-computation platforms have facilitated the recent growth of citizen science-public participation in scientific research. Citizen science provides lay audiences platforms for data collection and classification alongside access to large scientific databases. Although these platforms are intended for non-experts, they are often designed by scientists, who may not fully appreciate their importance. This may result in platforms that are incompatible with users’ needs and thus underused . This article describes the use of Human Computer Interactions (HCI) in a citizen science project for monitoring air-quality in the local environment. Using interviews, focus groups, questionnaires and log data from the project website (n = 138), in a three-phase iterative process, we identified public requirments from an online data presentation platform. The findings suggest participants were interested in real time, local, easy to understand information, which is practical, ready-to-use and presented in the context. These insights were implemented in the design of a new platform, constructed as a simple three-layer information display with representations of air-quality standards and practical recommendations. We examine participants’ use of the platform and discuss motivations and impediments to participation in the future design of citizen science projects for enhancing public engagement in science.

Analyzing scientific context of researchers and communities by using complex network and semantic technologies

Social network communities are composed of people with common interests who influence or are influenced by themselves. In the scientific context, Scientific Social Networks are characterized as social networks that represent the social relations established by researchers. Identifying and exploring these relationships are fundamental activities to support scientific experiments. In this study, we aim to discuss the use of complex networks combined with semantic analysis in a network of scientific publications called DBLP. DBLP can be classified as big data, and its use for the analysis of connections and influences among researchers can be considered a context-aware approach. Therefore, in the present study, concepts of complex network analysis are applied to verify the level of influence among researchers, by analyzing the structure of the scientific social network under study and its communities. A bidirectional graph-based model was proposed in order to evaluate the influence of researchers, in addition to algorithms to analyze the network structure and identify scientific communities, using ontological terms and rules, considering the scientific context, and identifying new connections to promote scientific collaboration. For the identification of scientific communities, we proposed an overlapping community detection algorithm, named NetSCAN. A large scientific database (DBLP) together with digital libraries were used to evaluate the model and the algorithms in a historical research experiment. The results point to the viability and effectiveness of the proposed solution.

SIMARECH 3: A New Application for the Governance of Scientific Research

In the international context of research assessment, many countries appear to move critically towards a quantitative evaluation policy, which would eventually complement or replace the traditional peer review system. However, infometrics studies, based on the running of large international scientific databases, are confused by the complex organization of their research system. Furthermore, these databases prove to be inadequate to study the local research institutions and units. After a description of the current situation and a needed analysis survey, this proposal presents the design and development of an information system conceived as a tool for monitoring the research carried out by a university or another institution. Based on the use of an effective application developed by a team of Abdelmalek Essaâdi University(UAE) dedicated to conduct collaborative extranet, this information system, called SIMArech “Systeme d’Information de la Recherche Scientifique”, is fully customizable in real-time. It is available in Arabic, English and French and its flexibility enables it to dynamically adjust to the specificities of any institution having research units. Actually, several universities in three countries are implementing this system to improve their management of scientific research. Several examples are given to demonstrate how this tool is able to continuously develop a state of the art or a dashboard for these structures and their scientific production. The emphasis is put on the fact that local research structures, as well as national structures, needless research evaluation than valorization of their research.

Digital card games in education: A ten year systematic review

This paper presents a 10-year review study that focuses on the investigation of the use of Digital Card Games (DCGs) as learning tools in education. Specific search terms keyed into 10 large scientific electronic databases identified 50 papers referring to the use of non-commercial DCGs in education during the last decade (2003–2013). The findings revealed that the DCGs reported in the reviewed papers: (a) were used for the learning of diverse subject disciplines across all educational levels and leaning towards the school curriculum, in two ways: game-construction and game-play, (b) were mainly proposed by their designers as meaningful, familiar and appealing learning contexts, in order to motivate and engage players/students and also to promote social, rich and constructivist educational experiences while at the same time integrating modern technologies and innovative gamed-based approaches, (c) were implemented using a plethora of digital tools, (d) mainly adopted social and constructivist views of learning during their design and use, although the views were explicitly reported in only a few of these, (e) were evaluated – in more than half of the studies – with positive results in terms of: student learning, attitudes towards DCGs and enrichment of social interaction and collaboration, (f) appeared to support students to acquire essential thinking skills through DCG-play. However, despite the rich DCG-game experiences reported in the reviewed papers, some essential but under-researched topics were also specified.

Building creative thinking into the STEM undergraduate classroom experience using large databases: The Paleobiology Database example

Undergraduate research experiences have been linked to increased student recruitment and retention in STEM, particularly within traditionally underrepresented populations. However, research experiences can be cost prohibitive due to the infrastructure necessary to conduct experiments or collect field data. Existing, large scientific databases can be leveraged to provide students (including students in online courses) with authentic research experiences without the logistical costs. The Paleobiology Database (paleobiodb.org) is one of many publicly available (and free) scientific databases. This project describes authentic research activities which engage students at several 4 and 2-year institutions in the southeastern United States use the data available in the Paleobiology Database to engage in the creative process of developing their own research questions, hypotheses, and investigations. Once produced an evaluated, these research activities will be made available to instructors across the world on the Paleobiology Database website, which will also encourage educators to create and post their own activities as well.

Leveraging Pattern Recognition Consistency Estimation for Crowdsourcing Data Analysis

Crowdsourcing is an effective method for analyzing large scientific databases. However, data annotation relies on untrained volunteers, making it difficult to control the quality of the annotation. Here, we propose a method to estimate the consistency of the annotations of human classifiers in citizen science projects. Since the performance of supervised machine learning systems decreases as the level of noise in the data increases, the method is able to rank human annotators by the consistency with which they annotate. Because the method uses the accuracy of an automatic classifier trained with these samples, it does not require ground truth or data annotated by other citizen scientists. The method allows reducing the number of annotations required for each sample by identifying the most efficient data annotators, as well as improving the overall quality of the data by giving higher weights to the classifications of the more consistent data annotators. The proposed method can also be used for improving the citizen science user experience by providing feedback in real time. Experimental results using a large citizen science project— Galaxy Zoo —and a subset of over $1.1\times 10^6$ data annotations made by 4000 citizen scientists show Pearson correlation of 0.966 between the quality estimation provided by the method and the actual performance of the data annotators. The method also demonstrated efficacy in improving the performance of offline statistical consensus methods.

Scientific Ranking over Heterogeneous Academic Hypernetwork

Ranking is an important way of retrieving authoritative papers from a large scientific literature database. Current state-of-the-art exploits the flat structure of the heterogeneous academic network to achieve a better ranking of scientific articles, however, ignores the multinomial nature of the multidimensional relationships between different types of academic entities. This paper proposes a novel mutual ranking algorithm based on the multinomial heterogeneous academic hypernetwork, which serves as a generalized model of a scientific literature database. The proposed algorithm is demonstrated effective through extensive evaluation against well-known IR metrics on a well-established benchmarking environment based on the ACL Anthology Network.

A method for the identification of collaboration in large scientific databases

The analysis of scientific collaboration networks has contributed significantly to improve the understanding of the collaboration process between researchers. Additionally, it has helped to understand how scientific productions by researchers and research groups evolve. However, the identification of collaborations in large scientific databases is not a trivial task, given the high computational cost of the prevalent methods. This paper proposes a method for identifying collaborations in large scientific databases, namely, ISColl – Identification of Scientific Collaboration. Unlike methods that use techniques such as exhaustive comparisons of publication pairs, the proposed method produces satisfactory results with a low computational cost, thus providing an interesting alternative for the modelling and characterization of large scientific collaboration networks. To demonstrate the potential of the proposed technique, tests were conducted using scientific publications data registered in the Lattes Platform of CNPq, with the obtained results yielding excellent accuracy during the identification of scientific collaborations.

Data, Statistics, and Controversy: Making Science Research Data Intelligible

Making published, scientific research data publicly available can benefit scientists and policy makers only if there is sufficient information for these data to be intelligible. Thus the necessary meta-data go beyond the scientific, technological detail and extend to the statistical approach and methodologies applied to these data. The statistical principles that give integrity to researchers’ analyses and interpretations of their data require documentation. This is true when the intent is to verify or validate the published research findings; it is equally true when the intent is to utilize the scientific data in conjunction with other data or new experimental data to explore complex questions; and it is profoundly important when the scientific results and interpretations are taken outside the world of science to establish a basis for policy, for legal precedent or for decision-making. When research draws on already public data bases, e.g., a large federal statistical data base or a large scientific data base, selection of data for analysis, whether by selection (subsampling) or by aggregating, is specific to that research so that this (statistical) methodology is a crucial part of the meta-data. Examples illustrate the role of statistical meta-data in the use and reuse of these public datasets and the impact on public policy and precedent.