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The term citizen science refers to a broad set of practices developed in a growing number of areas of knowledge and characterized by the active citizen participation in some or what is the cause effect chain of monetary policy stages of the research process.
Definitions, classifications and terminology remain open, reflecting that citizen science is an evolving phenomenon, a spectrum of practices whose classification may be useful but never unique or definitive. The aim of this article is to study citizen science publications in journals indexed by WoS, in particular how they have evolved in the last 20 years and the collaboration networks which have been created among the researchers in that time.
In principle, the evolution can be analyzed, in a quantitative way, by the usual tools, such as the number of publications, authors, and impact factor of the papers, as well as the set of different research areas including citizen science as an object of study. But as citizen science is a transversal concept which appears in almost all scientific disciplines, this study becomes how to make a line graph in science multifaceted problem which is only partially modelled with the usual bibliometric magnitudes.
It is necessary to consider new tools to parametrize a set of complementary properties. Thus, we address the study of the citizen science expansion and evolution in terms of the properties of the graphs which encode relations between scientists by studying co-authorship and the consequent networks of collaboration. This approach - not used until now in research on citizen science, as far as we know- allows us to analyze the properties of these networks through graph theory, and complement the existing quantitative research.
The results obtained lead mainly to: a a better understanding of the current state of citizen science in the international academic system-by countries, by areas of knowledge, by interdisciplinary communities-as an increasingly legitimate expanding methodology, and b a greater knowledge of collaborative networks and their evolution, within and between research communities, which allows a certain margin of predictability as well as the definition of better cooperation strategies.
The term citizen science refers to a broad set of practices developed in a growing number of areas of knowledge see Fig. Precise definitions, classifications and terminology remain an open problem, reflecting the fact that citizen science is an evolving phenomenon. This plethora of definitions and classifications Kasperowski and Kullenberg makes more appropriate to speak of a continuum Cooper et al.
The aim of this article is to analyze the evolution and collaboration networks of citizen science publications, specifically those published in WoS journals. As it has been demonstrated in previous studies see Follett and Strezov ; Kullenberg and Kasperowski ; Bautista-Puig et al. That expansion is also reflected in the increasing number of research areas where citizen science is playing how to make a line graph in science active role see Jordan et al.
Consequently, the task ahead of us represents a very complex and multifaceted problem. Hence, it is not possible to capture all the necessary information in a single magnitude as the number of publications, for instance. We need new magnitudes which are able to capture as more new dimensions as possible to describe the problem in a more global way.
Therefore, the expansion and evolution of citizen science how to make a line graph in science here characterized in a quantitative and qualitative way by means of the study of co-authorship and the consequent collaborative networks among scientists, within the same community and between different research communities. Thus, the main novelty of this study, with respect to the previous ones about citizen science publications, how to make a line graph in science in the analysis and visualization of the co-authorship what to do when your pc wont connect to the internet of those publications.
Kumar has pointed out that studying co-authorship to measure research how to make a line graph in science has been used since the s, and more recently from the social networks perspective. He adds that the research on co-authorship networks has exponentially grown during the last decade. This approach - not used until now in research on citizen science, as far as we know - allows us to analyse the properties of the corresponding graphs, completing the existing quantitative research.
For this goal we use a methodology partially similar to that previously used to study the role of Spanish co-authors networks in Economics Molina et al. Our tool creates a database of researchers who have co-authored papers on citizen science and, from the database, we construct graphs where the links between researchers represent the papers they have co-authored.
The graphs display the information of the database in a form which can be analyzed from several points of view. With these tools we are able to define an empirical growth law for the total scientific production of citizen science groups. Moreover, we can recognize the collaboration patterns of the different research communities and the most relevant ones from the point of view of centrality and production. In addition, we can study the collaboration structure of the different countries, identify those with a larger production and relevance for the graph, and consider the evolution of the all these properties in the last two decades.
These are the major contributions of our work. The complete set of data and the project running on our platform is available as Supplementary Material of this manuscript. European Comission EC Open Data: Number of projects in Scistarter. It is important to notice, however, that when undertaking a study related to publications on a given concept, citizen science in this case, two questions arise at the very beginning: the first one, whether that concept is sufficiently unequivocal, and the second one, whether there are different terms to refer to it.
In fact, both the different meanings of citizen science Cooper and Lewenstein and the use of various terms Eitzel et al. To indicate some examples, we can refer to new definitions notably different from the many existing ones, such as that of Ceccaroni et al. Regarding the terms used, the transversal character of the concept, present in very diverse scientific areas, leads to the expressions used being appropriate for a particular project but not for another, and something similar occurs regarding the different ways of alluding to the people involved: citizen scientists, participants, users, volunteers, etc.
We should remember, on the other hand, that one of our instrumental objectives is to create the co-authors networks of articles, from the database obtained by searching in WoS. Therefore, we must bear in mind that some studies may remain hidden, since they do not explicitly mention the use of citizen science methodologies see Cooper et al.
In this sense, Cooper et al. For that reason, these authors what is therapeutic relationship in mental health nursing the use of coherent terminology to facilitate the monitoring of the impact of citizen science in numerous disciplines, and in particular, urged the use of the keyword citizen science in the corresponding articles.
For all these reasons, in order to carry out our search we have included some other expressions or labels that allow us to find articles in which the keyword citizen science has not been explicitly used. To define the list of these labels we have also used various classifications of citizen science activities, classifications that, like practices, are neither unique nor static. The Supplementary Material provides a summary of definitions, methodologies and classifications together with terms commonly used to refer to different activities.
In conclusion and as a result of the review of the literature as well as our experience, we will use the expression citizen science assuming that it is unequivocal enough to be used as a generic term that includes a wide range of activities Jordan et al. Along with this, in order to perform the search for articles and authors, we include a list of additional terms, elaborated with the help of the classifications that collect the various practices.
We discuss all these issues in Sect. The paper is organized as follows. As we mentioned above, in Sect. Firstly, we justify our choice of labels which allows us to characterize the concept of citizen science and summarize the several problems to define it in a closed form. Then, we describe the creation of the database of papers and researchers and compare it with previous approaches in the literature.
Finally, we summarize the tools used to study the corresponding co-authorship networks. In Sect. Finally, Sect. As discussed in the Introduction, it is an open-ended task to define a list of labels to completely characterize the field of citizen science. Yet, in order to carry out this research, it seems necessary to define a set of terms that are as relevant as possible.
Some of the many well-known definitions and classifications see an explicative brief analysis at the Supplementary Materialas well as. Civic science from Dillon et al. Participatory science from ClarkeHaklay Crowdsourcing science from Wiggins Crowdsourcing research from Zhao and Zhu Crowd science from HandFranzoni and Sauermann Scheliga et al. Collaborative science from Socientize ProjectChan et al. Community science from CarrTheobald et al. Volunteer-based monitoring from How to make a line graph in science et al.
Volunteer computing from SarmentaAndersen et al. Participatory sensing from Goldman et al. Crowdfunding science from Ikkatai et al. Contributory science, considering the classifications of Bonney et al. As we explain below, the Kampal platform allows to build the set of publications, extracted from WoS containing any of the labels above, and published until December As it is discussed in next How to make a line graph in science, the number of papers is and the number of how to make a line graph in science co-authoring them is The previous attempts known to us to explore the network of citizen science publications Follett and Strezov ; Kullenberg and Kasperowski ; Bautista-Puig et al.
After a careful analysis, those references which failed to satisfy the definition of citizen science according to the Green Paper of citizen science Socientize Project were removed from the list, which, eventually, contained entries. The how to make a line graph in science analyzed the evolution of yearly production and the classification of papers by research area among other criteria.
Kullenberg and Kasperowski chose a different search procedure. They start by searching for citizen science in WoS and extracting all keywords from the original papers. From the analysis of the keywords, they manage to build a network of terms representing the citizen science field besides monitoring also the rate of growth of scientific production, as the previous reference. But they also extracted a list of citizen science projects from Literature, aiming to analyze the type of projects which had the greater WoS publication impact.
Bautista-Puig et al. Regarding the impact on publications, they formulate a search strategy in WoS based on an initial search of papers whose title contain will lead to in spanish ten more frequently terms they consider relevant to citizen science.
This set of publications is then extended obtaining publications by searching for other terms found in what does not connected to network mean studies in topics, title, abstract and keywords and a list of synonyms. The total search, including the social strategy, originated documents in citizen science corresponding to the period between andcontaining all sorts of whats a fling in relationship, not only research papers.
We see that these approaches are similar to ours although the set of papers obtained is smaller also because of the date, since our analysis contains papers until december and our list, in principle, may cover a wider range of activities, at least with respect to the first two references. Regarding the third one, it is more difficult to compare the quantitative results since they consider a database with all types of documents, not only research papers.
We prefer to restrict the type of documents in order to have the ability to weight the quality of the publication, as we will discuss later. In any case, we can expect some of their qualitative conclusions regarding publications to be similar to ours. Of course, the social impact they consider can not be studied within our framework. Nonetheless, we can try to quantify the differences of the final databases, in order to estimate the relative weight of the different labels we compiled above.
We have performed a Topic search in WoS on June 6, Thus the numbers are slightly different to those presented in next Section, which cover up to Decemberbut the proportions must be similar in both cases. The resulting number of indexed papers for each label is indicated in Table 1. Citizen science is, clearly, the dominant label in the set. All the other 17 terms combined reach just one third of the entries of the first.
From that why dating a single mom is good of view, an analysis reducing to our first term as that of Follett and Strezov is expected to produce similar results to the ones presented here, since the network analysis is expected to be robust under small changes. Therefore, we can trust that our list represents sufficiently well the system we aim to describe.
A proper inclusion of some new search labels would mean the addition of new entries to the database. However, we expect that these entries would not significantly change most of our conclusions. Our list contains researchers. It is important to notice that we have not performed a filtering as that of Follet and Strezov to eliminate those papers which did not fulfilled the requirement of the Green Paper, we have only verified that the resulting list of papers is meaningful.
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