We present an analysis of data citation practices based on the Data Citation Index (DCI) (Thomson Reuters). This database launched in 2012 links data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: Although in the areas of science and engineering & technology data sets were the most cited, in the social sciences and arts & humanities data studies play a greater role. A total of 88.1% of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data-a role that would enhance their value as a means of following the research process from data collection to publication.

In this paper we review the socalled altmetrics or alternative metrics. This concept raises from the development of new indicators based on Web 2.0, for the evaluation of the research and academic activity. The basic assumption is that variables such as mentions in blogs, number of twits or of researchers bookmarking a research paper for instance, may be legitimate indicators for measuring the use and impact of scientific publications. In this sense, these indicators are currently the focus of the bibliometric community and are being discussed and debated. We describe the main platforms and indicators and we analyze as a sample the Spanish research output in Communication Studies. Comparing traditional indicators such as citations with these new indicators. The results show that the most cited papers are also the ones with a highest impact according to the altmetrics. We conclude pointing out the main shortcomings these metrics present and the role they may play when measuring the research impact through 2.0 platforms

Objectives: To analyze scientific activity in Latin American nursing using bibliometric indicators.

Abstract.The visualization of scientific field structures is a classic of scientometric studies. This paper presents a domain analysis of the library and information science discipline based on author co-citation analysis (ACA) and journal cocitation analysis (JCA). The techniques used for map construction are the self-organizing map (SOM) neural algorithm, Ward's clustering method and multidimensional scaling (MDS). The results of this study are compared with similar research developed by Howard White and Katherine McCain [1]. The methodologies used allow us to confirm that the subject domains identified in this paper are, as well, present in our study for the corresponding period. The appearance of studies pertaining to library science reveals the relationship of this realm with information science. Especially significant is the presence of the management on the journal maps. From a methodological standpoint, meanwhile, we would agree with those authors who consider MDS, the SOM and clustering as complementary methods that provide representations of the same reality from different analytical points of view. Even so, the MDS representation is the one offering greater possibilities for the structural representation of the clusters in a set of variables.Keywords: domain analysis; author co-citation analysis (ACA); journal co-citation analysis (JCA); library and information science; multidimensional scaling (MDS); self-organizing map (SOM) IntroductionThe perception and representation of reality are complicated undertakings. Tufte [2] expressed it well with these words: '. . . the world is complex, dynamic, multidimensional; paper is static, flat. How are we to represent the rich visual world of experience and measurement on mere flatland?' The visualization of information is an activity that humans have developed over time in a two-dimensional form, conditioned by the restrictions of the traditional document forms [3]. The arrival of the digital computer meant a brave new tool for processing, visualizing and analysing information structures that could not be comprehended outside a computerized context. Williams [4] White and McCain [5] introduce the problem of the visualization of literatures, stating, 'The trend now is to combine computerized graphics -visualizations -with computerized document retrieval, thereby making literatures seem more responsive.' This would represent the convergence of the two main lines of information science (IS) research into a single area, that of the visualization of the specialized literature of the discipline. The first of these lines of research comprises informetric-bibliometric studies, and is also known as the domain analysis [6]; the second would be that of information retrieval [7,8].Thus, we find ourselves with two clearly differentiated functions -analysis and interface -which we must attempt to integrate by introducing the methodology of visualization. There is, however, a gap between the two spheres. This gap has been described, though not resolved, by several author...

In this study, along with some key messages about the key shifts in publication trends, in terms of subject, where published and by whom, we propose a new methodology which could be useful to professionals as well as researchers, in which the exhaustivity and precision rates for scientific information retrieval improve.