Interdisciplinarity is considered the best way to face practical research topics since synergy between traditional disciplines has proved very fruitful. Studies on interdisciplinarity from all possible perspectives are increasingly demanded. Different interdisciplinarity measures have been used in case studies but, up to now, no general interdisciplinarity indicator useful for Science Policy purposes has been accepted. The bibliometric methodology presented here provides a general overview of all scientific disciplines, with special attention to their interrelation. This work aims to establish a tentative typology of disciplines and research areas according to their degree of interdisciplinarity. Interdisciplinarity is measured through a series of indicators based on Institute for Scientific Information (ISI) multi-assignation of journals in subject categories. Research areas and categories are described according to the quantity of their links (number of related categories) and their quality (with close or distant categories, diversity, and strength of links). High levels of interrelations between categories are observed. Four different types of categories are found through cluster analysis. This differentiates "big" interdisciplinarity, which links distant categories, from "small" interdisciplinarity, in which close categories are related. The location of specific categories in the clusters is discussed.

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The study of acknowledgements in research publications is gaining ground in science. At present, acknowledgements are considered an important element in the scholarly communication process, forming part of the so-called "reward triangle" together with authorship and citations (Cronin & Weaver, 1995). Acknowledgements may contain expressions of gratitude to individuals, institutions or research infrastructures that have contributed to the work being reported, as well as formal recognition to research funders. Accordingly, the study of acknowledgements is of interest not only to better understand communication practices in science, but also for research policy purposes (Paul-Hus, Desrochers & Costas, 2016; Rigby, 2011). The collection of funding acknowledgments merits special attention because it may facilitate a wide range of studies. The aims of such efforts include tracking the research output supported by funding bodies and specific grant and research programs (e.g.

Open access (OA) to every research result supported by funding bodies is a medium to long-term goal. This work aims to find out whether OA publication is useful for all research fields, regardless of their specific features. As a sample, articles from the WoS databases from two disparate disciplines (one from SSCI and another from SCIE) are selected, and several hypotheses related to the presence of funding acknowledgements, cooperation and citations are tested. A first look at the general distribution of publications shows that collaborative and funded research obtains a higher proportion of cited articles, and that this proportion increases in the case of OA publications. Moreover, the logistic regression reveals that the probability of finding an OA publication is significantly increased in the SCIE discipline, and by the presence of EU funding, international collaboration and citations. This probability rises with some interactions (e.g. presence of international funding and international collaboration, or international funding and citations). Regarding OA types, Green OA publications are the most related to fund recognition, although Gold OA/Bronze OA articles in international collaboration are also significantly related to financing. Concerning impact, the most likely cited OA type is the Hybrid OA. However, if papers include funding acknowledgements, the Bronze OA and Green OA publications increase their citation likelihood. Similarly, when Gold OA articles include international collaboration, there is a greater chance of citation. With these findings, it is possible to venture that OA publishing will be useful for all research fields, although their specific features should be considered. Consequently, funders should be aware of these particularities to stimulate OA without compromising the quality of the research.

In a context of increasingly limited resources, the demand for information from research funding bodies is growing. The exploitation of the funding acknowledgements collected in WoS publications can be useful for these sponsors, not only because it allows them to know the published results with their financial support, but also because it provides a framework to evaluate the efficiency of the different funding instruments. The present work adds to the knowledge of previous studies to offer a simple and efficient methodology that automatically identifies major sponsors, and their funded research, using keywords. To this end, articles with Spain in the address field and English in the language field are obtained (years 2010-2014), given that WoS only considers funding acknowledgements written in English. Subsequently, the Funding Agency (FA) field of these articles is treated, selecting funders' variants that will serve as keywords in the FTS (Full-Text Search) for the location of the research supported by major sponsors. In addition, a sample of reviewed documents is provided to evaluate the reliability of the proposed methodology, performing also some statistical tests. The results show a recall of 91.5% of the sample articles, with a precision of 99%. Notwithstanding, there are differences in the automatic identification of funders by institutional sector and/or area, being the Government sector the one with the highest precision and recall, and the area of Agriculture, Biology & Environment the one with the best degree of association between the automatic classification and the reviewed one. Finally, possible future developments are offered, paying special attention to increasing the automation of the standardisation of funders' names.