Response to the letter 'Field classification of publications in Dimensions: a first case study testing its reliability and validity'.

With Dimensions, Digital Science provides the research community a new approach on research related information, bringing formerly siloed content types such as grants, patents, clinical trials with publications and citations together, making it as openly available as possible (see app.dimensions.ai). Due to the different content types, (controversial) journal based classifications were not an option since it would not allow to categorise grants etc. Hence Digital Science opted for applying a categorisation approach using machine learning and based on the content of the documents and well established classification systems for which a training set was available. The implementation at launch was a first step and requires to be improved-although we observe a reliability comparably to manual coding for grants, the implementation at launch comes with some shortcomings as observed by Bornmann (2018), mostly due to challenges with the training set coverage. To overcome the shortcomings of the initial categorization approach we implemented an improvement process with the research community and Lutz Bornmann's analysis presented a great opportunity to provide more transparency and insights in the ongoing improvements.

Categorizing biomedical research: the basics of translation.

As biomedical research has evolved over the past century, the terminology employed to categorize it has failed to evolve in parallel to accommodate the implications of these changes. In particular, the terms basic research and translational research as used today in biomedicine seem especially problematic. Here we review the origins of these terms, analyze some of the conceptual confusions attendant to their current use, and assess some of the deleterious consequences of these confusions. We summarize that the distinction between basic and translational biomedical research is an anachronism. Elimination of this often contentious distinction would improve both the culture and the effectiveness of the scientific process, and its potential benefits to society.-Flier, J. S., Loscalzo, J. Categorizing biomedical research: the basics of translation.

International Alzheimer's Disease Research Portfolio (IADRP) aims to capture global Alzheimer's disease research funding.

Alzheimer's disease (AD) is a recognized international public health crisis. There is an urgent need for public and private funding agencies around the world to coordinate funding strategies and leverage existing resources to enhance and expand support of AD research. To capture and compare their existing investments in AD research and research-related resources, major funding organizations are starting to utilize the Common Alzheimer's Disease Research Ontology (CADRO) to categorize their funding information. This information is captured in the International Alzheimer's Disease Research Portfolio (IADRP) for further analysis. As of January, 2014, over fifteen organizations from the US, Canada, Europe and Australia have contributed their information. The goal of the IADRP project is to enable funding organizations to assess the changing landscape of AD research and coordinate strategies, leverage resources, and avoid duplication of effort.