Information on research funding is important to various groups, including investigators, policy analysts, advocacy organizations and, of course, the funding agencies themselves. But informatics resources devoted to research funding are currently limited. In particular, there is a need for information on grants from the US National Institutes of Health (NIH), the world's largest single source of biomedical research funding, because of its large number of awards (~80,000 each year) and its complex organizational structure. NIH's 25 grantawarding Institutes and Centers have distinct but overlapping missions, and the relationship between these missions and the research they fund is multifaceted. Because there is no comprehensive scheme that characterizes NIH research, navigating the NIH funding landscape can be challenging. At present, NIH offers information on awarded grants via the RePORTER website (http:// projectreporter.nih.gov). For each award, RePORTER provides keyword tags, plus ~215 categorical designations assigned to grants via a partially automated system known as the NIH research, condition and disease categorization (RCDC) process (http://report.nih.gov/ rcdc/categories). But keyword searches are not optimal for various information needs and analyses, and the RCDC categories are only intended to meet specific NIH reporting requirements, rather than to comprehensively characterize the entire NIH research portfolio. To facilitate navigation and discovery of NIH-funded research, we created a database (https://app.nihmaps.org/) in which we use text mining to extract latent categories and clusters from NIH grant titles and abstracts. This categorical information is discovered using

Cells respond to many stressors by senescing, acquiring stable growth arrest, morphologic and metabolic changes, and a proinflammatory senescence-associated secretory phenotype. The heterogeneity of senescent cells (SnCs) and senescence-associated secretory phenotype are vast, yet ill characterized. SnCs have diverse roles in health and disease and are therapeutically targetable, making characterization of SnCs and their detection a priority. The Cellular Senescence Network (SenNet), a National Institutes of Health Common Fund initiative, was established to address this need. The goal of SenNet is to map SnCs across the human lifespan to advance diagnostic and therapeutic approaches to improve human health. State-of-the-art methods will be applied to identify, define and map SnCs in 18 human tissues. A common coordinate framework will integrate data to create four-dimensional SnC atlases. Other key SenNet deliverables include innovative tools and technologies to detect SnCs, new SnC biomarkers and extensive public multi-omics datasets. This Perspective lays out the impetus, goals, approaches and products of SenNet.

This article presents the results of a 7-year-long quest into the development of a "dream tool" for our research in information science and scientometrics and more recently, network science. The results are two cyberinfrastructures (CI): The Cyberinfrastructure for Information Visualization and the Network Workbench that enjoy a growing national and interdisciplinary user community. Both CIs use the cyberinfrastructure shell (CIShell) software specification, which defines interfaces between data sets and algorithms/services and provides a means to bundle them into powerful tools and (Web) services. In fact, CIShell might be our major contribution to progress in convergence. Just as Wikipedia is an "empty shell" that empowers lay persons to share text, a CIShell implementation is an "empty shell" that empowers user communities to plug-and-play, share, compare and combine data sets, algorithms, and compute resources across national and disciplinary boundaries. It is argued here that CIs will not only transform the way science is conducted but also will play a major role in the diffusion of expertise, data sets, algorithms, and technologies across multiple disciplines and business sectors leading to a more integrative science.

At the first international Visualization Summit, more than 100 international researchers and practitioners defined and assessed nine original and important research goals in the context of Visualization Science, and proposed methods for achieving these goals by 2010. The synthesis of the whole event is presented in the 10th research goal. This article contributes a building block for systemizing visualization research by proposing mutually elaborated research goals with defined milestones. Such a consensus on where to go together is only one step toward establishing visualization science in the long-term perspective as a discipline with comparable relevance to chemistry, mathematics, language, or history. First, this article introduces the conference setting. Second, it describes the research goals and findings from the nine workshops. Third, a survey among 62 participants about the originality and importance of each research goal is presented and discussed. Finally, the article presents a synthesis of the nine research goals in the form of a 10th research goal, namely 'Visualizing Future Cities'. The article is relevant for visualization researchers, trend scouts, research programme directors who define the topics that get funds.

This paper presents the results of an analysis and visualization of 428,440 movies from the Internet Movie Database (IMDb) provided for the Graph Drawing 2005 contest. Simple statistics are presented as well as a tapestry of all movies with an overlay of the giant component of the co-actor network. Academy award winners are highlighted. Major insights are discussed.