{"id":14473,"date":"2023-02-20T11:53:21","date_gmt":"2023-02-20T11:53:21","guid":{"rendered":"https:\/\/www.dimensions.ai\/?post_type=resource&p=14473"},"modified":"2023-07-28T13:29:54","modified_gmt":"2023-07-28T13:29:54","slug":"university-of-minnesota-directing-the-focus-of-new-scientific-research","status":"publish","type":"resource","link":"https:\/\/www.dimensions.ai\/resources\/university-of-minnesota-directing-the-focus-of-new-scientific-research\/","title":{"rendered":"University of Minnesota: Directing the Focus of New Scientific Research"},"content":{"rendered":"\n
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\u201cDimensions unlocks a lot of possibilities for important scientific analyses. It\u2019s the technology that people have been waiting for and has profound implications for how we approach research across the globe.\u201d<\/h2>\n\n\n\n

Russell Funk, Associate Professor in the Strategic Management and Entrepreneurship group, Carlson School of Management, University of Minnesota, US<\/strong><\/p>\n<\/div><\/div><\/div>\n\n\n\n

<\/p>\n\n\n\n

Improving the direction of research, while increasing quality and efficiency<\/h2>\n\n\n\n

Scientific knowledge offers a deeper understanding of the world around us. It\u2019s transformative: when we understand something, it empowers us to create change. However, research is intrinsically difficult \u2013 and progress, slow. Scientists are constrained by limited time, disconnected sources and \u201cmessy data\u201d<\/em>, an experience Russell Funk knows all too well.<\/p>\n\n\n\n

“Early on in my career, working with data was quite arduous. I probably spent 80 percent of my time in grad school cleaning data and trying to deduplicate records, instead of carrying out the research I was trained to do.”<\/strong><\/p>\n\n\n\n

All too often, research projects come adrift. Time runs over, funding runs out. The data itself has an expiration date: if your results are outdated, you may have to start anew. You might even discover another researcher has taken a different approach to your work and is closer to publishing than you. Enhancing the quality, reliability and efficiency of the research process is paramount.<\/p>\n\n\n\n

But more than this: improving the direction of research, understanding which questions could yield valuable results or where there are gaps in knowledge, is essential for science to advance and have a positive impact on society.<\/p>\n\n\n\n

Russell Funk, Associate Professor at the University of Minnesota’s Carlson School of Management, needed a more reliable way to work with data \u2013 one that could free up his time and offer a more nuanced picture of the research landscape and its influence.<\/p>\n\n\n\n

Expanding research capabilities<\/h2>\n\n\n\n

Russell\u2019s current research consists of two streams of work: measuring innovation in science and technology, and in a similar vein, understanding how science is changing over time and whether progress is slowing. Addressing such vast topics requires a systematic approach, along with comprehensive data, to avoid ambiguity or confusion.<\/p>\n\n\n\n

For his work exploring scientific innovation, Russell spends a lot of time identifying papers that are opening up novel areas of research, solving important problems or steering the conversation in new directions. Citation metrics are commonly used as performance indicators in research, yet they frequently act as biased measurements and overlook other key factors.<\/p>\n\n\n\n

“Citations are an important benchmark, but the true objective of science is not in citations. It’s ideas and concepts and explanations and hypotheses. To really get a deeper understanding of how science falls and scientific impact, you need to look at the actual text of papers, but scientists spend so much of their time writing and doing that it\u2019s not always possible.”<\/strong><\/p>\n\n\n\n

This is where Dimensions comes into its own, helping researchers like Russell reimagine data discovery.<\/p>\n\n\n\n

A more nuanced approach<\/h2>\n\n\n\n

With access to comprehensive data from multiple sources, including high quality texts from the titles and abstracts of papers, Dimensions has enabled Russell to better understand the context of different publications, while optimizing his time and efficiency. He is also able to extract concepts from documents which describe their main topics, using these as the basis for more advanced analysis.<\/p>\n\n\n\n

Beyond this, grants, patents, clinical trials and policy documents offer a more nuanced look at which kinds of scientific progress are slowing, and why, supporting Russell\u2019s second stream of research.<\/p>\n\n\n\n

“You start to see at what stage things are slowing, whether we\u2019re seeing less novelty in the ideas themselves, or if the ideas are there, but it\u2019s becoming harder to execute them.”<\/strong><\/p>\n\n\n\n

Contextualizing data<\/h2>\n\n\n\n

While published papers and those in peer-reviewed journals are an important product of science, they\u2019re only one part of the picture. For Russell, it\u2019d be \u201cwrong to make conclusions about what\u2019s going on in science more broadly\u201d<\/em> without including other contextual information.<\/p>\n\n\n\n

Dimensions links and contextualizes data from different sources across the whole research lifecycle, so Russell can explore earlier stages of research \u2013 for example successful projects which received start-up grants but didn\u2019t make their way into a publication.<\/p>\n\n\n\n

“It tells you something very different about science, especially in key areas like computer science and machine learning. Publications are less important in this space \u2013 you need to examine preprints, working papers and conference proceedings, all of which are included in the Dimensions database. The fact that it brings everything together in a standardized format is hugely beneficial for the research community.”<\/strong><\/p>\n\n\n\n

Dimensions also uses processes to disambiguate researchers and institutions, enabling scientists like Russell to easily map out collaboration networks and build more enriched sets of information.  <\/p>\n\n\n\n

Making better research decisions<\/h2>\n\n\n\n

Google BigQuery integration offers further insights and predictive analytics to help support the selection of research questions. This can have a huge influence on the direction of scientific research. <\/p>\n\n\n\n

With BigQuery, researchers can perform large scale analysis of Dimensions data, in combination with their own data or data from other sources. Russell says: \u201cI use it all the time. With BigQuery and Dimensions combined, I can test out new ideas to see if they\u2019re plausible and worth investigating further \u2013 or if I need to try a different route. It\u2019s a huge time saver.<\/em><\/p>\n\n\n\n

\u201cIt\u2019s also great for finding examples to help illustrate complex concepts. By running queries I can easily pull out really specific and interesting cases to include in papers, instead of having to comb through my own dataset.\u201d<\/strong><\/p>\n\n\n\n

Promoting better research for all<\/h2>\n\n\n\n

The more scientists use Dimensions, the easier it\u2019ll be to systematically code data and replicate studies, lending credibility to their findings. Russell hopes that this will lead to more cross-institutional collaborations and greater accessibility of research.<\/p>\n\n\n\n

 \u201cIf what\u2019s available guides the direction of research, then using Dimensions is a huge step forward. It\u2019s exceeded my expectations far beyond any other approach or tool.\u201d <\/strong><\/p>\n\n\n\n

Would you like to explore how Dimensions can support research within your organization? Get in touch and one of our experts would be happy to speak to you.<\/p>\n\n\n\n

Get in touch<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"

Improving the direction of research, while increasing quality and efficiency Scientific knowledge offers a deeper understanding of the world around us. It\u2019s transformative: when we understand something, it empowers us to create change. However, research is intrinsically difficult \u2013 and progress, slow. Scientists are constrained by limited time, disconnected sources and \u201cmessy data\u201d, an experience […]<\/p>\n","protected":false},"featured_media":14477,"menu_order":0,"template":"","resource_type":[4],"resource_audience_segment":[21,24],"class_list":["post-14473","resource","type-resource","status-publish","has-post-thumbnail","hentry","resource_type-case-studies","resource_audience_segment-academic-institutions","resource_audience_segment-researchers"],"acf":{"sidebar_title":"","sidebar_images":false,"sidebar_text":"","sidebar_links":false,"header_image":"","cta":""},"_links":{"self":[{"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/resource\/14473","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/resource"}],"about":[{"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/types\/resource"}],"version-history":[{"count":0,"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/resource\/14473\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/media\/14477"}],"wp:attachment":[{"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/media?parent=14473"}],"wp:term":[{"taxonomy":"resource_type","embeddable":true,"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/resource_type?post=14473"},{"taxonomy":"resource_audience_segment","embeddable":true,"href":"https:\/\/www.dimensions.ai\/wp-json\/wp\/v2\/resource_audience_segment?post=14473"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}