Text & Data Mining: For Information Managers

Arming information managers and research teams with tools and strategies

Text and Data Mining (TDM) is the automated process of selecting and analyzing large amounts of text or data resources in a way that can provide valuable information needed for studies and research projects. This includes searching for content, finding patterns, discovering relationships, semantic analysis, and learning how content relates to ideas and needs.

As the volume of scientific publications increase and TDM software tools improve, we are moving towards a more formalized process to enable TDM, and strive to make this as simple as possible for customers and researchers.

Interested in learning more? Check out some of the latest tools and resources Springer Nature has put together to best arm you and your researchers.

Latest tools and resources

Webinar

MassBio & Springer Nature Data Summit 2022

Podcasts

Episode 1: Experts from 3M’s Knowledge Discovery & Analytics Group: Exploring the Roles Information Professionals Can Play in TDM Initiatives                                                          

Listen now to our interview with Jonnie Hauswirth, Rachel Wangerin and Jennifer Nelson from 3M’s Knowledge Discovery & Analytics Group talk about their roles in TDM initiatives and how they’ve raised awareness — and gained recognition — for their team by applying their unique expertise to help develop creative solutions for their users.

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Episode 2: Robin Padilla from Springer Nature: TDM Projects Taking Place at SN, and the Ways that Information and KM Professionals Can Contribute Strategically to TDM Projects in their Organization          

Listen now to our interview with Springer Nature’s Robin Padilla, Director of Product Management for Data and Analytics Solutions, as he talks about the TDM initiatives that Springer Nature has been developing for clients as well as for internal projects.

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