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Practical applications of data in publishingThe second in a series looking at the major themes of this year's TOC conference.At TOC, you're as likely to run into media professionals, entrepreneurs and innovators as you are publishers, booksellers and others working in traditional publishing. This, in turn, makes the underlying themes as varying and diverse as the attendees. This is the second in a series, taking a look at five themes that permeated interviews, sessions and/or keynotes at this year's show. The complete series will be posted here. As the world — and publishing — becomes more and more digital, more and more data is produced and, ideally, collected. Knowing what kinds of data can be useful and how data analytics can be applied to inform publishing decisions is on the minds of many publishing professionals. Data was one of the overriding themes at this year's Tools of Change for Publishing conference, including discussions on how publishers can benefit from real-time data, practical applications of data and analytics, and how data can not only inform publishing decisions, but can actually aid in content creation. In a keynote address, Roger Magoulas, director of market research at O'Reilly Media, talked about data research and the view of the data space at O'Reilly. He offered practical suggestions on how to incorporate data and addressed some of the reasons behind the buzz going on in the data space: ![]() Machine learning and natural language processing, for instance, have become mainstream tools. Magoulas said the tools for making use of big data have kept pace with the increasing amounts of data produced, allowing a small team like his — just three people — to do everything. When incorporating data to inform business decisions or to analyze business scenarios, Magoulas said data alone isn't enough — the data needs a narrative; the numbers alone won't tell the story. He addressed the area of data science from a functional viewpoint:
Magoulas said those are the two key parts, but that the most important part probably is having or cultivating a culture that can accommodate the data: "People need to understand the message that you're giving ... and how to value the input ... People need to be able to think in an experimental way and to stay curious." When offering practical suggestions on incorporating data into a business, Magoulas stressed that becoming data savvy is important; "you can't just go buy big data and expect to know what you're doing." He also said keeping the data close to the analysis is important:
You can view Magoulas' keynote in the following video (and you can find his slides here): The data discussion turned real-time and academic in the "Mendeley Case Study: How The World's Largest Crowdsourced Academic Database Is Changing Academic Publishing" session, hosted by Jan Reichelt, director and co-founder of Mendeley Ltd. Reichelt shared some lessons learned at Mendeley and talked about how real-time data on content usage provides important insights into how academics interact with research. He stressed the increasing importance of social and community-collaborated content:
In addition to insights gleaned from the data around content usage, data around content production also was telling. Similar to other areas of the publishing industry — journalism, self-publishing — Reichelt highlighted the blurring lines between types of content producers and the types of content produced in academic publishing:
Reichelt's presentation slides can be found here. Peter Collingridge (@gunzalis), co-founder of Enhanced Editions, talked about how publishers can benefit from real-time data and analytics in terms of marketing. In an interview, he said data can inform answers to vital questions:
As the data deluge grows in the digital age, it not only is useful for analysis and informing decisions, it also can be used to create content. In a video interview, Robbie Allen, founder and CEO of Automated Insights, a company that produces narrative content from raw data, addressed this topic. He said for now, quantitative content created from structured data — think sports stories, financial reports — is best suited for automation, but that creating content from unstructured data isn't out of the question:
Allen's full interview can be viewed in the following video: If you couldn't make it to TOC, or you missed a session you wanted to see, sign up for the TOC 2012 Complete Video Compilation and check out our archive of free keynotes and interviews. Related: |
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