Data and decanting
Tell us a little about your background and qualifications…
I consider myself a serial entrepreneur and I am a recurring-revenue, licensing and B2B information expert. I currently serve as CEO of Data Licensing Alliance. I also serve as CEO of DMedia Associates, where I’ve led the company to be twice named on the Inc.5000 list of fastest growing companies.
Of relevance, I earned a B.S. degree in genetics/business from The University of Maryland, a M.B.A. in finance from Pepperdine University and a Juris Doctor degree from American University. Over the past 30+ years, I’ve had several different careers since entering the workforce and starting Data Licensing Alliance.
I’ve held roles as strategic planning analyst for a Fortune 10 company, senior associate at a cross-border M&A investment bank, vice president of business development for a biotechnology company and also for a ‘dot-com’ business. In early 2000, I found my way to the professional and scholarly publishing industry, joining Wolters Kluwer Health/Ovid as executive director for global licensing and business development, where I spent seven years. Since leaving Wolters Kluwer, I’ve spent the last 15 years as CEO of DMedia Associates, a bespoke consultancy specialising in licensing content. In these roles, I’ve specialised in strategy, licensing sales and business development, and legal.
I’ve led the development of strategic plans and developed and led the effort for new product licenses, new strategic partnering and acquisition targets. I’ve personally drafted, negotiated and closed over 500 domestic and international licensing agreements and negotiated and closed countless business alliances, strategic partnering, and revenue generation deals.
I am an active member of the California State Bar, a prior member of the Content Board of the Software and Information Industry Association, and of many publishing industry associations.
Can we hear about your new project – Data Licensing Alliance?
Absolutely! Data Licensing Alliance, or DLA for short, is a marketplace targeted specifically for STEM data licensing. The intended use case is to match licensors (i.e. owners of data) with licensees (i.e. users of data) for AI/Machine Learning purposes.
We have finished the initial development of the marketplace, and we are in the process of loading our first batch of data and will be beta testing it over the next few months.
What are the intended benefits for the wide scholarly communications landscape?
Licensing data, especially for AI/ML, is a very frictioned process. I should know; I’ve been licensing data for over two decades and there are certain deals, for one reason or another, that have either taken years to conclude or never do, mainly because the parties cannot come to an agreement about the use or the value of the data in question.
Through the DLA Marketplace, the overall benefit will be significantly reduced friction in the licensing of STM data. More detailed intended benefits are:
• From the Licensee perspective, it is a central platform where data scientists can find the appropriate data to better train their models, deliver insights and derive knowledge; and
• From the Licensor perspective, this is a unique business opportunity to add needed new revenue stream(s). We are at an inflexion point where data owners will need to separate subscription and data licensing rights as they search for much needed revenue. It will also allow data scientists/researchers (and their related Institutions) an outlet to monetise their data – be it their raw data or a more complete corpus of information.
How do you think AI/ML will have developed in 10 years’ time, and how will it effect academia in general?
I’ll start out with a quote from The Matrix that I think says it all: ‘I don’t know the future. I didn’t come here to tell you how this is going to end. I came here to tell you how it’s going to begin.’
In my vision of the future, from a publisher perspective, I am certain that revenue from licensing data will (soon) have overtaken subscription sales. Government regulations are, and will continually require, comprehensive data for AI/ML in order to increase diversity and eliminate bias in algorithms and its outputs. Further, Increased government encouragement and regulatory environment will bring more funding and mandates for AI/ML. From a technological perspective, the ever-decreasing cost of storage, and advancements in technology developed specifically for Ai/ML, will make AI/ML the de-facto technology that drives our world.
This will translate down in a decade or so to academia in many unknown ways. However, if I were a betting man, I would put my money on the following:
• Primary learning and information will come from specifically designed algorithms rather than from traditional academic settings
• Information that was siloed in ivory towers and academic repositories since the dawn of time will be set free (or at least free-er) by the need for ever-increasing sets of data and the advancement of discovery tools;
• Ai/ML will be used to not only generate information, but derive knowledge; and
• Information and knowledge will be delivered to us based on our own specific needs and use-case(s), rather than us searching for it.
What are your wider hopes for the future of scholarly communications?
That’s a big question and is probably the subject for a second conversation.
That said, my hope for the future of scholarly communications is two-fold: 1) A normalisation of communications that currently is monopolised by a few of the more powerful commercial publishers. Don’t get me wrong, these publishers are communicating many times wonderful information. What I am referring to is that today, many of the society and association publishers messaging is buried under the sheer volume of content coming from experienced marketers with deep pockets and connections. What I am suggesting is that there needs to be room for communications from and for smaller or more niche constituencies. 2) More seamless forums to produce and disseminate content. This will include tools and methodologies to create more timely and relevant data and the increasing ability to discover such data as part of daily workflows.
Finally, do you have any fascinating facts, hobbies or pastimes that you’d like to admit to?
There are few for sure. For starters, I love wine, especially red wine. In fact, so much so that back in 2013, I started a wine company called Myers Family Cellars. We produce two wines: one that I like to call a ‘cult’ wine called The Hunter. It is a Cabernet Sauvignon produced from grapes from the famed Stagecoach Vineyard in Napa, California. We also produce a much more accessible red Zinfandel blend called SquaRed. It is named after my two children Sophie and Sam. Check us out at www.myerswines.com!
Interview by Tim Gillett