Ahead of ESOF 2014, we talk to three leading figures in science, technology and academia who through frustrations of not having the effective tools necessary to do their work, decided to build their own.
In this three-part series in the run-up to Europe’s largest, general science meeting held every two years, this year in Copenhagen (June 21-26), we look at the increasing number of start-up companies that are “spinning out” of academic institutions worldwide.
Here, the founder of Brainspace, Dave Copps talks about how social platforms are changing the way in which scientists work and how technology is being used to advance open research.
Dave is a social scientist and serial entrepreneur that has founded and launched three companies focused on scalable semantic discovery. He is currently CEO of Brainspace Corporation where he is leading the creation of BrainspaceScience, the first global semantic network for science professionals. BrainspaceScience transforms the published works of scientists all over the world into a collective intelligence that can be used by science professionals everywhere to semantically connect to relevant people and knowledge.
Where did the idea for Brainspace originate from?
I’ve always been a bit of a search geek and enjoyed discovery systems, but also often quite frustrated by them. Over time as the volumes of data are getting increasingly bigger, the systems that we have are equally becoming less and less effective.
I read a report recently that the success rate of an internet search is 50% and that the improvement over the last ten years has been 0%. This is a result of both just evolutionary improvement in search technology and an exponential increase in the amount of data being produced.
I think search is fundamentally broken on many levels. Some of our most basic assumptions about how search works are flawed. The current state of the art for Big Data is to make bigger searchable indexes that we then hack at with keywords. Sometimes we employ taxonomies, lexicons, word lists and other static logic, but even those can’t keep up with the flow of new knowledge. Search as a transaction is dying and will be replaced by systems that learn and connect people and things semantically. So being the anthropologist I am, I had this idea, a kind of “what if” question, so to speak. I thought what if I could aggregate all of the socially curated and peer reviewed content on the web and build it into a collective intelligence, a machine learning that connects all of the thoughts into a Brain. And then, what if we could give everyone access to this Brain to help connect people more intimately with people or things rooted closer to their interests. That is what we are delivering today.
How is technology being used to advance open research and science / changing the scientific landscape?
What we’re seeing today is fairly dramatic and there is a sea change happening with open access publishing and the large publishers. On one hand, there is still a major focus on aggregating and selling access to information while on the other side documents are not only recognized for their content, but also as “social objects”, that connect people in a certain context. This shift towards social is causing the transformation towards connectedness. The very fact we have millions of people physically connected on the Internet today is just the beginning. We’re starting to look at *how* we connect people that share in common knowledge, interests or passions. This socialization of knowledge and meaningful connection of the global science community will be the next major evolution we see in technology and on the web.
The formation of this global interest graph is the most dramatic change that’s happening today. Creating these meaningful connections will make a real difference in the world accelerating innovation and discovery. The six degrees of separation that currently divides us is quickly melting away.
What has been the impact and benefits of the semantic network tool since establishing?
The core technology of Brainspace is currently all over the world in some of the world’s largest companies. The Brainspace semantic network has just recently launched and is growing rapidly. Our intention is to really focus on science and research and companies that employ these people across the world. We’re very intent on gearing the content to that community.
An interesting thing that’s happened since we started this is that the actual learning network itself has grown dramatically. So the current Brainspace is being built from the knowledge sharing happening now across several social services. We’re aggregating documents that are being shared across these social services and ultimately transforming them into a single artificial intelligence, a Brainspace. It’s growing at a rate of about 150,000 documents a day and set to double very soon. The Brainspace will grow from tens of millions of documents today to hundreds of millions next year and essentially put the knowledge of all of us at the fingertips of each of us.
How many people are using the network and what do you see as a success in the future?
We just started inviting people a couple of weeks ago. There are thousands of people involved right now and it’s starting to grow exponentially, but we’re still very much at the nascent stages at this point. Brainspace grows smarter as the network of users grows and knowledge sharing increases. We are using the same strategy Pinterest and other similar networks employed by growing the network organically through invites. We are already seeing triple digit growth in all of our metrics across Brainspace. We’ll be very intentionally onboarding networks of people, groups and communities.
How will social platforms change the way in which scientists work in the future?
I think it is interesting. Social platforms connect people by who-knows-who, which is fine on Facebook when you are connecting with friends from the past an present, but to move forward in their area of interest scientists must connect with information and people they may not have known were relevant to their interests. Static keywords are replaced by a dynamic semantic network that connects people by who-knows-what. For example, if I have written five papers on a certain topic then my name should be intimately associated with the thoughts, concepts and ideas that are dominant in those papers. I shouldn’t have to build a static profile or constantly monitor and update key terms as my interests change or grow. As I write, as I publish, the network should learn about what I’m doing and not only make me discoverable in that context, but also show me other people and information related to my interests. What I make public or private is completely up to me.
What qualities do entrepreneurs share with scientists?
Quite a bit actually. Curiosity, the desire and willingness to make a difference and choosing a life driven by your passion, are just a few. Both scientists and entrepreneurs are also very comfortable stepping into the unknown where the answers may not be so obvious.
As scientists, we are here to make a difference and the same is true of entrepreneurs. Whether you’re researching,exploring, experimenting, teaching or building a business, you have to be dedicated to your craft. It’s that passion that despite the odds or challenges has them waking up every morning and wanting to do what they do every day. So, I believe they’re very similar.
And what do you think is the biggest transition from science to business?
The answer to that question has definitely changed over the last few years. It is a lot easier to start a business these days. You can start with very little money, try an idea and create a lean start-up. I think a lot of the barriers to entry that used to be there where people would spend lots of money writing business plans, hiring consultants and building the more traditional business structures have been changed. “Two scientists in a lab” are the new “two guys/gals in a garage”. So with both capital and people abundantly available, the biggest transition may be the transition itself- the decision to make the leap. If you’re not sure of your ability as an entrepreneur, look to join a local incubator where you are given access to local mentoring and even startup capital. If it’s really just money you need, look to sites like Kickstarter or IndieGoGo for crowd sourced funding. Whatever you do, start now as there’s no better way to see how good your idea is than putting it out there in the world. It’s easier than it has ever been before.
Getting your business launched is also the best way to understand how prepared you, personally, for being an entrepreneur. Are you a people person? Can you motivate and grow teams and understand how to create a business model. It is one thing to have an idea, but another to have a business model that allows your business to make money so you can actually stay in profit and grow. Those skills are not the easiest to acquire, but best acquired by trying. Start small, move fast and then Build, Measure, Learn (repeat).
What are the biggest challenges you’ve faced and what have you learned from them?
The hardest thing for me has been managing growth. We grew 300% in one year and that’s really hard. You’re so used to working in small groups and teams and all of a sudden you have a large company around you and maintaining the intimacy of a small company is very important to me and harder to do if you start to achieve high levels of growth.
Have you seen growing trends / numbers of academics starting companies as a result of their frustrations?
I think so, yes. You’re seeing evidence of that all over. There’s a lot of entrepreneurial activity around open access publishing and around online networks and communities. With open source software now going mainstream, academics building startups can begin using the very same platforms employed by Companies like Google, Yahoo and Facebook. All the tools are there for academics to become entrepreneurs. It is not a physical problem anymore; it is more of a choice to make. It is just whether you have the persistence to jump into something and make it your life.
What do you believe are the main challenges the academic system faces in supplying these effective tools? And what needs to be done to make this happen and alleviate frustrations?
It is more of a cultural problem and I think we’re seeing an uncomfortable shift right now in academia. This is not too dissimilar from other very large industries that have undergone dramatic change.
I think that knowledge is now turning into a flow, there is more open access publishing, peer review is changing and the world is more connected, so things have to start working differently. Things must change as the systems and structures we have in place today to manage knowledge and to connect people are insufficient. So we really have to consider looking towards dramatically different technology that is not transactional, if you will. Search systems where you put a key word in a box and get a list of results are dying out and being replaced by dynamic sharing networks where people are writing, sharing, collecting and collaborating. There’s an exponential aspect to those networks that does not exist today in search systems and so that’s the dramatic change. The question is whether the institutions are willing to let go of some control to create a more abundant community and I think the answer is yes, but that’s yet to be seen. We are living in the midst of the transition today.
Dave’s Top Three Industry Tips:
- Build. Do it now. Don’t wait and don’t let people tell you that there’s a million things you have to consider before you do it. Think deeply about your business, find the right team that can help you build it, build it quickly and put it out there.
- Learn and measure what you do. Understand how you can measure as many aspects of your business as possible. Employ open source technologies that enable you to build reports and see clearly what working and not working.
- Recast failure as iteration. Throw away the concept of failure. It’s not about growing a business that either works or doesn’t work out of the box, but rather it’s about persistently learning and iterating or pivoting on what you learn again and again.
Dave is one of three interviewees who will be talking at an ESOF 2014 panel session called “I owe my business to my frustration as a scientist” on Monday, 23 June from 3pm-4.15pm (CET) at the Malting Hall. The session will be a more in-depth exploration of the three case studies in the sphere of science communication. It will focus on the genesis of these ideas, and what it took to turn them into a successful, viable business.
If you can’t make the ESOF panel in person, then we will be tweeting using the hashtag #ESOFmyscibus