Commons - IPSC 2016

Commons - Breakout Session IV - IPSC 2016

 

Licensing Open Government Data – Jyh-An Lee

The Romance of the Commons – Sean Pager

3d Bioprinting Patent Boundaries – Tabrez Ebrahim

Governing Medical Commons – Mike Madison, Brett Frischmann & Katherine Strandburg

The North American Mitochondrial Disease Consortium:  An Emerging Knowledge Commons – Brett Frischmann & Katherine Strandburg

 

Licensing Open Government Data – Jyh-An Lee

Abstract: Governments around the world create and collect enormous amount of a wide range of data. For various policy reasons, open data has become a popular government practice and international movement in recent years. It is estimated that more than 250 national or local governments from around 50 developed and developing countries have launched open government data initiatives. Businesses have developed innovative applications, products, and services based on open government data. Open data policies have wide been recognized as a tool to foster government transparency and economic growth. Open data policy involves various legal issues. Among others, it is critically important for governments involved in the open data movement to devise a most appropriate legal way to release its data, and intellectual property (IP) licensing has been viewed as one of the main obstacles for governments’ open data releasing. Entrepreneurs may hesitate to use or re-use government data if there is no reliable licensing or clear legal arrangement. This Article focuses on legal issues associated with open government data licenses. Different government agencies with different policy goals have chosen different licensing terms to release their data. This Article compares current open data licenses and argues that licenses terms reflects policy considerations, which are quite different from those contemplated in business transactions or shared in typical commons communities. The licensing of government data also concerns some fundamental IP issues, which are not covered or analyzed in depth in current literature.

Victoria Stodden: Two questions about incrementalism - 1) What happens when someone applies a totally inappropriate license to data (share-alike, etc.)? 2) How do you cope with evolving / changing data sets?

A: 1) Compatability is the issue. For a creative common license, they can be interoperable. Some regions have taken account of compatibility in the license. But you are right that share-alike is not the most appropriate for government data licenses. In this paper, I argue that preventing commons from shrinking is not a policy goal, because the data is always there. 2) In regions that protect data, there is a danger that if you make a significant addition every year, you could protect data forever.

Sean Pager: <Couldn't hear Sean's question over some construction noise>

A: It's not easy to apply commercial concepts to a publicly funded database.

Brett Frischmann: In the U.S., there was a debate about needing to grant patent rights to incentivize universities to use information generated. Does that pop up in the public sector data context, like weather or traffic data? Do we need exclusive rights to incentivize use of the data?

A: One example, in the Netherlands, data generated about the city of Amsterdam has been made open access.

 

The Romance of the Commons – Sean Pager

I may be the anti-commons paper. I'm trying to push back on some rhetoric used by commons proponents in the copyright context that borders on magical thinking. Romantic commons theory is the opposite of romantic authorship, but ends up at the same dystopian endpoint. Romantic authorship critique: Copyright skeptics picked up a French deconstruction of the importance of authors. Copyright skeptics suggest that corporate entities usurp the benefits and use authors like a stalking horse to that end. 

Now, the romantic commons critique engages in some of the same magical thinking about the Internet and its ability to suspend the gravity of economic and commercial reality. Authors are undervalued and under-rewarded, while powerful corporate entities take advantage of the primacy of free movement of information on the Internet to usurp profits while authors fail to benefit. But the romantic commons critique mistakes volume for quality. People still send money to acquire commercial, professional content. Beyond a certain scale, it is difficult to make creative content for free. The romantic commons critique also mistakes technology for talent: home computers that duplicate 20th century technology doesn't turn the owner of the tech into a valuable creator. There is abundant content, but not of sufficient scope and ambition made by people with sufficient talent. Failing to compensate authors and incentivize creativity leaves us in a situation where, like the Olympics in the early 20th century, the only one who can afford to train / create are the ones who are independently wealthy.

Annemarie Bridy: 1) Define copyright skeptic. 2) Are we undervaluing authors, or simply a certain type of author? You seem focused on a certain type of professional, commercial level author. Why?

Sean Pager: 1) I am responding in part to the logic in papers like Lemley -  IP in a World with No Scarcity. That paper makes a number of the claims I'm directly critiquing. Diane Zimmerman, Eric Johnson - These are the copyright skeptics to whom I'm responding. 2) I think copyright needs to make allowances for non-professional authors, but I think the magic commons thinking undervalues professional level authorship.

Annemarie: You seem to be making a value judgment.

Sean: I am, measured economically, the money people are willing to spend.

Brett Frischmann / Victoria: Can you back that claim in aggregate value?

Sean: I'm thinking per work.

Victoria: If everyone were willing to part with 1/8 of a cent, frictionless, it might generate more money than fewer $5 tickets.

Brett: Are they necessarily mutually exclusive?

Sean: Not necessarily.

<Eager cross-talk>

Mike Madison: Scholars who make your style of argument more powerfully - Jane Ginsburg, among others, are making an express value-based, ethical argument. They are making a desert argument that isn't captured by a value-based, economic argument. The economic argument you are making may not be supportable. You are saying the dynamics of the system aren't making the things we (should) value.\

Sean: I'm talking about the rhetoric, not the economics per se.

Brett: McKenna is working about ambiguity of normative ends. There are a variety of ways to construct the world: fully supported professional class. You may need to think through the tradeoffs, and it may be difficult to make strong claims. 2) I'm not sure this is "commons" - you are using a romantic version of commons that is convenient for you, but I don't know if this is commons.

Mike: It sounds like you are talking to John Perry Barlow in 1996. That's not commons.

Brett: We commons scholars don't talk about commons this way.

Jyh-An Lee: Is there another term that might work?

Mike: I don't know what it is.

 

3d Bioprinting Patent Boundaries – Tabrez Ebrahim

3d Printing is an additive form of printing objects. 3d Bioprinting is a means of printing biologic material (tissues, organs) using the same additive process. For example, you can take tissue from someone's genetic makeup and print a tissue or organ. A potential problem - this sounds like a human organism, and under patent law, you can't patent a human organism. My paper is aims to define the boundaries of patentability and patent scope, and to analyze the ethics and morality involved.

Even if human organisms are not patentable, method claims, for example, might be patentable. In Europe, there is a morality test for living organisms (Article 53(a)).

With regard to ethics / morals, I'm investigating, in part whether patent law does / should embody ethical values in addition to economic values.  

Is 3D bioprinting different from and deserving greater scrutiny than 3D printing? Should it be regulated differently than 3D printing? 

I make two proposals: 1) claims of 3D printing should be shourter to avoid overreacher. 2) patent law should develop ethical limits, perhaps an "ethical PHOSITA (person having ordinary skill in the art), and perhaps the PTO should hire examiners with an ethical background.

One potential patentable claim: a Beauregard claim structure to claim what is printed in an electronic CAD file (storage medium). Are there limits when there are biologic elements? Is this "abstract material," post Alice? Is this a type of manufacture, or just abstract data?

I propose limiting the duration of the patent if we patent it, to enable quicker access. We might also consider regulatory limits on what can be marketed, although still patented.

 

Brett: Say more about ethical PHOSITAs.

Tabrez: I claim that there are ethical norms embedded, but not clearly defined, and we should clarify the ethics. There should be a morality inquiry regarding the PHOSITA.

Sapna Kumar: From an institutional design perspective, the PTO doesn't show any talent for ethical judgment. The FDA, on the other hand, is an entity that makes ethical judgments. Why not the FDA?

Jyh-An: When you say "needs more scrutiny," what needs more scrutiny?

Tabrez: Patentable subject matter - we should be making an ethical inquiry.

Mike: Deven Desai has been doing the most interesting big-picture examination of 3d printing technologies generally. His view is that 3d technology heralds the cusp of another industrial revolution - 3d printing is the steam. By raising the ethical implications of mechanical production and bioethics, you are adding something to the big picture. You have the introduction to a really interesting project, if you think beyond the technical questions for a certain subset of patents, and think broader about the intersection of 3d printing, health law, and ethics.

Brett: I find the patentability of this technology least interesting, and ethical, moral, and regulatory questions more interesting. In these sorts of fields, its often all about the upside. It's hard for me to know what the downsides are. Classifying and describing the downsides of what we do and don't know would be useful from an ethical / regulatory perspective. That's where I want to see you go.

 

Governing Medical Commons – Mike Madison, Brett Frischmann & Katherine Strandburg

This is a descriptive project. Knowledge commons = knowledge and information sharing institutions. The knowledge commons framework is a template for empirical research. We are trying to untangle empirical questions about tragic commons, scarcity, and abundance questions. We are looking at the institutions that try to solve knowledge and information production and distribution questions, coordination of researchers, preservation of information, etc. We are trying to capture what's actually going on, over time, systematically. We argue that collective action to solve these collective action dilemmas is 1) possible 2) without state intervention or strong IP rights. We are inspired by Elinor Ostrom's Instututional Analysis framework. 

Our first book, Governing Knowledge Commons, collects case studies on how knowledge commons are working. Our new book takes the same research framework looking at a more specific framework, Governing Medical Commons. We'll probably focus domain by domain in the future. 

What have we learned so far? No strong conclusions, but here are the headline takeaways: 1) knowledge commons may confront diverse obstacles / social dilemmas, which are not as simple as the free rider / tragic commons binary. 2) Knowledge commons operate / are nested within other complex systems. 3) Knowledge commons often depend on shared infrastructure. 4) Informal governance institutions, including trusted leadership, often play key roles. 5) Commons seem to play an important role in early stages of some industries. 6) There are many and complex motivations for individual participants.

In the medical commons context, we see the same things, but here are a few specific insights: 1) clustering and nesting - we see supply side, demand side, and infrastructural commons. 2) Data curation and coordination problems become clear. 3) Trusted leadership becomes critical. Social hierarchies continue to play a role - not clearly egalitarian systems. 4) Commons, esp. in this context, doesn't mean the absence of state intervention.

 Jyh-An: What's unique about medical commons?

Mike: It's hard to say in the abstract. This is our first domain specific book. But we chose medicine first in part because Brett and Kathy conducted an early case study in a medical area. Many scholars were engaging in relevant research in health and biotech. It's hard to say that knowledge commons are dominant / particularly salient in medicine. I want to do research into education knowledge commons. Michael Burstein is interested in entrepreneur knowledge commons. Then we can start explaining how different knowledge commons are distinctive, if they are. 

Amy Kapczynski: It may be interesting to ask, for example, how communities handle disputes. And it may be value to import this to conventional IP regimes / thinking.

Mike: Ostrom's design principles are curious, because they seem more like rules and guidelines. We spend 6-7 years trying to figure out how to do Ostrom-like inquiry that was flexible enough to investigate what we want to. It is important to think about porting into standard IP literature, and also information science people / IS community. Political scientists, institutional economists, are asking similar questions.

 

The North American Mitochondrial Disease Consortium:  An Emerging Knowledge Commons – Brett Frischmann & Katherine Strandburg

To respond to Amy's last question, we've looked at dispute resolution. For some knowledge commons, it ends up being unimportant. 

Amy: We made need more systematic inquiry into dispute resolution. Some case studies get at it, and some don't.

Brett: Ostrom's design principles arose from 30 years of case studies. We need to cast a broad net as we figure out how to get at what we want to know.

Our latest case study looks at another rare disease and a consortium looking at how to treat the disease. Rare disease researchers face challenges - they are treating a relatively small community, and information sharing and coordination is a critical issue. They want drugs / pharma, but you need data to attract pharma, so you need cooperation from a small community of patients and researchers. The consortium we studied, NAMDC, is a nested commons. The network and the consortium within the network is a good test bed for our framework and methodology.

A nested commons is various consortia that share protocols and research ideas at the macro level, and we zoom in on one member of these Rare Disease Consortia. The consortium we looked at has different members of the commons that belong to different institutions, like NIH, Pharma companies, and clinical research sites. And you can zoom in on a clinical research site like a hospital, and find another commons - different researchers, patients, families, and etc.

Main objectives for RDCRCs: 1) Creating pool of research subjects / patient data; 2) sustain / grow community 3) promote knowledge sharing among members of community, and to outsiders; 4) cooperate with patients in setting research agenda priorities; 5) translating research into treatment.

Consortia are complex environments. Researchers hope that solving mitochondrial disease may actually provide information that helps with other treatment.

In applying the knowledge commons framework to our study of this commons, we focused on seven "action areas", grouped in three categories: 1) Creating / sustaining collaborative research community 2) developing / managing shared pool of research subjects / patient data / biological specimens; and 3) managing relationships with pre-existing mitochondrial disease organizations. NAMDC is a new organization facing two challenges - a) treating patients, and dealing with the diagnostic dilemma - how best to treat patients when you have little data and b) developing a community and governance institutions. This lets us see an early history of a knowledge commons. 

Two problems manifest: research criteria is sometimes too strict, and sometimes there are data entry problems and conflicting opinions about how to code data received.

Sean Pager: A law question / datapoint. A researcher had a relationship with a group of patients, in a quasi-contractual relationship with patients. When the researcher left, the university kept the data, and a court concluded the university could do so, despite patient displeasure, and patient understanding that their relationship was with the researcher. Are these consortiums thinking about the ownership question?

Brett: Interesting question.

Mike: Data ownership is the undiscovered country w/r/t university research. Despite the facts there are massive amounts of data generated, stored, and used, the lack of attention at all to basic law / governance questions is striking.

Victoria: Or everyone assumes they own it.

Brett: Not held as a trade secret.

Annemarie: My husband works in this field, and there are many collective action / coordination problems.

<Excited cross-talk>

Brett: NAMDC owns / restricts access to data. Data is deposited at multiple institutions. 

Victoria: Participants say they want their data to be open, but standard informed consent principles seem to cut in the other direction.

Brett: There is a data use policy. If you are a NAMDC researcher, you can get access, buy you have to have your research project approved. Universities haven't asserted ownership to date. The NIH grants anonymized public access after five years. And I'm not seeing that patients in this research consortium about open access as much as privacy.

Yvette Liebesman: Some members of these communities are willing to take greater risks.

Amy: If hacking data is a crime, you do own data. People can't use property, so they are trying to use contract to govern data, which functionally works a lot like property. Contract does allow for some control over third parties.

Mike: Who the "my" is in "my data" is a complicated question, between patients, researchers, and the university.