#BigData #AdventureTime #pechakucha presentation

The youtube video (practice version) embedded within deck now so that the slides make sense.


The 6 minutes of Big Data discussion talk details are listed here for tomorrow if you would like to attend (it is a PechaKucha talk, 20 slides @20 seconds each):


I will also live tweet it using the tag #BigData if you want to follow along or have any questions I can explore after the talk.  I will be wearing the Finn hat for the first few slides :)

Main findings to report from this adventure
1. Big Data are an amazing opportunity.

2. Ecology is facing similar challenges but can also contribute novel insights to Big Data solution sets.

3. Big Data are all about the letter ‘V’ primarily Volume, Variety, and Velocity. However, Veracity & Variability are becoming increasingly important as we begin to appreciate fully the challenges.

4. Big Data challenges are about the letter ‘C’ including capture, curation, context, and complexity-analytics.

5. Big Data are here to stay, data are evidence, so we need to use to illuminate context, connections, or interactions to affect a greater good in how we live.

6. My personal system primarily for health and life data is define context, focus on interactions using schema & aggregation, and use generalized metrics for synthesis to connect and compare how I am doing. I call this my ‘CIS’tem.  Cheezy I know but works for me as a mnemonic when facing challenges.

7. Smartphones have changed everything.

8. The Cochrane Collaboration & NCEAS are personal inspirations for me to stimulate engagement with Big Data both personally & professionally.

9. Correlation almost always implies causation – use to your advantage.

10. Ecology paradigm + Big Data means focus on interactions in tackling challenges with evidence.





‘#Elementary’ ecology and the value of red herrings


At first, I resented the postmodernism of Elementary. However, I now enjoy the human dimension associated with character development and for its challenges to my thinking about the science of interactions and hypothesis testing. The most recent episode was a brilliant piece for me in terms of my struggles with a paper I am working on with a collaborator that includes contrasting predictions. The episode was entitled ‘Hemlock’, and it is a very apt metaphor (for me at least) for some of the challenges that modern ecologists face.

Here are the elements that inspired me to think about how we sometimes approach ecological interpretations to evidence.

1. Sherlock and Watson investigate the disappearance of a lawyer. Unlike most episodes in contemporary detective/police shows (and even this show), this episode does not begin with a macabre crime scene or body. We never do see the body. Sounds like ecology. Species disappear, and we need to know why. Dramatic global change is occurring, but frequently, the effects are evident only in the gradual loss of a species or process and not through a disaster with a grisly, photographic opportunity for collection of evidence or political leverage. There is no smoking gun. In ecology, we rarely happen upon outcomes that are not driven by complexity or sets of interactions with processes emergent from interdependence.  There can be a smoking gun, but sometimes, it is the indirect interactions with the gun/agent that are real driver of change and not the direct effects. Positive interactions can also have negative effects on ecosystems (i.e. no gun at all but smoke).

smoking gun

2. Sherlock generates both numerous hypotheses (explanations of how the system/phenomenon works) and associated predictions (testable, specific outcomes with evidence) that are refuted as mostly immaterial evidence accumulates in this episode. This is fascinating to me. There are many more failures to support predictions than the usual episode, and it is refreshing. I get the sense that many contemporary experimental community ecology studies certainly generate the hypothesis a priori but refine/adjust the predictions post hoc. I recognize that we have moved beyond strict Popperian falsification, but we are talking about single studies that have associated prediction sets within each paper reported as perfectly satisfied. This seems a bit convenient. My collaborator and I set up the particular experiment we are writing up now with a hypothesis to describe the system but with opposing predictions. Given that ecology embraces complexity, I realized that I have read few papers recently that have contrasting predictions sets that alternatively support or refute the hypothesis. I want that complexity back, and I want to include some of it my papers from now on to highlight the importance of judgment and fair evidence handling alongside appropriate statistics. I know there is a very real bias against non-statistically significant findings and failure to support dominant hypothesis within a subdiscipline, nonetheless, the red herrings we chase make the instances of support all the more robust, honest, and reproducible.

I propose there are at least conceptions of the red herring from the detective genre for ecology.

1. Red herring as distraction. RED HERRING

In the most reviled sense from a publication-bias perspective, failure to support is a distraction at best, a hindrance to scientific progress at worst.  I disagree. Distractions provide insight, illuminate errors, and highlight the importance of effective methods in detecting and reporting false positives.

2. Red herring as Bayesian calibration tool.


Our capacity to assess relative frequency, importance, and experience from a procedural/effective experimental design paradigm is enhanced and accelerated by a clear sense of the red-herring effect within sets of factors or within the manifestations of ecological processes of interest.

3. Red herring as a source of creative inquiry.


Ecology is both science and art. Explicitly seeking the red herring can provide information on processes that are difficult to measure directly, and in imagining and designing experiments wherein a factor does not apply, we better understand the context when it does. The red herring moments are also often synonymous with eureka moments – perhaps not even for you but for the reader in enjoying your narrative of how you solved the ecological mystery at hand.

Failure in science is not a crime, and false leads provide necessary scientific truths.



Enabling scientific discourse: how to make a square table round


I enjoy discussion, working groups, and teaching. Specifically, I love it when folks get brainstorming, and the collective process generates novel and often creative insights or solutions. I have had the good fortune of participating in ’roundtable’ discussions for teaching, service (less fun), science, and sometimes political ones (even less fun). Clearly, I am poorly adapted to political ones, but with respect to the teaching and science roundtables, here are a few tips that I have used successfully to promote discussion.

1. Montessori-level preparation. Collect and provide the best possible materials to stimulate discussion and challenge assumptions. This can include peer-reviewed publications, editorials, but even more importantly for teaching media, online public discourse, and relevant public datasets or evidence.

2. Present process not product. It is easy to teach to product (i.e the book chapter or assigned reading), but to stimulate discussion, focus on process and do #1 with an emphasis on providing insights/decisions associated with the scientific topic. Provide the dataset, first pre-print, reviews or comments associated with product online, or your own challenges in processing the information in the final product.

3. Provide materials well in-advance. If possible, provide not only the primary material (i.e reading) but also one teaser of the additional material that illuminates process.  Then frantically prep more before lecture or lab.

3. Embrace, accept, and use awkward silences to your advantage. When you ask a question and silence follows, it is so hard not to end it. Dignity, nervousness, and lack of hope all prevail.  However, I have found that waiting that extra little bit often gets folks discussing the idea.

4. Take the pressure off. Provide big topics for discussion or questions then allow students even a short period to discuss amongst themselves (even in a big lecture) and you usually end up avoiding #3.  Heck, even circulate around, chat with the smaller groups, get the ‘answers’ and then offer to the class collectively as an additional substrate to promote discussion.

5. Offer an alternative outlet to class-level discussion. Blog, discussion board, twitter, or even emails to solicit additional discussion points.  However, you must bring these back to the class the following week, even in brief, to ensure that students are ‘heard’ and to resuse these ideas for discussion.

6. Finally, the big one, be vulnerable. Explain what you know, admit what you do not, and present the discussion as an opportunity for collective discovery. This makes teaching more fun and that is what it is supposed t0 be anyway right!

1. Prepare materials in advance. Tufte is a big fan of the handout. If possible, send a sample of the topic out to the group to mull over. This can be representative paper, a review, a dataset, or anything concrete that appeals to other modalities and provides appropriate substrate for gestation.

2. Provide an agenda. I abhor outlines in talks but for roundtables they are useful. Even if all of the items are not addressed or if you get out of order, it provides those creative academics a bit of structure to their discussion and thinking and can reduce the likelihood of going down the rabbit hole.

3. Provide sandpaper. Remember, a roundtable is about discussion. A presentation at the beginning is a great idea.  The more polished the better. However, the roundtable should not be a long presentation clearly presenting only the research findings like a job talk. Then at the end, you say questions anyone? You might get lucky, but you might not get any discussion. Hence, do the presentation of course but focus on the ‘sandpaper’ of the topic. What were the elements of the research that bothered you/rubbed you the wrong way or provided a challenge.  Even hinting at these will more likely guide the discussion towards opportunity instead of confirmation of what you found.

4. Provide glue. Same as #3 but mention they elements of the research that really stuck. They are also an opportunity to advance discovery as much as the sandpaper.

5. Provide questions that you do not know the answer to. Risky, yes. Useful, absolutely. After-all, why are you there? If you are the facilitator, aggregate questions from the participants in advance. Ask for them. Then offer them up plus your own at the end of a presentation. This approach kickstarts the discussion even before the discussion begins.

Active versus passive inquiry in both teaching and research roundtables generates more valuable outcomes. These are just the quick tips that I have experimented with, sometimes unsuccessfully, but that can frequently enhance scientific discourse.