Summer Projects Update

08. June 2009 · Write a comment · Categories: collaborative science, research ideas · Tags: , , , ,

I posted some initial ideas for projects for our summer students awhile back. I’m pleased to say that the students have been making great progress in the last few weeks (despite, or perhaps because of, the fact that I haven’t been around much). Here’s what they’ve been up to:

Sarah Strong and Ainsley Lawson have been exploring how to take the ideas on visualizing the social network of a software development team (as embodied in tools such as Tesseract), and applying them as simple extensions to code browsers / version control tools. The aim is to see if we can add some value in the form of better awareness of who is working on related code, but without asking the scientists to adopt entirely new tools. Our initial target users are the climate scientists at the UK Met Office Hadley Centre, who currently use SVN/Trac as their code management environment.

Brent Mombourquette has been working on a Firefox extension that will capture the browsing history as a graph (pages and traversed links), which can then be visualized, saved, annotated, and shared with others. The main idea is to support the way in which scientists search/browse for resources (e.g. published papers on a particular topic), and to allow them to recall their exploration path to remember the context in which they obtained these resources. I should mention the key idea goes all the way back to the Vannevar Bush’s memex.

Maria Yancheva has been exploring the whole idea of electronic lab notebooks. She has been exploring the workflows used by the climate scientists when they configure and run their simulation models, and considering how a more structured form of wiki might help them. She has selected OpenWetWare as a good starting point, and is exploring how to add extensions to MediaWiki to make OWW more suitable for computational science, especially to keep track of model runs.

Samar Sabie has also been looking at MediaWiki extensions, specifically to find a way to add visualizations into wiki pages and blogs as simply as possible. The problem is that currently, adding something as simple as a table of data to a page requires extensive work with the markup language. The long term aim is to make the insertion of dynamic visualizations (such as those at ManyEyes), but the starting point is to try to make it as ridiculously simple as possible to insert a data table, link it to a graph, and select appropriate parameters to make the graph look good, with the idea that users can subsequently change the appearance in useful ways (which means cut and paste from Excel Spreadsheets won’t be good enough).

Oh, and they’ve all been regularly blogging their progress, so we’re practicing the whole open notebook science thingy.

Climate Visualizations

21. May 2009 · Write a comment · Categories: research ideas · Tags: , , , , , ,

As a fan of Edward Tufte’s books on the power of beautiful visualizations of qualitative and quantitative data, I’m keen on the idea of exploring new ways of visualizing the climate change challenge. In part because many key policymakers are not likely to ever read the detailed reports on the science, but a few simple, compelling graphics might capture their attention.

I like the visualizations of collected by the UNEP, especially their summary of climate processes and effects, their strategic options curve, the map of political choices, summary of emissions by sector, a guide to emissions assessment, trends in sea level rise, CO2 emissions per capita. I should also point out that the IPCC reports are full of great graphics too, but there’s no easy visual index – you have to read the reports.

Now these are all very nice, and (presumably) the work of professional graphic artists. But they’re all static. The scientist in me wants to play with them. I want to play around with different scales on the axes. I want to select from among different data series. And I want to do this in a web-brower that’s directly linked to the data sources, so that I don’t have to mess around with the data directly, nor worry about how the data is formatted.

What I have in mind is something like Gap Minder. This allows you to play with the data, create new views, and share them with others. Many Eyes is similar, but goes one step further in allowing a community to create entirely new kinds of visualization, and enhance each other’s, in a social networking style. Now, if i can connect up some of these to the climate data sets collected by the IPCC, all sorts of interesting things might happen. Except that the IPCC data sets don’t have enough descriptive metadata for non-experts to make sense of it. But fixing that’s another project.

Oh, and the periodic table of visualization methods is pretty neat as a guide to what’s possible.

Update: (via Shelly): Worldmapper is an interesting way of visualizing international comparisons.

Electronic Lab Notebooks

12. May 2009 · 3 comments · Categories: collaborative science, research ideas · Tags: , ,

Summer projects: I posted yesterday on social network tools for computational scientists. Greg has posted a whole list of additional suggestions.

Here, I will elaborate another of these ideas: the electronic lab notebook. For computational scientists, wiki pages are an obvious substitute for traditional lab notebooks, because each description of an experiment can then be linked directly with the corresponding datasets, configuration files, visualizations of results, scientific papers, related experiments, etc. (In the most radical version, Open Notebook Science, the lab notebook is completely open for anyone to see. But the toolset would be the same whether it was open to anyone, or just shared with select colleagues)

In my study of the software practices at the UK Met Office last summer, I noticed that some of the scientists carefully document each experiment via a new wiki page, but the process is laborious in a standard wiki, involving a lot of cut-and-paste to create a suitable page structure. For this reason, many scientists don’t keep good records of their experiments. An obvious improvement would be to generate a basic wiki page automatically each time a model run is configured, and populate it with information about the run, and links to the relevant data files. The scientists could then add further commentary via a standard wiki editor.

Of course, an even better solution is to capture all information about a particular run of the model (including subsequent commentary on the results) as meta-data in the configuration file, so that no wiki pages are needed: lab notebook pages are just user-friendly views of the configuration file. I think that’s probably a longer term project, and links in with the observation that existing climate model configuration tools are hard to use anyway and need to be re-invented. Let’s leave that one aside for the moment…

A related problem is better support for navigating and linking existing lab book pages. For example, in the process of writing up a scientific paper, a scientist might need to search for the descriptions of number of individual experiments, select some of the data, create new visualizations for use in the paper, and so on. Recording this trail would improve reproducibility, by capturing the necessary links to source data in case the visualizations used in the paper need to be altered or recreated. Some of requires a detailed analysis of the specific workflows used in a particular lab (which reminds me I need to write up what I know of the Met Office’s workflows), but I think some of this can be achieved by simple generic tools (e.g. browser plugins) that help capture the trail as it happens, and perhaps edit and annotate it afterwards.

I’m sure some of these tools must exist already, but I don’t know of them. Feel free to send me pointers…

Data sharing and boundary objects

24. April 2009 · 1 comment · Categories: climate science, data modeling, EGU 2009 · Tags: , , , , , , , ,

Okay, slow day today, as I took some time out to get my talk ready for this afternoon. In the meantime, it gives me a chance to reflect on a few ideas. For example, I’ve seen many talks this week on data sharing, and had some very juicy discussion over dinner last night with Bryan. Two key challenges seem to stand out in this work: (1) the lack of shared ontology between scientific sub-communities who want to share datasets, and (2) the inevitable separation of data from commentaries on that data (which includes problems of knowledge provenance, and meta-data management). The latter problem is endemic because the data sources and the commentary sources are in different communities, operate asynchronously, and often have very different goals.

There seem to be plenty of people considering the technical aspects of these problems, exploring the use of ontology description languages (e.g. OWL and its relatives), and markup languages (e.g. the many application schemas of GML). But very little emphasis has been placed on the human side of this problem. First, the sociological problem of ontological drift has been ignored – the problem that objects gradually change their meaning as they pass between difference communities. (Chalmers gives an overview of various responses to this problem).

A key problem here is that scientific communities have collaborated reasonably effectively in previous centuries through the use of boundary objects (first characterized by Leigh Star). Boundary Objects are…

…  both plastic enough to adapt to local needs and constraints of the several parties employing them, yet robust enough to maintain a common identity across sites. They are weakly structured in common use, and become strongly structured in individual-site use. They may be abstract or concrete. They have different meanings in different social worlds but their structure is common enough to more than one world to make them recognizable means of translation. [Wikipedia defn]

Examples include taxonomies, maps, scientific methods, etc. I talked a little with Leigh about boundary objects in the early 90’s, and I observed that boundary objects are very effective because they represent a minimal shared understanding – just enough so that different communities have some common frames of reference, but no so much than anyone has to work hard on ensuring they have the same mental models.

The problem is that boundary objects fool us into thinking that we share much more meaning than we really do. When we try and embed our boundary objects into computer systems (thinking that we have a shared semantics), we bind the boundary objects to a particular interpretation, and hence they lose their plasticity. As soon as we do this, they are no longer boundary objects. They are brittle reflections of the real boundary objects. Whereas before, the objects themselves could be adapted to each communities needs, now the communities themselves must do the adapting, to the fixed definitions of these frozen objects. No wonder everyone finds this hard!

So what do we do? I don’t really know, but I have some ideas. Lots of small local ontologies, with loose flexible mappings, between them created on the fly by the communities that use them, social tagging style? Or heavier weight tools from psychology for teasing out mappings between terminologies and concepts used by different expert communities, such as repertory grids (e.g. Shaw and Gaines developed a technique applying Rep Grids for exploring conflicting terminology). Or perhaps more flexible ontology languages built over paraconsistent logics?  I’ve played with all these ideas in the past, and think they all have some value. How to exploit them in practical data sharing systems remains a big open question.

Agent-based simulations

14. April 2009 · Write a comment · Categories: climate modeling, climate science, systems thinking · Tags: , , , , , , , , ,

Had an interesting conversation this afternoon with Brad Bass. Brad is a prof in the Centre for Environment at U of T, and was one of the pioneers of the use of models to explore adaptations to climate change. His agent based simulations explore how systems react to environmental change, e.g. exploring population balance among animals, insects, the growth of vector-borne diseases, and even entire cities. One of his models is Cobweb, an open-source platform for agent-based simulations. 

He’s also involved in the Canadian Climate Change Scenarios Network, which takes outputs from the major climate simulation models around the world, and extracts information on the regional effects on Canada, particularly relevant for scientists who want to know about variability and extremes on a regional scale.

We also talked a lot about educating kids, and kicked around some ideas for how you could give kids simplified simulation models to play with (along the line that Jon was exploring as a possible project), to get them doing hands on experimentation with the effects of climate change. We might get one of our summer students to explore this idea, and Brad has promised to come talk to them in May once they start with us.

Oh, and Brad is also an expert on green roofs, and will be demonstrating them to grade 5 kids at the Kids World of Energy Festival.

Collective Intelligence for Global Change

03. April 2009 · Write a comment · Categories: collaborative science, research ideas · Tags: , , , , ,

I just spent the last two hours chewing the fat with Mark Klein at MIT and Mark Tovey at Carleton, talking about all sorts of ideas, but loosely focussed on how distributed collaborative modeling efforts can help address global change issues (e.g. climate, peak oil, sustainability).

MK has a project, Climate Interactive,[update: Mark tells me I got the wrong project – it should be The Climate Collaboratorium. Climate Interactive is from a different group at MIT] which is exploring how climate simulation tools can be hooked up to discussions around decision making, which is one of the ideas we kicked around in our brainstorming sessions here.

MT has been exploring how you take ideas from distributed cognition and scale them up to much larger teams of people. He has put together a wonderful one-pager that summarized many interesting ideas on how mass collaboration can be applied in this space.

This conversation is going to keep me going for days on stuff to explore and blog about:

And lots of interesting ideas for new projects…

Distracted by the footprints

24. March 2009 · 1 comment · Categories: advocacy, philosophy, politics · Tags: , , , ,

At many discussions about the climate crisis that I’ve had with professional colleagues, the conversation inevitably turns to how we (as individuals) can make a difference by reducing our personal carbon emissions. So sure, our personal choices matter. And we shouldn’t stop thinking about them. And there is plenty of advice out there on how to green your home, and how to make good shopping decisions, and so on. Actually, there is way too much advice out there on how to live a greener life. It’s overwhelming. And plenty of it is contradictory. Which leads to two unfortunate messages: (1) we’re supposed to fix global warming through our individual personal choices and (2) this is incredibly hard because there is so much information to process to do it right.

The climate crisis is huge, and systemic. It cannot be solved through voluntary personal lifestyle choices; it needs systemic changes throughout society as a whole. As Bill McKibben says:

“the number one thing is to organize politically; number two, do some political organizing; number three, get together with your neighbors and organize; and then if you have energy left over from all of that, change the light bulb.”

Now, part of getting politically organized is getting educated. Another part is connecting with people. We computer scientists are generally not very good at political action, but we are remarkably good at inventing tools that allow people to get connected. And we’re good at inventing tools for managing, searching and visualizing information, which helps with the ‘getting educated’ part and the ‘persuading others’ part.

So, I don’t want to have more conversations about reducing our personal carbon footprints. I want to have conversations about how we can apply our expertise as computer scientists and software engineers in new and creative ways. Instead of thinking about your footprint, think about your delta (okay, I might need a better name for it): what expertise and skills do you have that most others don’t, and how can they be applied to good effect to help?

How can we help?

19. March 2009 · 3 comments · Categories: collaborative science, research ideas · Tags: , , , , , , ,

A group of us at the lab, led by Jon Pipitone, has been meeting every Tuesday lunchtime (well almost every Tuesday) for a few months, to brainstorm ideas for how software engineers can contribute to addressing the climate crisis. Jon has been blogging some of our sessions (here, here and here).

This week we attempted to create a matrix, where the rows are “challenge problems” related to the climate crisis, and the columns are the various research areas of software engineering (e.g. requirements analysis, formal methods, testing, etc…). One reason to do this is to figure out how to run a structured brainstorming session with a bigger set of SE researchers (e.g. at ICSE). Having sketched out the matrix, we then attempted to populate one row with ideas for research projects. I thought the exercise went remarkably well. One thing I took away from it was that it was pretty easy to think up research projects to populate many of the cells in the matrix (I had initially thought the matrix might be rather sparse by the time we were done).

We also decided that it would be helpful to characterize each of the rows a little more, so that SE researchers who are unfamiliar with some of the challenges would understand each challenge enough to stimulate some interesting discussions. So, here is an initial list of challenges (I added some links where I could). Note that I’ve grouped them according to who immediate audience is for any tools, techniques, practices…).

  1. Help the climate scientists to develop a better understanding of climate processes.
  2. Help the educators to to teach kids about climate science – how the science is done, and how we know what we know about climate change.
    • Support hands-on computational science (e.g. an online climate lab with building blocks to support construction of simple simulation models)
    • Global warming games
  3. Help the journalists & science writers to raise awareness of the issues around climate change for a broader audience.
    • Better public understanding of climate processes
    • Better public understanding of how climate science works
    • Visualizations of complex earth systems
    • connect data generators (eg scientists) with potential users (e.g. bloggers)
  4. Help the policymakers to design, implement and adjust a comprehensive set of policies for reducing greenhouse gas emissions.
  5. Help the political activists who put pressure on governments to change their policies, or to get better leaders elected when the current ones don’t act.
    • Social networking tools for activitists
    • Tools for persuasion (e.g. visualizations) and community building (e.g. Essence)
  6. Help individuals and communities to lower their carbon footprints.
  7. Help the engineers who are developing new technologies for renewable energy and energy efficiency systems.
    • green IT
    • Smart energy grids
    • waste reduction
    • renewable energy
    • town planning
    • green buildings/architecture
    • transportation systems (better public transit, electric cars, etc)
    • etc

Tools for collaborative sense-making

16. March 2009 · Write a comment · Categories: collaborative science, research ideas · Tags: ,

Okay, some of the tools produced by the Essence project are pretty cool:

http://globalsensemaking.wik.is/ESSENCE/Tools

I especially like Debategraph, but mainly for its aesthetic properties when you pull the graph around, and the ability to zoom in to nodes by clicking, rather than how it’s actually being used (mapping debates about whether climate change is happening? That’s so last century). Could we use a tool like this for playing with i* models?