Category Archives: Online Tools / Apps / Data Sources

birds, bees, bugs, plants

On the green infrastructure front, there are lots of resources out there on what plants support what kinds of wildlife.

“Bugs” have a PR problem as a group, but they have their charismatic members – bees, butterflies, and dragonflies to name a few. If you support these, you will probably support others by accident. There is plenty of information out there, for example:

The Xerces Society for Invertebrate Conservation has a ton of free publications on plants, pollinators, and design; including bee-friendly plant lists for all regions of the United States and several other countries.

The Lady Bird Johnson Wildflower Center has a ton of free native plant information, including recommended mixes to attract various types of wildlife in all U.S. states and Canadian provinces.

Finally, the Natural Resources Conservation Service (part of the U.S. Department of Agriculture) has free fact sheets on about a thousand plants.

A lot of good can be done for wildlife and humanity on small scraps of land, and even more good could be done if we gave serious thought to how all those scraps of land fit together and connect to larger parks and preserves. So let’s get out and plant something this spring, even if it’s small. Or if you have a scrap of land but you don’t feel like planting anything, find a frustrated armchair gardener who doesn’t have their own scrap and let them plant something on yours.

how U.S. taxes are spent

In a poll of U.S. taxpayers, 95% of respondents had no idea how much the country spends on foreign aid, which is much less than 1%. It just shows that although rational people can disagree on how our tax money should be spent, we are not having a rational debate because most of us have no clue what it is really being spent on. A taxpayer receipt is a simple idea to help cure this problem. Ideally this should be done by the IRS or Treasury Department, but the White House has stepped in to do it since nobody else will.

I picked a hypothetical married couple with children making an income of $80,000 per year. There are a million different ways you can slice it. But no matter what you do, the biggest categories jump out at you. Income tax is only about 40% of what the government takes in from this family, with Social Security and Medicare taxes making up the other 60%. Pensions for retired people make up the majority of how the money is spent, with Social Security alone making up almost half. Even without an offical public health care system, the federal government spends a lot on health care – almost 20% of all the money spent between Medicare (for older people) and programs to help lower-income people (Medicaid and children’s health insurance programs mostly). Of course, state and local governments also tax and spend on health care, which is not reflected here.

The military makes up around 10% of all federal spending. If you add veteran’s benefits (I’m double counting here, since these include retirement and health care) and homeland security, that number comes to more like 13%.

So however you slice it, the big numbers are retirement, health care, and defense. If we want to make significant changes in either the amount of tax, or the outcomes of government programs, we should focus most of our debating energies in these areas.

 

R graph catalog

Here’s a nice catalog of graphs made with R, along with source code for each. Some of the images were broken or missing when I tried it, but hopefully they’ll get that fixed. (By they way, this is my personal experience with interactive “Shiny” apps so far – I love the idea and the look, but there always seems to be something wrong that needs to be fixed, and fixing it takes more time and requires more specialized training than just dealing with plain old code. At first, I thought it might be a productivity enhancer, but instead it’s a drag when your job is not to build cool-looking apps, but to produce useful data analysis results in a reasonable amount of time.)

open source street noise model

Here’s an open-source code for modeling street noise propagation. It’s written in R and open source database and GIS tools.

This paper describes the development of a model for assessing TRAffic Noise EXposure (TRANEX) in an open-source geographic information system. Instead of using proprietary software we developed our own model for two main reasons: 1) so that the treatment of source geometry, traffic information (flows/speeds/spatially varying diurnal traffic profiles) and receptors matched as closely as possible to that of the air pollution modelling being undertaken in the TRAFFIC project, and 2) to optimize model performance for practical reasons of needing to implement a noise model with detailed source geometry, over a large geographical area, to produce noise estimates at up to several million address locations, with limited computing resources. To evaluate TRANEX, noise estimates were compared with noise measurements made in the British cities of Leicester and Norwich. High correlation was seen between modelled and measured LAeq,1hr (Norwich: r = 0.85, p = .000; Leicester: r = 0.95, p = .000) with average model errors of 3.1 dB. TRANEX was used to estimate noise exposures (LAeq,1hr, LAeq,16hr, Lnight) for the resident population of London (2003–2010). Results suggest that 1.03 million (12%) people are exposed to daytime road traffic noise levels ≥ 65 dB(A) and 1.63 million (19%) people are exposed to night-time road traffic noise levels ≥ 55 dB(A). Differences in noise levels between 2010 and 2003 were on average relatively small: 0.25 dB (standard deviation: 0.89) and 0.26 dB (standard deviation: 0.87) for LAeq,16hr and Lnight.

 

automated aggregation of scientific literature

I am intrigued by this example from Stanford of computerized review and synthesis of scientific literature:

Over the last few years, we have built applications for both broad domains that read the Web and for specific domains like paleobiology. In collaboration with Shanan Peters (PaleobioDB), we built a system that reads documents with higher accuracy and from larger corpora than expert human volunteers. We find this very exciting as it demonstrates that trained systems may have the ability to change the way science is conducted.

In a number of research papers we demonstrated the power of DeepDive on NMR data and financial, oil, and gas documents. For example, we showed that DeepDive can understand tabular data. We are using DeepDive to support our own research, exploring how knowledge can be used to build the next generation of data processing systems.

Examples of DeepDive applications include:

  • PaleoDeepDive – A knowledge base for Paleobiologists
  • GeoDeepDive – Extracting dark data from geology journal articles
  • Wisci – Enriching Wikipedia with structured data

The complete code for these examples is available with DeepDive.

Let’s just say an organization is trying to be more innovative. First it needs to understand where its standard operating procedures are in relation to the leading edge. To do that, it needs to understand where the leading edge is. That means research, which can be very tedious, and time consuming. It means the organization is paying people to spend time reviewing large amounts of information, some or even most of which will not turn out to be useful. So a change in mindset is often necessary. But tools that could jump start the process and provide short cuts would be great.

This is my own developing theory of how an organization can become more innovative: First, figure out where the leading edge is. Second, figure out how far the various parts of your organization are from the leading edge. Third, figure out how you are going to bring a critical mass of your organization up to the leading edge – this is as much a human resource problem as an innovation problem. Fourth, then and only then, you are ready to try to advance the leading edge. I think a lot of organizations have a few people that do #1, but then they skip right to #4. Then that small group is way outside the leading edge while the bulk of the organization is nowhere near it. That’s not a recipe for success.

Scratch

“Scratch” is another programming language supposedly aimed at children.

Scratch Overview from ScratchEd on Vimeo.

If you watch the TED talk in the first link, there is an analogy I like – just because you use technology created by others (web browsing, texting, etc.) doesn’t make you fully literate in that technology. It is akin to being able to read but not able to write.

online productivity and creativity apps

This article from Civicly lists useful online apps for planners – actually, I think they are useful for anybody whose job involves trying to solve problems with a little creative latitude. I especially like the free tools for infographics – it looks like you can pick a template and customize it for your data.

habitat fragmentation and connectivity

Did you ever wonder how to quantitatively analyze the quality, shape, and degree of connectivity of natural habitats? Well, there’s an open source app for that, called FRAGSTATS, and good documentation that describes the theory behind it. To summarize, it looks at area and edge, shape, core area, contrast, aggregation, and diversity. Here are just a few quotes describing some of the metrics.

“Core area is defined as the area within a patch beyond some specified depth-of-edge influence (i.e., edge distance) or buffer width.”

“Contrast refers to the magnitude of difference between adjacent patch types with respect to one or more ecological attributes at a given scale that are relevant to the organism or process under consideration.”

“Aggregation refers to the tendency of patch types to be spatially aggregated; that is,
to occur in large, aggregated or “contagious” distributions.”

“FRAGSTATS computes 3 diversity indices. These diversity measures are influenced by 2 components- richness and evenness. Richness refers to the number of patch types present; evenness refers to the distribution of area among different types.”