2a:null 2b:["$","title",null,{"children":"How we use Observable | EarthScope Consortium | Observable"}] 30:T91e,agu_fall_2022_poster = html`

**Thinking with Data Ergonomically**

UNAVCO Geodetic Data Services is building software more quickly than ever for the web to support the geoscience community. We are writing interactive Observable notebooks in a collaborative manner that allows us to take a fun idea and produce a visualization or frontend interface for our web services in hours or days, rather than weeks and months. You will see examples of interactive maps and graphical user interfaces for searching archival GNSS files, meteorological data, and campaigns. Explore how we easily integrated our own search tools with those of Native Land to support simple and accurate indigenous territory acknowledgements. We have made pedagogical tools aimed at K-12 and higher education for exploring velocity files, geoid height calculations, and even the history of our station network development since the very beginning. Furthermore, we will show you interactive visualizations that depict the topology of our network sensitivity for earthquakes using GNSS stations. “Helping everyone make sense of the world with data, together,” is the way the software and vibrant community called Observable describes its own mission. This platform for rapidly developing frontend applications to serve the scientific community that UNAVCO supports simply has less friction to communicating ideas with code than anything we’ve seen before. Don’t take our word for it, though. We invite you to explore what we have built and published with Observable so that you may poke, prod, modify and build upon what you find. Leave behind tedious developer environments and don’t let technical barriers prevent team members from thinking with data to make big decisions together. The ergonomics of frontend development is changing. We could not be more excited for the impact that will have in the scientific community, education, and anyone who depends on our data.

`31:T926,## It's all about the Browser In 2021 we started experimenting with creating front-end data access "applications" for our web-services using Observable notebooks. Rather than building single page applications for our data access APIs with Vue or Angular and managing the commensurate code base and complexity that those frameworks entail, we figured we might try a different approach. We can rapidly prototype web interfaces built with Observable notebooks and even try using them in production as a means for creating web-based tools for exploring, obtaining, and hopefully understanding the sorts of GNSS data that comes from UNAVCO archives and real-time cloud-based data pipelines from sensors out in the wild. The name of the game here is to build things that are used in the browser to illustrate, explain, compute, explore, and access data which may well be used in tools outside and beyond the scope of what we can do in the browser. We want tools to Just Work™ when you click a link. No install, no toolchain tedium. For many of the same reasons the scientific community adopted Jupyter Notebooks to communicate research and produce what amounts to mini software applications for personal usage as well as more public adoption, we feel Observable notebooks might be the right tool for the job for us to explore data and actually publish software tools. Unlike Jypyter Notebooks, which are evaluated in a centralized server in most cases with results sent back to the client's browser, Observable Notebooks are a bit more more interactive, with computation done client-side and the user interfaces benefiting from using JavaScript (and all its visualization libraries) as the main tool for manipulating the data and the [DOM](https://en.wikipedia.org/wiki/Dom) (what you are looking at on your screen!). This notebook attempts to tour what we have done to create not only data access tools that work both independently and together as part of a *toolchain*, but also what we have explored in a series of pedagogical tools aimed at simply explaining geoscience concepts work with interactive demonstrations. This is an experiment both for UNAVCO and the geoscience community that we support. We hope you will consider joining us in this endeavor by using our notebooks, commenting on them, and certainly suggesting improvements.32:T4d2,Interactivity is the name of the game with Observable notebooks. We won't attempt to make a case for why interactivity is useful in modern software for the browser. We will simply show what it looks like in our usage so far. For those coming from Jupiter notebooks, here are some cool things to consider about Observable notebooks: - JavaScript, executed right here in the browser. - Built in support for all the best from the data-visualization kernel D3 as well as high performance database connectors, file uploading, and all sorts of whiz-bang convenience methods for getting data of basically any shape and form into the browser for easy analysis. Less tool headaches means more energy to focus on communicating ideas to others with the software you write. - The Observable runtime creates a directed acyclic graph of dependencies and runs your notebook cells in whatever order they need to be run without you needing to organize cells in linear execution order. Think like a human, not like a computer! - Built-in code editor with easy version control (Git) and multiplayer editing. - No command-line stuff. 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Observable","thumbnail":"d05852bc84c46f148b0e2b1f3e6f27e8e8db871890d8c498a8aff145726a293a","access_level":"public","create_time":"$D2022-12-02T16:36:56.979Z","update_time":"$D2022-12-15T04:23:31.384Z","view_time":null,"first_public_time":"$D2022-12-05T17:29:32.105Z","has_unpublished_edits":null,"fork":false,"stars":14,"starred":false,"owner":{"type":"team","id":"a505e42d43acc70e","login":"earthscope","name":"EarthScope Consortium","avatar_url":"https://avatars-next.observableusercontent.com/67b67628e86b445b34c9523269b6dd272fcc1cf8cc712983d6749ffdfda4c553","tier":"enterprise_2024"},"version":590,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"f11356ce54f25c8b","login":"bmershon","name":"Brooks Mershon","avatar_url":"https://avatars-next.observableusercontent.com/5331359238b7666c1cb986b48f8e69f0c357feba767a709324063cd52818c420","tier":null}],"members":[{"type":"individual","id":"f11356ce54f25c8b","login":"bmershon","name":"Brooks 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if you saw it at the [AGU Fall Meeting 2022](https://www.agu.org/Fall-Meeting).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":208,"value":"

*The American Geophysical Union (AGU), which was established in 1919 by the National Research Council and for more than 50 years operated as an unincorporated affiliate of the National Academy of Sciences, is now a nonprofit corporation chartered under the laws of the District of Columbia. The Union is dedicated to the furtherance of the geophysical sciences through the individual efforts of its members and in cooperation with other national and international scientific organizations. \n*

\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":563,"value":"- Abstract ID: 1192364\n- Abstract Title: Thinking with Data Ergonomically (with Observable)\n- Session Number and Title: IN42D: Next-Generation Data Systems for Earth Science: Combining Interactive Visualization, Exploratory Analysis, Geographic Information Systems, and High-Performance Data Processing in the Commercial Cloud II Poster\n- Session Date and Time: **Thursday, December 15th; 9:00 AM - 12:30 PM CST**\n- Location: McCormick Place, Poster Hall, Hall A","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":197,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":178,"value":"## Enter Observable","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":11,"value":"tweet(\"1467888262752522244\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":261,"value":"Without further ado, here's a little `` example of a notebook we made that purely serves to communicate some information in an interactive and visually engaging manner with as little code and development effort as possible:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":97,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":567,"value":"## Maps","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":569,"value":"We make a lot of maps.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":573,"value":"

\n \n

With great power comes great restraint in choice of map projections.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":31,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":200,"value":"[Here are all of our collections for you to explore.](https://observablehq.com/@unavco?tab=collections)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":40,"value":"## Interactivity as an aid to *understanding*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":44,"value":"The following *embedded* notebook attempts to *interactively* illustrate the findings published by Blewitt and Lavalleé in 2001 regarding bias in estimation of site velocities.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":42,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":84,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":279,"value":"To prove the point, here's a simple example we made to show how something as simple as the [Mermaid](https://mermaid-js.github.io/mermaid/#/) markup language for generating flowcharts and other diagrams becomes *really fun* when you programmatically generate the markup.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":285,"value":"[Cyclic permutation](https://en.wikipedia.org/wiki/Cyclic_permutation) within a random shuffle becomes apparent if we draw the cycles with a flowchart diagram.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":282,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":73,"value":"---\nAnd here's part of an *explainer* aimed at showing how windows of interest can be considered for a stream of position data from a sensor.\n\n*Click and drag your mouse around on the square below and see what happens.**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":75,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":290,"value":"---\nAnd finally, let's play with another interactive globe that attempts to illustrate UNAVCO network sensitivity to earthquakes of a given magnitude.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":292,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":80,"value":"---\n## Data Access","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":551,"value":"UNAVCO promotes research by providing access to data that our community of geodetic scientists uses for quantifying the motions of rock, ice and water that are monitored by a variety of sensor types at or near the Earth's surface. After processing, these data enable millimeter-scale surface motion detection and monitoring at discrete points, and high-resolution strain imagery over areas of tens of square meters to hundreds of square kilometers. The data types include GPS/GNSS, SAR and Lidar/SfM, strain and seismic borehole data, and Tropospheric data. Most of these can be accessed via web services. In addition, GPS/GNSS data sets, TLS data sets, and InSAR products are assigned digital object identifiers.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":88,"value":"This next embedded notebook demonstrates how a notebook can be used to create a front-end (*for all intents and purposes*) for one or more web-services that we offer as APIs that return JSON structured data for applications built by UNAVCO or anyone else, for that matter. A notebook like the following usually takes a day or two to make and another few days of iterative improvements as staff offer suggestions.\n\nOnce public, a notebook can easily be improved in response to comments left by anyone in the notebook. [Suggestions](https://observablehq.com/@observablehq/suggestions-and-comments) are like merge requests on GitHub. We like receiving *suggestions* from our own team and the rest of the geoscience community that we serve with our notebooks!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":115,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":128,"value":"---\n## Web Assembly","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":401,"value":"Don't worry! It ain't all about JavaScript.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":306,"value":"

\n \n

Drawing on the narrative of the Tower of Babel, the spread of languages across which useful software tools are implemented presents a bit of a problem if we still want to hang around the beautiful Web Browser in the scientific world. Web Assembly to the rescue!

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":130,"value":"Most recently, we have begun experimenting with using Web Assembly to compile code written in a language like, say, *Go* or *C++* to run in the browser. Wow!\n\nThe embedded notebook below shows a **RINEX nav file** that can be uploaded with easy drag and drop by the user being parsed in the browser by a library written by **Henry Berglund** in ***Go***.\n\nHow!?\n\nWell, the Go program was compiled into a .wasm file that we can load in a notebook and execute in the client's browser. The resulting **ephemeris data** that has been parsed from a text-based RINEX file to produce nice JSON data structures that we can interact with using our favorite JavaScript data visualization libraries is then used to render the **ground track of the satellites** you select below on an interactive globe.\n\nRad!\n\nUsing Web Assembly in notebooks is a means for easily building light-weight front-end tools around heavy-lifting computational tools.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":126,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":138,"value":"## An overhead view","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":140,"value":"One of the joys of working in Observable is using myriad examples from other creators as inspiration for novel ways to communicate. When Observable built in the [Mermaid](https://mermaid-js.github.io/mermaid/#/) flowchart markdown language we of course had to try it out!\n\nNaturally, we built this right after making that [*shuffle*](https://observablehq.com/@unavco/dynamic-diagrams) example you already saw.\n\nThe spirit of making Observable Notebooks is to build on smaller building blocks, idiomatic usage, and certainly libraries as you see other examples created in the wild. Examples beget examples! The more notebooks that are made, the easier it is to make more useful notebooks for our own needs. It helps to be able to see the guts; the code that makes other notebooks work in order to better understand and grow as developers.\n\nHere's a programmatically generated flowchart that shows the **topology** of our notebooks we have created so far.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":8,"value":"flowchart","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":169,"value":"## Data Exploration","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":144,"value":"Here's a sneak peek what it looks like to perform basic data analysis in an Observable notebook for the kind of work UNAVCO does. \n\nStarting with a file containing 2.7 *million* rows of data in a comma separated file related to snowpack in Yellowstone, we can unzip a compressed file in the notebook. Then, parsing that file in the browser we use Observable's built in [DuckDB](https://duckdb.org/) in-memory database to create a high performance data structure on which we can execture SQL queries aimed at slicing and dicing our data to extract insights. We can do all this without dealing with anything but a web browser to conduct our analysis. Awesome. Using the Plot library built in to Observable, we can play with the data visually and look for interesting patterns is easy:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":162,"value":"

\n \n

The more stuff that is built into Observable, the more we feel like Inspector Gadget, with just the right tools right at our fingertips.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":157,"value":"

\n \n

We sure love using the Plot library.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":333,"value":"```js\nPlot.plot({\n width: width,\n insetBottom: 25,\n insetRight: 50,\n y: {\n label: \"Depth (cm)\",\n grid: true\n },\n x: {\n label: \"Day of the year\",\n grid: true\n },\n marks: [\n Plot.dot(yearDayAverageData, {\n r: 1.5,\n x: (d) => d.day,\n y: \"avg(depth)\",\n fill: \"#ccc\",\n z: \"year\"\n }),\n Plot.dot(extrema, {\n r: 4,\n x: (d) => d.day,\n y: \"depth\",\n stroke: (d) => (d.type == \"max\" ? \"red\" : \"blue\"),\n facet: \"include\"\n }),\n Plot.line(extrema, {\n r: 4,\n x: (d) => d.day,\n y: \"depth\",\n stroke: (d) => (d.type == \"max\" ? \"red\" : \"blue\"),\n facet: \"include\"\n }),\n Plot.text(extrema, {\n r: 4,\n x: (d) => d.day,\n dy: 15,\n y: \"depth\",\n fontSize: 12,\n text: (d) => d.year\n })\n ]\n})\n```","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":159,"value":"

\n \n

We tend to develop our graphics in an iterative manner. Start simple, and then slowly add complexity as we get a feel for what we are looking at. But the key is to start quickly and not take months to develop, but rather hours or perhaps days instead to get visual results that we can publish.

\n \n

We have experimented with \"daisy chaining\" notebooks together through the use of shareable urls that encode state to allow one tool to pass messages to another with relative ease. Just copy paste and start using the next tool.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":476,"value":"The following diagram illustrates some of the URL connections between our data access tools.\n\nFor example: If you gather GNSS stations by drawing polygons using the [GNSS Data Access](https://observablehq.com/@unavco/gnss-data-access) notebook, you can then gather meteorological data without having to redraw your polygons by simply using a URL that encodes state.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":519,"value":"viewof textarea = Inputs.textarea({\n label: \"Shareable URL\",\n width: width,\n rows: 12,\n disabled: true,\n value:\n \"https://observablehq.com/@unavco/meteorological-data-access?stations=%5B%22%22%5D&polygons=%7B%2293a23dc2cffb2b157687636ffed681dc%22%3A%5B%5B-107.99011185403884%2C19.945050380082208%5D%2C%5B-103.3040562593488%2C16.38372274779752%5D%2C%5B-97.10404424175945%2C14.298123533256216%5D%2C%5B-94.00403823296504%2C14.018510930107922%5D%2C%5B-93.28310660301386%2C15.760247958083156%5D%2C%5B-93.57147925499449%2C19.67374244024677%5D%2C%5B-96.7435784267845%2C21.428785679179782%5D%2C%5B-103.66452207432663%2C22.43191466906829%5D%2C%5B-107.70173920205917%2C22.764703850096694%5D%2C%5B-107.99011185403884%2C19.945050380082208%5D%5D%7D&rinex2Selections=%5B%22obs%22%5D&rinex3Selections=%5B%5D&referenceFrames=%5B%5D&analysisCenters=%5B%5D&sampleIntervalSelection=%5B%22%3E1%22%5D&antennaSelection=null&receiverSelection=null&radomeSelection=null&startDate=%222022-12-02%22&endDate=%222022-12-09%22\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":468,"value":"mermaid`flowchart LR\n\nweb-services(Web Services API)\n\nsubgraph Data_Access\n gnss-data-access(GNSS)\n meteorological-data-access(Meteorological)\n campaign-data-access(Campaign)\n station-metadata(Station Metadata)\n event-data-access(Event)\nend\n\nweb-services-- import --> land-acknowledgement\nweb-services-- import --> gnss-data-access\nweb-services-- import --> meteorological-data-access\nweb-services-- import --> event-data-access\nweb-services-- import --> campaign-data-access\n\n\ngnss-data-access-. URL .-> meteorological-data-access\ngnss-data-access-. URL .-> gnss-data-access\nmeteorological-data-access-. URL .-> gnss-data-access\nmeteorological-data-access-. URL .-> meteorological-data-access\n\nevent-data-access-. URL .-> gnss-data-access\nevent-data-access-. URL .-> event-data-access\n\nweb-services-- import --> station-metadata\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":484,"value":"

\n \n

A polygon drawn in the GNSS Data Access notebook to select stations.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":479,"value":"

\n \n

A polygon transferred through a shareable URL from one notebook to another.

\n \n

See a bug or have a request. Just leave a comment.

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":384,"value":"### 2. Or, you can fork a notebook, modify it, and use [suggestions](https://observablehq.com/@observablehq/suggestions-and-comments) to have us merge your changes.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":166,"value":"---\n## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"","database":"$undefined"},{"id":300,"value":"html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"import { tweet } from \"@observablehq/tweet\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"import { flowchart } from \"@unavco/notebook-flowchart\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"import { chart as networkSensitivity } from \"@unavco/network-sensitivity\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"},{"id":528,"value":"import { usaMapCoordinates, worldMapCoordinates } from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1"}} 2f:"$2e:body"