29:null 2a:["$","title",null,{"children":"Tereza Iofciu, PhD, Observable Ambassador, Head of Data Science at neuefische | Observable | Observable"}] 2f:T5b2,**How much data do you typically work with?**
Not a lot of data these days, I would say it would all qualify as small data. We have operational data about our bootcamps at work, and otherwise for data viz I would still go for dealing with small or aggregated data. **How do you discover / how do you "get" your data?**
I usually start from a curiosity I have, sometime around a given topic, for example in the 30DayChartChallenge there was daily topics. For the mountain topic, I was wondering how many people live in mountain areas vs plains and seaside.. I started searching for that and it turned out there wasn't really a dataset for it.. I only found a UN report where the data was reported with respect to developing countries and then ended up going on a new path :D **What skills do you have now that you wish you had when you first started coding?**
It's not so much as skills but more about knowing about how I learn. Some people can learn coding by following books and coding exercises, I personally need ulterior motives, like working on a task or a project. Learning about D3.js was more like this, I wanted to do data viz and I basically went on and figured things out, of course, this approach alone means I cannot really call myself a D3.js developer. So if that would be my aim, then I would have to do the books and properly learn at some point, but then I would really know how to apply what I learn quite quickly. 30:Tcfa, **How did you come across Observable?** I saw an online presentation, I think two of the ambassadors were doing a live twitch stream with data viz on observable. **Why did you choose to use Observable?** I always wanted to learn D3.js, since around 2015 when I first stumbled on it.. the learning curve back then seemed a bit too much, as I was more on the backend and data product development side. So I did an out off box data viz with D3 by just editing the expected JSON. So I guess I was always waiting for something like observable to come along. **Where does it sit in your tool chain? How do you+ team (if you use it with a team) use it?**
Observable sits pretty high up, these days if I do data visualization I usually go to Observable, either to get inspired or to work on the visualization. I also used observable for building some tools I needed for work, like a bootcamp planner or a diagram for data science skills. **Top 3-5 reasons you continue to use it?**
I love the community that grew around the platform, people actively suggesting improvements or providing help with the visualizations. The other thing that I really like and would be hard to find somewhere else is the public collection of stunning visualizations that are open source. Thus more or less (:D the more stunning the less easy haha) easy to reproduce **What would make your experience better?**
I suppose code suggestion or correction would be the next thing that would help me. I find JS not so easy to debug, compared to Python 😅 **Before you used Observable, what challenges were you having with:**
Discovering the data - I wasn't really working with open data that much, so due to how Observable has setup the data access options it really changed what kind of data I started interacting with. Also, being able to access the data - I was mostly used to "work" data, so SQL. I really like the ability to call apis or access csv data that Observable provides **What did you want to be able to do that you couldn’t do, or couldn’t do as well as you needed to be able to do?** Do any D3.js data visualization, or have the patience to learn how. **How did Observable help you in your data work? / How does Observable impact your life? **
Making processes simpler: I can do data viz in D3.js without having to know everything about D3.js :D which is essential as I wouldn't have time to dedicate to an in-depth learning approach. Another way it helps me is it lest you test ideas: I sometimes used other's people more complex visualization and just changed the data source to try it out, other times just copied parts of the code and adapted or extended to my needs. The collaborative style of observable makes this possible. **Has Observable lead to any interesting discoveries that may not have been possible otherwise?**
I don't think that I would have gotten started with data visualization if Observable wasn't there and the beautiful work done by others wasn't out there. **How does Observable’s repository of reusable code components help you?**
I think this is the strongest magic Observable has. It feels like reusing and building upon other's people work is the expected way to work. Thus setting a very collaborative tone and culture in the community. 31:T455, **What are some of your favorite notebooks that you've created, or that you're currently working on? Why?** During the #30DayChartChallenge I tried sticking to a template in my [contributions](https://observablehq.com/collection/@terezaif/30daychartchallenge2022), where I had a simple message in the title and a maximum another message in the visualization, I converged to this after seeing work from others and noticing their titles had a message. Basically switching from titles like "look at my distribution" to titles that contain my interpretation and the story I wanted to tell, like "19% of countries have less than 15 trees per capita". One of my favorite visualization I did was on the [marathon world records](https://observablehq.com/@terezaif/marathon-world-record-progression), the data was from Wikipedia and I did use excel to prepare it. I really wanted to do a beeswarm chart and it took a lot of tweaking to get the right bubble sizes in order not to distort the story too much, this made me realize what a thin balance there is between sticking to the truth and making it look pretty. 32:T443,**What are some of your favorite notebooks by other users? / Who inspires you in data visualization?** There are many notebooks and users that inspire me on Observable so I will list a few: - I love how [@pmisner](https://observablehq.com/@pmisner) is also documenting her process in her notebooks https://observablehq.com/@pmisner/day-6-technology-adaption-in-the-us - This collection https://observablehq.com/collection/@saneef/re-plicas-mixes is amazing! - And [@urmilaj](https://observablehq.com/@urmilaj)'s contribution to the #30DayChartChallenge really cool to watch and felt like they took a lot of time to create https://observablehq.com/collection/@urmilaj/30daychartchallenge - I love this playful viz https://observablehq.com/@maxeneg/forest-coverage-by-country - I really liked how beautiful these notebooks https://observablehq.com/collection/@irenedelatorre/coronavirus-tribute are - I am really bad with maps.. but every time I think of doing something with maps I check out [@neocartocnrs](https://observablehq.com/@neocartocnrs) and [@fil](https://observablehq.com/@fil)33:[{"id":"97d8a12385de0dff17200e3567237b78c167aa44935752488ee79a888c16df2609ce7a52441b5e8a33ef602fab5c585646128965e02c83eeb8a45d05de001a1d","href":"https://static.observableusercontent.com/files/97d8a12385de0dff17200e3567237b78c167aa44935752488ee79a888c16df2609ce7a52441b5e8a33ef602fab5c585646128965e02c83eeb8a45d05de001a1d","name":"latetotheparty.png","type":"image/png","lastModified":1665006235249.015,"size":276517},{"id":"c22ac8f93680b6956b4895078459e03b3ce2adddddd06ac8c946fc03f768782e2586ecf5b981124383318dbfbba9d400e543fc272d9a0af0175f3391cbbee7fa","href":"https://static.observableusercontent.com/files/c22ac8f93680b6956b4895078459e03b3ce2adddddd06ac8c946fc03f768782e2586ecf5b981124383318dbfbba9d400e543fc272d9a0af0175f3391cbbee7fa","name":"mountain_people.png","type":"image/png","lastModified":1665006235249.015,"size":350398},{"id":"6a54c7d7c3d104a5ed382b545cc8ccab99b6ab9e09f31ad12516590e632960ba8f221fff9c5cb57155a78bd0c57f9d065548fe9ab242ad98445af1ceb9dffebc","href":"https://static.observableusercontent.com/files/6a54c7d7c3d104a5ed382b545cc8ccab99b6ab9e09f31ad12516590e632960ba8f221fff9c5cb57155a78bd0c57f9d065548fe9ab242ad98445af1ceb9dffebc","name":"Tereza - 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","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"tereza_iofciu_square","database":"$undefined"},{"id":313,"value":"At the heart of Observable is the community. The people who make up our community create, collaborate, connect, and influence with data. The purpose of the Observable Ambassador program is to partner with community members who are actively using Observable.\n\nLearn more about the [Observable Ambassador program here](https://observablehq.com/@observablehq/ambassador-overview).\n\n**Previous Ambassador Stories:**\n[Andrew Wooldridge](https://observablehq.com/@observablehq/andrew-wooldridge-observable-ambassador?collection=@observablehq/observable-blog), [Aaron Kyle Dennis](https://observablehq.com/@observablehq/spotlight-aaron-dennis-observable-ambassador?collection=@observablehq/observable-blog),\n[Maxene Graze](https://observablehq.com/@observablehq/ambassador-maxene-graze?collection=@observablehq/observable-blog)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":319,"value":"---\nIn October 2022, the Observable team caught up with Tereza to learn a bit more about our Ambassadors' diverse background and interests, as well as how Ambassadors are using Observable at work.\n\nFirst, some quick facts.\n\n**Ambassador since:** October, 2021\n\n**Languages and Tools:** D3.js, Python\n\n**Uses Observable for**: Make processes simpler, help test ideas. \n\n**Why Observable?:** I always wanted to learn D3.js and I was always waiting for something like Observable to come along.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":322,"value":"---\n**Tereza, thanks for taking the time to share your story! Where are you located at the moment?**\n
\nThank you for this opportunity! I'm currently in Hamburg, Germany as the Data Science Head of neuefische GmbH - School and Pool for Digital Talent, I'm Vice Chair on python Python Software Verband and DISC Steering Committee Member of [Diversity & Inclusion in Scientific Computing](https://numfocus.org/programs/diversity-inclusion)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":328,"value":"**What are your areas of interest? \n**
\nI enjoy data science, storytelling, building data products as well as managing and growing data teams. \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":44,"value":"$2f","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"InterviewGuide","database":"$undefined"},{"id":147,"value":"$30","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"InterviewGuide1","database":"$undefined"},{"id":245,"value":"**What other data tools do you use in conjunction with Observable? How do they work together?** \n\nI sometimes use Python and Github, sometimes the data wrangling I needed to do was too complex for my JS skills.. or the data is easily available via Python libraries, e.g. astronomical data avaible via [Skyfield](https://rhodesmill.org/skyfield/) library I used in the [moon to earth notebook](https://observablehq.com/@terezaif/moon-to-earth-distance-radial-area?collection=@terezaif/30daychartchallenge). I then use published the final data plus the python code to a public github repository and access the data from there. Another tool that I use quite often is excel, or local text files, if I get data from Wikipedia or places where the data download comes with funny headers that are hard (for me :D ) to parse then in JS.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":223,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":221,"value":"\n

\n \n

\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"latetotheparty","database":"$undefined"},{"id":228,"value":"Another one of the visualizations that I really enjoyed doing was the one about [mountain people](https://observablehq.com/@terezaif/vulnerability-of-mountain-peoples). I had a different plan for it, I originally wanted to find data on how many people live in the mountains vs not.. but that turned out to be tricky to find. During the research, I stumbled on a UN report on the vulnerability of mountain peoples and their access to food. I ended up learning a lot about a topic I had no idea existed. Then I spent hours trying to plot triangles :D which are not standard shapes like squares and circles. Luckily I found a [notebook](https://observablehq.com/@harrystevens/polygon) showing how to plot polygons and then came up with a strategy for aligning the coordinates and mountain heights to the data.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":232,"value":"

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