Tydy is building the world's most comprehensive \u0026 automated onboarding platform

Tydy

Totally Nerdy founder Patrick Pittich-Rinnerthaler joins us in this AMA to talk about his API technology tyny.dev. Slogging tyny.dev is an API technology that makes building a custom API easy, without the need for coding skills. You can find out more about the software . here This Slogging thread by Jack Boreham, ex_pat_pat, Abeer, Mónica Freitas, Limarc Ambalina and SuperSaiyanProgramming occurred in slogging's official #amas channel, and has been edited for readability. Jack Boreham Jan 27, 2022, 12:00 PM Hey @channel, please join me in welcoming our next AMA guest, ex_pat_pat the founder of Totally Nerdy, a software company based in the UK. Totally Nerdy are the creators of a JSON API software that allows you to build a custom JSON API in minutes without coding skills. Please feel free to ask Patrick anything about: http://tyny.dev What a JSON API is Why he created and what it does http://tyny.dev What the life of a software developer looks like Startup businesses Anything technology related! Jack Boreham Jan 27, 2022, 12:02 PM Hi ex_pat_pat, a pleasure to have you with us. Can you explain a bit about yourself and your background to start off this AMA? ex_pat_pat Jan 27, 2022, 12:03 PM Jack Boreham Hi Jack, thanks a lot, likewise! I’m happy to ex_pat_pat Jan 27, 2022, 12:09 PM Where to start, let’s see: I’m a tech guy, first of all, working on different things all the time. Interested in various tech topics from Gaming over Smart Home to web technologies, embedded devices and all that stuff. As Jack mentioned I’m the Managing Director of a UK based Software Company mainly doing web and app stuff. Besides that, I’m very fresh in the startup biz with our new product . This whole career I started almost 20 years ago. http://tyny.dev ex_pat_pat Jan 27, 2022, 12:12 PM I was born and raised in Germany and my beautiful family and I just recently moved to the country we love, which is the UK. Jack Boreham Jan 27, 2022, 12:14 PM ex_pat_pat So what made you create a startup? After all that experience, it's definitely not an easy thing to do! ex_pat_pat Jan 27, 2022, 12:19 PM Jack Boreham It’s quite the opposite I’d like to say, all the experience of 20 years of software development especially for the web made me create the startup in the first place. Because we saw a gap in the market which we try to fill with . http://tyny.dev Jack Boreham Jan 27, 2022, 12:34 PM ex_pat_pat that's interesting, so what gap did you see? How did you come about finding it? ex_pat_pat Jan 27, 2022, 1:07 PM Jack Boreham To explain “the gap” a bit more, I’d like to talk about how software architectures in the modern web are structured, just briefly. Because to understand what does and why it fills this gap you simply need this background knowledge. Bear with me, I try to make it as “non-technical” as possible. http://tyny.dev Starting on the user side of things, you normally interact with some kind of client, a browser, an app, or a desktop application - the Frontend. These clients talk to interfaces that hold your business logic, the code which does something for various use cases - the Backend. On the web, we talk about APIs. Application Programming Interfaces. But it’s not a web thing only. When you now start the process of developing an app, for example, you think about all those different components you’d need to finish your product, a nice looking frontend, APIs to handle your use cases, a database to store information….and off you go, the development begins. But what you don’t might consider from the start is how is your product going to evolve, what are things which might change in the future. And what are the things which a Product Owner (a non-technical person) might like to change without writing code? That’s one thing which does focus on - controllability of your product going forward….in the most standardised way there is, which is in form of a JSON API. http://tyny.dev ex_pat_pat Jan 27, 2022, 1:25 PM Jack Boreham…because of the fact that we couldn’t find a product out there which fosters this idea. There are big players out there that offer you an API as a service for your headless CMS but this approach targets different use cases, like structure data which you need to store all of your data. In the case of Hackernoon, these might be the articles, accounts, etc. not so much unstructured data to control certain things. And then on the other hand you can speak to your developers and write everything from scratch which does make sense a lot of the time but not always. Therefore gives you an affordable option to have that API for unstructured data together with an easy to understand WYSIWYG editor out of the box. http://tyny.dev ex_pat_pat Jan 27, 2022, 1:28 PM Jack Boreham The answer to how we found this gap is up there as well. Way too often did we join projects where only the final product was in focus, not so much the Evolution of it. And you re-iterate and re-iterate and lose a lot of money. Another aspect can be that you might not really know yet if your product is going to fly, so therefore reducing costs and time for developing your product is worth it. Abeer Jan 27, 2022, 3:17 PM Hey Patrick. It’s great to have you here. I’m curious, as a software developer, how did your day to day life look and how did it change after starting tyny.dev? ex_pat_pat Jan 27, 2022, 3:28 PM Abeer Hi there and thanks for your question. Great one. I’m still hands-on developing day today. You see. has just started off and 100% of my time is still working as an Architect/Developer/Consultant for clients of Totally Nerdy Ltd. To make the money I need 😉 It’s as practical as that. http://tyny.dev So the other 30% of my time (yes, you calculated correctly, it’s more than 100% ;)) I spend building the company and the product. It’s like being a jack of all trades from time to time, writing code, thinking about the system architecture, answering questions about MongoDB (I do consultancy work related to that database), thinking about the content we should write next for , and working on marketing strategies. I’m literally done in the evenings! 🙂 http://tyny.dev ex_pat_pat Jan 27, 2022, 3:30 PM But I love those different aspects I must admit. And I couldn’t spend one day without coding myself 😉 Jack Boreham Jan 27, 2022, 4:28 PM ex_pat_pat thank you for the insightful and in detail answers. So you talked about tyny.dev use cases and how it can be used for unstructured data. What other use cases make it stand out from the crowd? ex_pat_pat Jan 27, 2022, 5:48 PM Jack Boreham Thank you. Its biggest selling point is probably the WYSIWYG (what you see is what you get) editor for JSON together with the API that ships it. This enables non-technical people to work with JSON and manipulate it in an easy way. Due to the abstract nature of JSON, the use cases are rather endless but we picked four of them which we actively use to explain the product: Defining and controlling user interfaces Storing and serving static unstructured data like textual contents Rapid prototyping, if you just need an API to ship whatever data into your product fast….or as a first MVP Domain-specific languages, this is a rather huge and abstract case and concludes the others in a way. Just use a more practical example which would be form generation, see https://rjsf-team.github.io/react-jsonschema-form/ In summary, what makes it stand out from the crowd today is that it concentrates on the above things which are based on programming paradigms and development processes rather than being your go-to-tool for building a whole product without code. Mónica Freitas Jan 27, 2022, 9:07 PM Hi ex_pat_pat! What would you say are the main challenges you face in growing your company? ex_pat_pat Jan 27, 2022, 9:44 PM Hi Mónica Freitas, thanks for your question. That’s a really good one. For us at the moment I would say it’s finding the right balance between paid agency work for funding growth employee-wise and the investment we do for our product. Jack Boreham Jan 28, 2022, 9:51 AM ex_pat_pat so are you saying anyone could pick up tyny and use it. No developers needed at all? 😁 ex_pat_pat Jan 28, 2022, 11:14 AM Jack Boreham In general ‘yes’, but you would need to have a product to integrate it with. Whether this product was created with another low-code/no-code platform (without developers) or written from scratch by developers doesn’t matter. Mónica Freitas Jan 28, 2022, 11:32 AM ex_pat_pat, how would you like your company to grow? What's next for Totally Nerdy? ex_pat_pat Jan 28, 2022, 11:43 AM Mónica Freitas first of all I like to grow it in the most organic way possible, which means without external investments and so on. After that I’m aiming to grow it in every direction, which means doing what we’ve always done, delivering solutions to clients, joining projects where our help was demanded and selling our product to people who need it. Therefore Totally Nerdy is potentially very interesting for young talents because we have it all, agency work and a product that we constantly drive forward. Who knows maybe we will become a company focused and evolving around one product in the future only but for now it’s “the best of two worlds”. 🔥 1 Limarc Ambalina Jan 28, 2022, 12:05 PM Hey, ex_pat_pat have you ever tried Skyrim on Alexa? If so, what do you think about it? 😄 ex_pat_pat Jan 28, 2022, 12:08 PM Hi, Limarc Ambalina you’re speaking about Skyrim the Elder Scrolls game? On Alexa?! What does that look like? SuperSaiyanProgramming Jan 28, 2022, 12:07 PM Hey aside from HackerNoon, what are some places, forums, social networks where you posted about your startup to get the word out? ex_pat_pat Jan 28, 2022, 12:10 PM Hey, SuperSaiyanProgramming we’re present in a few of the popular channels like LinkedIn, Google My Business and Twitter. Mónica Freitas Jan 28, 2022, 12:20 PM ex_pat_pat Totally Nerdy is great for new talents. All recent grads want is an opportunity to jump into the job market. As we're on the subject, what type of talents do you feel your company needs the most at the moment? ex_pat_pat Jan 28, 2022, 12:25 PM Mónica Freitas In general, I think we’re going to look for talent all over the board during this upcoming year, from Marketing over Community Manager to Full-Stack Developers. But at the moment we’re going to look at Full-Stack-Developers only to scale our workloads. Jack Boreham Jan 28, 2022, 12:36 PM ex_pat_pat So you have mentioned future hires, but what does the next year look like for what milestones do you want to reach? http://tyny.dev ex_pat_pat Jan 28, 2022, 12:47 PM Jack Boreham I’d like to reach a point where the product does carry itself, which of course means more paying users. This on the other hand will give us more funds for developing the product further. We do have lots more in store for feature-wise. http://tyny.dev ex_pat_pat Jan 28, 2022, 12:55 PM In directly related to the product, I’d like all Product Owners out there to understand the reason behind it: controllability of code. And how this helps future iterations. Which is an approach I’m happy to illustrate and discuss with clients, even if they don’t want to use because they like to implement such a solution themselves. http://tyny.dev Limarc Ambalina Jan 28, 2022, 3:30 PM Yeah ex_pat_pat you mentioned "Gaming over Smart Home" and that was the only smart device game I knew of. It's like this: But not as dramatic lol. It's a real game ex_pat_pat Jan 28, 2022, 3:49 PM Limarc Ambalina Oh sorry, my bad. I didn’t mean “Gaming over Smart Home” I meant “from Gaming to Smart Home” when listing my interests 😉. That’s a funny ad from Bethesda though. Like it! :rolling_on_the_floor_laughing: 1 ex_pat_pat Jan 28, 2022, 3:51 PM Limarc Ambalina Speaking about Gaming though, I recently discovered Google Stadia as a great platform to satisfy my casual appetite for the newest games. Great platform, with flaws though. Jack Boreham Jan 30, 2022, 2:29 PM ex_pat_pat Stadia is great! Thank you for this AMA Patrick a pleasure to have you join us. Where can people find you and check out tyny. dev? 😄 ex_pat_pat Jan 30, 2022, 9:28 PM Jack Boreham Thanks for having me. The pleasure was mine. is the company website, the product website and we’re available on all major socials. I’m more than happy to connect, thanks again for the great conversation and for inviting me. http://totally-nerdy.com http://tyny.dev

Simplifying API with Tyny.dev Founder Patrick Pittich-Rinnerthaler 

Imagine: You are about to sit down with a newly-fetched data set , excited about the insights it will bring you and then you find out it is no use. If you’ve been there, then you know for sure what an untidy dataset is. A statistician from New Zealand once said: Tidy are all alike, but every messy dataset is messy in its own way. Indeed, as data may come in various forms and shapes, sometimes we are inundated with it. datasets As a result, our data science team becomes shortsighted and oops.. disillusioned by mountains of . The only way data is by keeping data clean and organized. unworkable data specialists can facilitate analysis What is Tidy Data? Essentially, tidy data is a term coined by Hadley Wickham in his Tidy Data paper (remember that statistician from NZ?). He defined tidy data as data that is neatly organized and all . set for analysis This way of organizing allows you to easily produce charts, diagrams, and . As it often happens, not all data comes out of the database clean, therefore to efficiently analyze it. summary statistics cleansing it is essential Without further ado, let us break down the principles that allow you keep your data nice and clean. Tidy Data Principles 1. Each row is an Observational Unit We’ll start with one of the basic principles. When you are giving your data the once-over, you should make sure each row .By definition, observation is the individual unit under question. contains an observation If we look at the table above, an observational unit could be called ‘people’. You can see that each person has an individual row on the table and all of the information for that person is in the same row. Observations are included in rows, variables are represented as columns and there is only one observational unit per table. Now THIS is tidy data. 2. Each Column is a Variable A variable is the unit you are assessing. Again, if we turn to our table above, age, hair_color and height fall within the . category of variables In tidy data each variable is represented in a separate column. Okay, now a one-second quiz: What is wrong with this dataset? Yep, you guessed it right. Never put multiple variables in one column, . otherwise your data analysis is doomed 3. Each Cell is a Value If you have got hold of the first two principles, this one . should already be a no-brainer Anyway, we’ll make an extra effort to lay it all out. Each cell should contain only one value. It is also important that all values in the same column are formatted the same way. On this data set, you can see that we have a table with four variables and three observations. Each cell contains one piece of information and . All of our age values are digits, hair color values are whole words – you get the idea. Therefore, this . our values all match dataset is tidy and almost fit for analysis 4. Each Column has a Unique Name , columns should have specific and descriptive names. Let us demonstrate you an example of this principle. In an ideal dataset The third column is labeled hair_color. This is a more specific heading that if we were simply to call it – hair. The word ‘hair’ can refer to anything from hair length to hairstyle. This will help you speed up the analysis process. level of specificity The Final Word Tidy data is an of realizing the full data potential that exists. , it can be used as input into a wide range of other functions. essential part Once your data is tidy

Can We Make Data Tidy?

This post shares about the idea of applying organising method to your digital photos, and I developed an IOS app  with AppleML and PhotoKits to solve the problem. I share my reflection on lean product development strategy and my journey of making the app end-to-end using a minimum, iterable tech stack and strategy. Kon Marie It started with our own problem with managing photos on our phones (which, we found out that many other people also had). As parents with young kids, or more accurately, as humans who own smartphones that have cameras, we co-produce gigantic loads of photos. Phone storage is outgrown so easily (remember when16GBs was enough, then 32GBs, then 128GBs. No, they never really are). How do people back up their phone photos? Our private Facebook or Instagram photo albums help a bit with curating the best shots we want to remember, but quite limited. There are definitely more photos that we want to keep, and we do not wish to upload many of them to these platforms. Cloud photo storage solutions (like Google Photos) can be a back up solution, they keep photos safe. The problem with them is, these 100’s of GBs of photos will be , in other words, 99% photos have very little chance of us browsing through them again. stale The problem of putting everything in the “garage” Anyone that has a physical garage would know this “garage hoarding” problem — stuff that you stash in the garage that you hope will be useful some day. In reality, many of them will just sit there covered with dust forever. Piling up stuff in the “garage” isn’t good for your soul. Photo by NeONBRAND on Unsplash Come back to the photos. We believe the fundamental solution is to keep our photos tidy and in manageable number. And so will be our memories. In fact, a quick review of our recent photos easily shows the 90% — 10% line. 90% of photos are random snaps, spammy shots, the “9 other blurry copies”, cute-but-not-really-needed-to-keep ones. The 10% that worth keeping are the special occasions, the birthdays, the new picnic places, the unique moments. Plus occasional random shots here and there would be fine, too. Indeed, if we could find the 10% we want to keep and clean up the rest, a quick calculation would show my phone storage would be full only after 7 years. And everything can stay on my device. What is the problem we want to solve? Each time the phone is full — we face that dreaded question — should we back up these Gigabytes of photos? Often, we have to — because deleting everything is not an option. Selectively cleaning up thousands of photos is impossible. all Cleaning-up is best done on a basis. Some even say it is the only possible way. If you leave your kitchen untidy for a week, it is 10x as hard to tidy up. regular We acknowledge that there will be people who simply ain’t interested in tidying or organising stuff . For those who are, there will be benefits far beyond reclaiming storage and keeping your photos in check. After all, people bought a best-selling book to learn just about tidying. The Marie Kondo way Marie Kondo, the author of “ ” (who admittedly was on trend an eternity ago) offered some parallel thoughts with her trademark KonMarie philosophy. To simplify your life, so Kondo suggested, you either put your possessions to use, or you should let them go. The life-changing magic of tidying up Removing stuff, while counter-intuitive to human possessive tendency, helps you (stashing stuff in garage doesn’t count) more stuff by focusing only on those that matter. Consequently, it gives you the joy of living in the present. actually keep The idea As all know, once-off clean up is easy. Building a habit is really hard. Or else, the book would not be a best seller. Just look at kitchens or cupboards. This is where the idea of an app came in. How can it help? A reminder A “Swiss knife” photo clean up utility built in with KonMarie principle — the 90% -10% principle (explained above) An AI assistant that help suggest what to keep, based on intelligent image recognition (for instance, photos with faces, or non-blurry photos, on average, are more valuable) and understanding your preference A habit builder (via incentives and clear goal settings ) A safe, friction-less way to clean up your photos with plenty of safety and reversibility measures in place. The last point proved to be extremely important, as I learned after validating the product, which will be elaborated in the product development session. This is how the end product looks like — I have published an app to Apple’s App Store. If you are keen to try the app itself, please visit or get it from the . https://three-a-day.app Apple App Store Starting out At my current workplace (ThoughtWorks Australia), I am blessed to be embedded in a place with excellent innovation and learning culture. (On a side note, with the current pandemic has been harsh for many people — I have to admit we are really fortunate to still have opportunities to work and learn during this difficult time). People here love trying and building innovative things, especially in the data & AI/ML space. Our amazing colleagues have produced really cool stuff, from , to the project using advanced analytics to guide improvement, to using deep learning on edge device. real-time AI-powered sock sorting using event streaming and transfer learning “Strava for Wheelie” counting bees While we all certainly had plenty of fun (you can be sure by the names), we love such projects also because of the learning opportunities. They afford us sharp opinions from a practical experience perspective. In this series of blog posts, I am sharing my learning from this side project. I reflect specifically on applying product thinking, finding a suitable lean strategy that allowed me to finish the app end-to- end in tiny chunks (it took many months), AI/ML and image tech in IOS app development, and the minimum tech stack needed for get my app off the ground. Part 2 —Product thinking: on lean, setting up the project to fail fast, finding an iterable strategy, and finding suitable product goals Part 3 — Technical considerations and the minimum tech stack to finish the app end to end: tools, techniques, architecture, Swift, Apple ML and Photos Kit, App publishing and performance tuning Part 4— Final tips and thoughts— asking for help when you need, using external resources, and how to not let exciting projects consume your life

The “Magic of Tidying for Photos” App — Introduction

Tidy Fridy — a plan for ongoing code care

It's been a while since my last appearance, but I'm excited to be back and to share something truly special with you. In this article, we'll explore my top 10 Google Sheets features that are guaranteed to boost your productivity, speed up your workflow, and make your data handling more efficient. So, without further ado, let's dive into these game-changing tools! https://youtu.be/iHAvhGO0Df0?si=j6ePVf_Y5814jupV&embedable=true Autofill One of the simplest yet most effective features in Google Sheets is Autofill. Imagine you need to input numbers from 1 to 100—instead of typing each one, simply start the sequence, grab the blue dot at the corner of the cell, and drag down. Google Sheets will fill the rest for you. This works not just with numbers, but with days of the week and months of the year too, saving you a significant amount of time. Removing Whitespace and Duplicates When working with large datasets, cleaning up data is crucial. Google Sheets makes this easy with tools to eliminate unwanted whitespace and duplicates. Just select your range, use the "Trim whitespace" option under Data Cleanup, and voilà—clean, tidy cells. Similarly, the "Remove duplicates" feature ensures that only unique values remain, streamlining your data for better analysis. Alternating Colors Enhancing readability can significantly improve the way you interact with your data. The "Alternating colors" feature applies different colors to alternating rows, making your spreadsheet easier to read and reducing errors when reviewing large blocks of data. Embedding Sheets in Web Pages For those who wish to integrate Google Sheets with their websites, the ability to embed sheets is invaluable. Simply choose to embed your document, copy the provided HTML code, and paste it into your website. This allows you to display live, interactive data directly on your web pages. Data Validation for Dates Data integrity can be maintained by restricting input to certain types of data. For example, you can set a cell to only accept dates. This is done through data validation, where you select "Date" as the criteria, and Google Sheets will provide a handy date picker to ensure accuracy. Importing HTML Need to pull data from a webpage into your spreadsheet? The "ImportHTML" function is your friend. Just write the formula, specify the URL, and choose the table you wish to import. This feature not only saves time but also ensures you can quickly update your spreadsheet with the latest web data. Extracting Unique Values To identify unique entries from a range, the "Unique" function is perfect. It extracts distinct values from your selected range, allowing you to see just the unique information without any repeats. Quick Sheet Creation If you need to create a new spreadsheet quickly, just type "sheets.new" in your Chrome address bar. This shortcut instantly opens a new Google Sheet, helping you get to work right away without navigating through menus. Import Range Sometimes, you might need to share data from a spreadsheet without giving access to the entire file. "Import Range" allows you to import specific ranges from one Google Sheet to another, keeping the data synchronized without manual intervention. Google Translate in Sheets Google Sheets can even translate text directly within cells using the "Google Translate" function. Simply specify the cell, the source language, and the target language, and the translation updates in real-time. Bonus Tip Column Stats For data analysts, the "Column Stats" add-on provides quick statistical insights into data columns without needing to apply complex formulas. This tool is excellent for a high-level overview of data characteristics. Inserting Images in Cells A lesser-known but handy feature is the ability to insert images directly into cells. This functionality allows for a more organized display of visual data, which can be particularly useful for inventory lists, directories, and catalogs. I hope you find these tips helpful for making the most out of Google Sheets. If you enjoyed this article, please consider liking and sharing it. Your feedback is always welcome, so feel free to drop a comment below. Don't forget to subscribe for more useful content, and I look forward to seeing you in future articles! Thank you for your support and happy sheeting! It's been a while since my last appearance, but I'm excited to be back and to share something truly special with you. In this article, we'll explore my top 10 Google Sheets features that are guaranteed to boost your productivity, speed up your workflow, and make your data handling more efficient. So, without further ado, let's dive into these game-changing tools! https://youtu.be/iHAvhGO0Df0?si=j6ePVf_Y5814jupV&embedable=true https://youtu.be/iHAvhGO0Df0?si=j6ePVf_Y5814jupV&embedable=true Autofill One of the simplest yet most effective features in Google Sheets is Autofill. Imagine you need to input numbers from 1 to 100—instead of typing each one, simply start the sequence, grab the blue dot at the corner of the cell, and drag down. Google Sheets will fill the rest for you. This works not just with numbers, but with days of the week and months of the year too, saving you a significant amount of time. Removing Whitespace and Duplicates When working with large datasets, cleaning up data is crucial. Google Sheets makes this easy with tools to eliminate unwanted whitespace and duplicates. Just select your range, use the "Trim whitespace" option under Data Cleanup, and voilà—clean, tidy cells. Similarly, the "Remove duplicates" feature ensures that only unique values remain, streamlining your data for better analysis. Alternating Colors Enhancing readability can significantly improve the way you interact with your data. The "Alternating colors" feature applies different colors to alternating rows, making your spreadsheet easier to read and reducing errors when reviewing large blocks of data. Embedding Sheets in Web Pages For those who wish to integrate Google Sheets with their websites, the ability to embed sheets is invaluable. Simply choose to embed your document, copy the provided HTML code, and paste it into your website. This allows you to display live, interactive data directly on your web pages. Data Validation for Dates Data integrity can be maintained by restricting input to certain types of data. For example, you can set a cell to only accept dates. This is done through data validation, where you select "Date" as the criteria, and Google Sheets will provide a handy date picker to ensure accuracy. Importing HTML Need to pull data from a webpage into your spreadsheet? The "ImportHTML" function is your friend. Just write the formula, specify the URL, and choose the table you wish to import. This feature not only saves time but also ensures you can quickly update your spreadsheet with the latest web data. Extracting Unique Values To identify unique entries from a range, the "Unique" function is perfect. It extracts distinct values from your selected range, allowing you to see just the unique information without any repeats. Quick Sheet Creation If you need to create a new spreadsheet quickly, just type "sheets.new" in your Chrome address bar. This shortcut instantly opens a new Google Sheet, helping you get to work right away without navigating through menus. Import Range Sometimes, you might need to share data from a spreadsheet without giving access to the entire file. "Import Range" allows you to import specific ranges from one Google Sheet to another, keeping the data synchronized without manual intervention. Google Translate in Sheets Google Sheets can even translate text directly within cells using the "Google Translate" function. Simply specify the cell, the source language, and the target language, and the translation updates in real-time. Bonus Tip Column Stats For data analysts, the "Column Stats" add-on provides quick statistical insights into data columns without needing to apply complex formulas. This tool is excellent for a high-level overview of data characteristics. Inserting Images in Cells A lesser-known but handy feature is the ability to insert images directly into cells. This functionality allows for a more organized display of visual data, which can be particularly useful for inventory lists, directories, and catalogs. I hope you find these tips helpful for making the most out of Google Sheets. If you enjoyed this article, please consider liking and sharing it. Your feedback is always welcome, so feel free to drop a comment below. Don't forget to subscribe for more useful content, and I look forward to seeing you in future articles! Thank you for your support and happy sheeting!

Top 10 Favorite Google Sheets Features for Everyday Work

This paper is under CC 4.0 license. available on arxiv Authors: (1) Jinrui Yang, School of Computing & Information Systems, The University of Melbourne (Email: jinruiy@student.unimelb.edu.au); (2) Timothy Baldwin, School of Computing & Information Systems, The University of Melbourne and Mohamed bin Zayed University of Artificial Intelligence, UAE (Email: (tbaldwin,trevor.cohn)@unimelb.edu.au); (3) Trevor Cohn, School of Computing & Information Systems, The University of Melbourne. Table of Links Abstract and Intro Background and Related Work Multi-EuP Experiments and Findings Language Bias Discussion Conclusion, Limitations, Ethics Statement, Acknowledgements, References, and Appendix 6 Conclusion In this paper, we introduce Multi-EuP, a novel dataset for multilingual information retrieval across 24 languages, collected from European Parliament debates. The demographic information provided by the Multi-EuP dataset serves a dual purpose: not only does it contribute to multilingual retrieval tasks, but it also holds significant potential for advancing research in the realm of fairness and bias. This dataset can play a pivotal role in investigating issues of equitable representations and mitigation of biases within document ranking settings. Multi-EuP facilitates diverse information retrieval (IR) scenarios, encompassing one-vs-one, one-vs-many, and many-vs-many settings. We demonstrated the utility of Multi-EuP as a benchmark for evaluating both monolingual and multilingual IR. Our study reveals the presence of language bias in multilingual IR when employing BM25. We further validate the effectiveness of mitigating this bias through the strategic implementation of whitespace as a language tokenizer. We propose to conduct future work in three main areas. First, we intend to expand our investigation of language bias to encompass a broader range of ranking methods, including neural methods such as mDPR (Zhang et al., 2021), mColBERT (Lawrie et al., 2023) and PLAID-X(Santhanam et al., 2022). Second, we will expand the dataset by developing an automated API to retrieve data published by the European Parliament (EP), thereby ensuring realtime synchronization of our dataset. Lastly, our current experiments have explored language bias only, but we plan to further investigate gender bias, age bias, and nationality bias. Limitations The limitations of the Multi-EuP dataset are notable but navigable. Primarily, the temporal coverage of the dataset is confined to the past three years. This temporal constraint arises due to the fact that, preceding 2020, documents released by the EU were predominantly available in mono-lingual versions only. However, a potential remedy lies in the amalgamation of the Europarl (Koehn, 2005) collection, enabling a more comprehensive and holistic MultiEuP dataset. Furthermore, it is worth noting the domain skew of the dataset, in that Multi-EuP inevitably centers on political matters. While this presents challenges, particularly in terms of the intricate nuances of political language, it inherently serves as an excellent foundational stepping stone for delving into the intricacies of multilingual retrieval. We believe, however, that this dataset can serve as a launching pad for broader explorations encompassing crossdomain and open-domain transfer learning scenarios, thus contributing to the broader landscape of language understanding and retrieval. Ethics Statement The dataset contains publicly-available EP data that does not include personal or sensitive information, with the exception of information relating to public officeholders, e.g., the names of the active members of the European Parliament, European Council, or other official administration bodies. The collected data is licensed under the Creative Commons Attribution 4.0 International licence. [8] Acknowledgements This research was funded by Melbourne Research Scholarship and undertaken using the LIEF HPCGPGPU Facility hosted at the University of Melbourne. This facility was established with the assistance of LIEF Grant LE170100200. We would like to thank George Buchanan for providing valuable feedback. References Luiz Henrique Bonifacio, Israel Campiotti, Roberto de Alencar Lotufo, and Rodrigo Frassetto Nogueira. 2021. mMARCO: A multilingual version of MS MARCO passage ranking dataset. CoRR, abs/2108.13897. Ilias Chalkidis, Manos Fergadiotis, and Ion Androutsopoulos. 2021. MultiEURLEX - a multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 6974–6996, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. 8 https://eur-lex.europa.eu/cont Jonathan H. Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki. 2020. TyDi QA: A benchmark for information-seeking question answering in typologically diverse languages. Transactions of the Association for Computational Linguistics, 8:454–470. Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020. Dense passage retrieval for opendomain question answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online. Association for Computational Linguistics. Omar Khattab and Matei Zaharia. 2020. Colbert: Efficient and effective passage search via contextualized late interaction over BERT. CoRR, abs/2004.12832. Philipp Koehn. 2005. Europarl: A parallel corpus for statistical machine translation. In Proceedings of Machine Translation Summit X: Papers, pages 79–86, Phuket, Thailand. Dawn Lawrie, Eugene Yang, Douglas W. Oard, and James Mayfield. 2023. Neural approaches to multilingual information retrieval. arXiv cs.IR 2209.01335. Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, JhengHong Yang, Ronak Pradeep, and Rodrigo Nogueira. 2021. Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations. https://github.com/ castorini/pyserini. Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016. MS MARCO: A human generated machine reading comprehension dataset. CoRR, abs/1611.09268. Ella Rabinovich, Raj Nath Patel, Shachar Mirkin, Lucia Specia, and Shuly Wintner. 2017. Personalized machine translation: Preserving original author traits. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 1074–1084, Valencia, Spain. Association for Computational Linguistics. Razieh Rahimi, Azadeh Shakery, and Irwin King. 2015. Multilingual information retrieval in the language modeling framework. Information Retrieval Journal, 18:246–281. Keshav Santhanam, Omar Khattab, Christopher Potts, and Matei Zaharia. 2022. PLAID: An efficient engine for late interaction retrieval. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, CIKM ’22, page 1747–1756, New York, NY, USA. Association for Computing Machinery. Jörg Tiedemann and Santhosh Thottingal. 2020. OPUSMT – building open translation services for the world. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 479–480, Lisboa, Portugal. European Association for Machine Translation. Eva Vanmassenhove and Christian Hardmeier. 2018. Europarl datasets with demographic speaker information. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, page 391, Alicante, Spain. Denny Vrandeciˇ c and Markus Krötzsch. 2014. ´ Wikidata: A free collaborative knowledge base. Communications of the ACM, 57:78–85. Konrad Wojtasik, Vadim Shishkin, Kacper Wołowiec, Arkadiusz Janz, and Maciej Piasecki. 2023. BEIRPL: Zero shot information retrieval benchmark for the Polish language. arXiv cs.IR 2305.19840. Peilin Yang, Hui Fang, and Jimmy Lin. 2017. Anserini: Enabling the use of lucene for information retrieval research. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1253–1256. Xinyu Zhang, Xueguang Ma, Peng Shi, and Jimmy Lin. 2021. Mr. TyDi: A multi-lingual benchmark for dense retrieval. arXiv cs.CL 2108.08787. A. Appendix [8] https://eur-lex.europa.eu/content/ legal-notice/legal-notice.html

Multi-EuP: Analysis of Bias in Information Retrieval - Conclusion, Limitations, and Ethics Statement

This paper is under CC 4.0 license. available on arxiv Authors: (1) Jinrui Yang, School of Computing & Information Systems, The University of Melbourne (Email: jinruiy@student.unimelb.edu.au); (2) Timothy Baldwin, School of Computing & Information Systems, The University of Melbourne and Mohamed bin Zayed University of Artificial Intelligence, UAE (Email: (tbaldwin,trevor.cohn)@unimelb.edu.au); (3) Trevor Cohn, School of Computing & Information Systems, The University of Melbourne. Table of Links Abstract and Intro Background and Related Work Multi-EuP Experiments and Findings Language Bias Discussion Conclusion, Limitations, Ethics Statement, Acknowledgements, References, and Appendix 4 Experiments and Findings We conduct preliminary experiments in both one-vs-one and one-vs-many settings, as described above. We base our experiments on BM25 with default settings (k1 = 0.9 and b = 0.4), a popular traditional information retrieval baseline. Our implementation is based on Pyserini (Lin et al., 2021), which is built upon Lucene (Yang et al., 2017). Notably, the latest LUCENE 8.5.1 API offers language-specific tokenizers, [6] covering 19 out of the 24 languages present in Multi-EuP. For the remaining languages — namely Polish (PL), Croatian (HR), Slovak (SK), Slovenian (SL), and Maltese (MT) — we use a whitespace tokenizer. Methods MRR@k denotes MRR computed at a depth of results. Note that the higher the number the better, and that a perfect retriever achieves an MRR of 1 (assuming every query has at least one relevant document). The choice of setting = 100 aligns with prior endeavors over MS MARCO (Nguyen et al., 2016). k k 4.1 Monolingual IR ( ) one-vs-one We first present results over Multi-EuP in a monolingual setting across the 24 different languages. Specifically, we evaluate single-language queries against documents in the same language. In this configuration, we partitioned our original collection of 22K documents into 24 distinct language-specific sub-collections. Table 2 presents the results broken down across languages. Experimental Setup Table 2 presents the MRR@100 results for BM25 on Multi-EuP. There are two high-level findings: Results and Findings First, Multi-EuP is a relatively easy benchmark for monolingual information retrieval, as the MRR@100 is always around 40 or greater (meaning that the first relevant document is in the top-3 results on average). Indeed, the average MRR across the 24 test languages is 49.61. While direct comparison is not possible, it is noteworthy that for Mr. TYDI, the average MRR is 32.1 across 11 languages. Part of this difference can be attributed to the fact that our relevance judgments are not as sparse as theirs. Second, similar to Mr. TYDI, direct comparison of absolute scores between languages is not meaningful in a monolingual setting, as the document collection size differs. 4.2 Multilingual IR ( ) one-vs-many In contrast to Mr. TYDI (Zhang et al., 2021), Multi-EuP supports one-vs-many retrieval, and allows us to systematically explore the effect of querying the same document collection with the same set of topics in different languages. This is because we have translations of the topics in all languages, documents span multiple languages, and judgments are cross-lingual (e.g., English queries potentially yield relevant Polish documents). For this experiment, we use the default whitespace tokenizer in the Pyserini library. Experimental Setup Results and Findings Table 2 presents the MRR results for BM25 for multilingual information retrieval on 100 topics from the Multi-EuP test set. It’s worth noting that these topics have translationequivalent content in the different languages. Consequently, the one-vs-many approach allows us to analyze language bias. We made several key observations: First, unsurprisingly, having more relevance judgments tends to improve ranking accuracy. Therefore, when comparing English topics with other languages, English exhibits notably better MRR performance. Second, despite there being consistency in the topics, document collection, and relevance judgments, there is a significant disparity in MRR scores across languages, an effect we investigate further in the next section. [6] Provided by the Anaylzer package in LUCENE. https: //lucene.apache.org/core/8_5_1/analyzers-common/ index.html

Multi-EuP: Analysis of Bias in Information Retrieval - Experiments and Findings

This paper is under CC 4.0 license. available on arxiv Authors: (1) Jinrui Yang, School of Computing & Information Systems, The University of Melbourne (Email: jinruiy@student.unimelb.edu.au); (2) Timothy Baldwin, School of Computing & Information Systems, The University of Melbourne and Mohamed bin Zayed University of Artificial Intelligence, UAE (Email: (tbaldwin,trevor.cohn)@unimelb.edu.au); (3) Trevor Cohn, School of Computing & Information Systems, The University of Melbourne. Table of Links Abstract and Intro Background and Related Work Multi-EuP Experiments and Findings Language Bias Discussion Conclusion, Limitations, Ethics Statement, Acknowledgements, References, and Appendix 3 Multi-EuP In our approach, we consider the debate topics to be the queries, and the text of each individual speech delivered by an MEP to be a document. The topics are officially annotated by the EU, and professionally translated into 24 different languages.[5] During preprocessing, we filter out procedural debate topics such as , leaving 1.1K unique topics. They will serve as a valuable resource for assessing language bias in multilingual ranking methods, given that all the topics across different languages are semantically consistent. Topics agenda The 22K multilingual documents within the Multi-EuP dataset originate from MEP speeches during parliamentary debates. Each document annotated with additional metadata, including the date of the speech, the MEP ID, and a link to the video recording for potential multimodal research but not used here. Table 1 shows a detailed breakdown of the language distribution and descriptive statistics of the dataset. We include in our corpus documents only in the original language, as spoken by the MEP, but not their translations into other languages. Our only use of translations is the debate topics themselves. Documents To assess the relevance of documents to a given query, we use a binary relevance judgment, based on whether the speech was part of a debate on the given topic, resulting in one positive relevance judgment per document, meaning that the document collection is much less sparse than Mr. TYDI and MS MARCO, for example. Judgments Multi-EuP covers 24 EU languages from seven families (Germanic, Romance, Slavic, Uralic, Baltic, Semitic, Hellenic), each of which is the official language of one or more member states. Table 1 provides a breakdown of each language’s EU usage, member state distribution, and population, using ISO-639 codes. Languages Multi-EuP encompasses 705 members elected across the 27 member states of the EU. We constructed the MEP dictionary by collecting MEP attributes such as and . We further annotated MEPs with gender and their birthdate, based on Wikipedia profiles and Rabinovich et al. (2017), and manually checked if difference existing. Figure 1 illustrates the gender and age distribution across MEPs, with male MEPs being more than twice as numerous as female MEPs, and the majority falling within the 40– 70 age range. This corpus is rare, perhaps unique, due to its richly detailed speaker demographic information, which enables research on fairness and bias in information retrieval. MEP name, photo, id in EU, nationality, place of birth, party affiliation, spoken language For data splitting, we select two sets with 100 language-specific and distinct topics for development and test set in 24 languages, and keep the remaining topics to the training set. This design choice was made to maintain an ample supply of topics and judgment samples essential for the training of deep learning models, and also facilitate subsequent cross-lingual comparative research. Data Split Similarly to Mr.TYDI (Zhang et al., 2021), Multi-EuP can be used for monolingual retrieval in English as well as non-English languages (eg. Swedish queries against Swedish documents). However, unlike Mr.TYDI, Multi-EuP encompasses multilingual documents and identical multilingual topics, ensuring that queries in different languages can be compared. Consequently, Multi-EuP can support diverse information retrieval experimental tasks. These including scenarios with single one language queries against single one language documents, in other words, monolingual or cross-lingual IR, scenarios with single-language queries against multilingual documents, i.e., multilingual IR, and scenarios involving multilingual queries against multilingual documents, i.e, mixed multilingual IR). Supported Task one-vs-one one-vs-many many-vs-many [5] https://www.europarl.europa.eu/translation/ en/translation-at-the-european-parliament/

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