Lego floatplane, side view

Lego Floatplane

This is an alternative build for Lego set 42084, Hook Loader. When I thought what to make of it, the two curved panels brought no other inspiration than an airplane. It felt a bit boring at first, but when I started tinkering with it, I realized that it might be a nice challenge to avoid building with straight angles. One fun fact about the design: the fuselage only stays in shape because of the axle-pin that connects the vertical tail to the pin-connector next to it. Besides all the weird angles, the tail planes have moving ailerons and the plane has a great whoosh factor. It doesn’t really float though. More pictures and the digital design can be found at https://frankvandermost.com/lego/floatplane/

Databases for research header image

Book review: Bella Martin and Bruce Hanington, ‘Universal methods of design’

If you are designing software, database systems, websites or other digital stuff, this book deserves your attention. The book describes ‘100 Ways to research complex problems, develop innovative ideas, and design effective solutions.’ as its subtitle claims. Organized alphabetically, each method receives two pages of attention. More tagging and indexing to make the book better accessible would be nice extras, but that does not take away that, as it is, it already is a good read and a treasure trove of design methods. Perhaps not all methods apply to your needs, wishes and circumstances as a designer, but those may change and as long as they don’t, I am sure there will be some interesting methods for you left worth exploring. Read the entire review here.

Graph of a data hub with a relational database at the center

Your data hub

The general idea

You’re likely to just start making your data with whatever software seems ‘natural’ to you. However, hold on for a moment, and consider the near future of your research project. Your table, notebook, network graph, or what have you, may quickly turn into a data hub. Perhaps you should consider a relational database.

Basic pros and cons of a relational database

One important trademark of relational databases is that they are relatively flexible. To be precise, the data stored in tables and woven together through relationships, can easily be changed. Tables can be split up, data can be moved from one to another. Relationships can be redefined, et cetera.

Secondly, relational databases are also quite good at importing and exporting data. In particular exporting is very easy. One can bring data together in a particular view, if only for the export, and export it to the outside world, often in different file formats.

Thirdly, relational databases are not particularly suited for data analysis, although they often come packed with basic possibilities to summarize, do simple statistics, and generate graphs. However for more advanced scientific analysis they are simply not suited. The reverse is also true: the software that is suited for advanced analysis usually does not offer the same flexibility to rearrange data as relational databases do.

These traits make a relational database an excellent hub for your research data. You produce and maintain your data in the database and when the time comes, you export it as needed, import and import it in other software for analysis. This is illustrated in the figure.

Continue reading here for additional topics:
• But, you only use one type of software for analysis?
• Dealing with inflexibility
• Knowing when to start the hub

Digital history group on LinkedIn

If you are a historian with an interest in digital issues, then consider joining the LinkedIn group on digital history.

You find it here.

All new pages on relational databases will be announced there.

The choice of software depends on the structure of your research data

Your choice of research tools is probably determined through your history. Your education and research experience have lead you to certain instruments of choice, that feel ‘natural’ to you. However, from time to time you may want, or are forced to, reconsider. There are some aspects to this. To name some: function ( What do you do with the tool? ), data structure ( What kind of data are you processing and what does it look like? ), costs and availability, ease of migration ( Can you move your data to the other software? Can you move it away again? ), transfer-ability to colleagues ( If you collaborate or hand over, how easily will your colleagues deal with your software? ). Here, I will look at the structure of your data. I will show some examples of research data and discuss which software is in my view best suitable to handle the data.

Continue reading here

How to change the world – book review

A dear friend of mine, M., recommended this book to me when I asked him for feedback on my project in the summer of 2017. A couple of years earlier, when I was looking for a completely new job, he had recommended another title ‘How to find fullfilling work’ from the same series called ‘The school of life’. Since that was such a success I couldn’t wait to read ‘How to change the world’. The read was definitely worth my while, but I finished it with mixed feelings, which I will briefly explain in the first section.

Besides that I realised I can read it in two ways: On the one hand, it offers a lot of practical help for the phase of my project where I feel I know what should be done to get more people doing more things that our planet and humanity need. On the other hand it also implicitly and explicitly gives some answers to my question, which are the topic of the second section.

Continue reading here