For our final column, we share some of our favorite tools, apps, platforms, and systems related to the open knowledge ecosystem. These tools are our preferred sources for data collection, analysis, and publishing; for library and learning management systems; and for everyday life.

DATA COLLECTION

KoBoToolbox (kobotoolbox.org) is a great mobile data collection tool designed by and for the international development and humanitarian community. It’s based on Open Data Toolkit (ODK), the de facto standard for mobile data collection. And while ODK offers many tools as part of its toolkit, the initial setup is rather involved. KoBoToolbox requires no setup and focuses on just three core functions: building forms, collecting data, and analyzing data.

Why we love it:

Getting a mobile data collection process off the ground can be a slow, expensive, and inefficient process, but KoBoToolbox makes it significantly easier— particularly when you’re working in a remote environment without stable internet access. Data collectors in the field can administer questionnaires with a tablet or smartphone, and data is stored on their local devices. Later, data can be uploaded to the server.

One thing we particularly love about KoBoToolbox is how easy it is to add new questions. KoBoToolbox comes with a bunch of different question types (select one, select many, text, barcode, map point, date/time stamp, rating, etc.).

ONLINE SURVEYS

While KoBoToolbox is fantastic for mobile data collection, LimeSurvey (limesurvey.org) is our choice for online data collection. It’s a solid alternative to SurveyMonkey or deploying forms via your website.

Why we love it:

LimeSurvey has the ability to create complex surveys in multiple languages. It’s easy to set up new surveys, copy surveys, and display and export results. The user interface that survey respondents see isn’t the prettiest thing in the world, but the ease of using LimeSurvey to administer surveys makes up for it in most cases. Questions can be added easily, duplicated, and reordered, and you can incorporate complicated survey logic. Surveys can be publicly accessible, or individuals can be invited to participate in them. Participants can be added via the import function.

Although LimeSurvey is designed for survey participants to complete their own surveys via the online form, there is a data entry option if you need to convert old, paper-based surveys or want to add a few paper-based responses to a primarily online survey.

Once a survey is live and respondents have answered some questions, admins are able to see responses and basic statistics from within LimeSurvey. If you want to perform deeper analysis with another package, you can easily export the data as a CSV file.

LimeSurvey is an open source PHP web application, so unlike SurveyMonkey, you’ll need to install LimeSurvey on a server, which has its pros and cons. On the plus side, sometimes it is important for security reasons to host your survey on your own server. On the down side, that means it’s one more application to support, secure, update, and maintain.

STATISTICAL ANALYSIS

The R Project for Statistical Computing (r-project.org) is a statistical analysis platform comparable to SPSS or Stata. R has been around for more than 15 years. However, during the past few years, we’ve seen more uptake of R around the world as researchers and scientists have been cutting ties with expensive commercial software in favor of this open source platform.

Why we love it:

For researchers who aren’t working at a university or corporate library with access to an expensive SPSS or Stata license, R provides access to a robust statistical analysis tool.

Plus, R continues to evolve with new packages and add-ons developed and shared by the R community. From within R, you can install specialized packages to simplify common tasks or perform tasks specific to certain kinds of data (spatial, time series, financial). The R community has also developed various libraries to download large datasets. For instance, the CensusAPI package retrieves U.S. Census data, or you can use the FAOSTAT package to download data from the Food and Agricultural Organization (FAO) of the United Nations.

DATA VISUALIZATION TOOLS

These days, any time we need to make a graph, chart, or other type of data visualization, we go straight to the Seaborn library in Python (seaborn.pydata.org).

Why we love it:

While Excel can make basic graphs and charts, and Power BI is superb for creating dashboards, Seaborn is designed to handle statistical data visualizations. It’s a great way to explore data. Through Seaborn, you can easily create scatter plots, swarm plots, and box plots; control the aesthetic style of plots; define color palettes; and more.