Discovering Existing Research Data

"Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike".

Source: https://opendatahandbook.org/guide/en/what-is-open-data/

What to expect from this library guide open data search?

In this library guide you are following a research process of open data search.  You will get more information about the data lifecycle, data repositories and the use of open datasets in your assignments.

The library guide consists of the following information:

- What data do I need?

- How do I find datasets?

- How can I use datasets?

- How can I cite datasets?

- How do I evaluate datasets?

For whom is the library guide useful?

The library guide open data search is useful for students of Hanze UAS in the economic or financial domain and might be the start of exploration of the search of open data. The guide is not comprehensive, but gives you a first insight in open data search.

Steps in the data lifecyle:

1. Creating data: collect data, the research itself, also the raw data
2. Processing data: process the data, make it fit to results, everything from data cleaning, data wrangling, and data formatting to data compression, encrypt the raw data.
3. Analysing data: all the computational and statistical techniques for analyzing data for some purpose: the algorithms and methods that underlie artificial intelligence (AI), data mining, machine learning, undefined and statistical inference,  to gain knowledge or insights, build classifiers and predictors, or infer causality.
4. Preserving data: to secure and safely storage the raw, processed and final data. Final data are deposited in data repositories as a safe place and services the managing of the data for further research.
5. Giving access to data: to develop further research, it is important to know if research data on the topic is already available in a data repository. 
6. Re-using data: the research data can be re-used for further research.

Metadata describe basic characteristics of the data, such as who created the data and what the data file contains. Metadata make it easier for you and others to identify and reuse data correctly at a later moment. You can provide basic human-readable or advanced machine-readable metadata. In both cases there are standards that you can choose to use.

Source: https://www.hanze.nl/eng/research/knowledge-development/research-support/implementation/data-and-sources/metadata

A DOI, or Digital Object Identifier, is a string of numbers, letters and symbols used to permanently identify an article or document and link to it on the web. A DOI will help your reader easily locate a document from your citation. Think of it like a Social Security number for the article you’re citing — it will always refer to that article, and only that one. While a web address (URL) might change, the DOI will never change.

Source:  https://library.uic.edu/help/article/1966/what-is-a-doi-and-how-do-i-use-them-in-citations

Thinking before acting is often good advice, especially when you have to do an assignment, and even more when collecting data. 

Search for suitable datasets that you can use and evaluate the dataset on key elements.

Prepare yourself and organise your research results and document where you got hold of the dataset.

The scope of your research refers to the different dimensions of your research, for example:

• the populational dimension (people, adults, children, teenagers, migrants)
• the temporal dimension (recent developments, economic history)
• the geographical dimension (the Netherlands, the EU, low income countries, etc.)
• the type of subjects (large firms or small startups?)

Setting the scope determines to an important extent what sources are available. Sometimes your research question specifically points to a certain scope: it is difficult to research the 1997 Asian financial crisis using only EU data from 2010.