In this Module and corresponding Activity 1 we will at first concentrate primary on the credibility of the source of information which actually should be understood as one of the aspects of reliability (see below). But before starting Activity 1 it is important to have the whole picture about the criteria for quality of data to understand that credibility of information source is crucial but still only one of the aspect we should look for.

The data and information should have desired quality to be able to support our decisions. We can point out following dimensions of quality that the data and information should have:

• Relevance

• Reliability, validity (accuracy) and completeness

• Accessibility

Relevance of the data is the extent to which they give insight to the questions of the user. The information and data that are gathered should be also relevant for the issue concerned.

The relevance could be viewed in two dimensions:

i.         Relevance for the user of the data

ii.   Relevance concerned the issue (subject matter, target groups etc.)

The above dimensions of relevance are interconnected as we as a recipient want to have relevant data for making relevant decisions so the data should suit or purposes but also be relevant for the target group, problem, questions we want to uncover (for more reference see also the Module 6 Evaluation). The relevance concerning the subject matter is connected to the quality criteria of completeness (see below).

We should ask following questions regarding relevance of data:

Are the data relevant for the issue I am exploring?

What are the data about, what topics and questions are they connected to (or what questions they are invoking)?

What are the data telling me about the topic concerned?

Are data consistent with my area of interest?

Reliability of data refers to the extend we can trust and have confidence in the data collected according the topic concerned. We ask question: can we rely on this data/information to make decision or formulate conclusions about the issue?

To have confidence in the data we should consider following aspects:    

-  Source of the data (credibility) – how is the source of the data or the method used to collect the data trusted, proved to be reliable and credible.

-  Validity – refers to the accuracy of the data. The data should correspond to/with real properties and characteristics of the object it is referring to.

-  Completeness – is concerned about covering the whole scope of the topic (area of interest). We cannot rely on the data for our decision when they would be just partial and not complete. Completeness is also closely connected with different points of view about the topic concerned and with biases.

We should ask following questions regarding source of data (see more in the section How to collect data and How to approach information on the internet):

Who is the author, who created it?

What motivations do the creators have for presenting the information? How does that affect the reliability of the source?

Does the author have any particular interests in the outcome? What are (possible) motivations of the authors?

What are the references for the credibility of the source of information?

What is the perspective of the source/author?

Aren´t the data collected biased towards specific point of view?

What sources is the author using? Are these sources reliable?

We should ask following questions regarding validity of data:

What kind of information is it (fact/opinion/PR-promotion)?

Is the information provided based/backed by evidence?

Is the presented fact actually valid - accurate (evidence is provided, we trust the credibility of the method used)?

Is the information presented coherent itself and with other evidence available?

We should ask following questions regarding completeness of data:

What aspects of the issue does the data / information covers (does it tell all we need/should know)?

Does the data cover all the relevant aspects of the topic?

Are all points of view considered when collecting evidence?

Aren´t the data collected biased towards specific point of view?

Accessibility of data refers to the resources needed to obtain the data. From our perspective it is important to consider resources (people, time, money) we need to invest and willing to invest to obtain the data. Therefore we have to design the research with the resources we have available (e.g. we could not afford to do own survey as we do not have time to performed it, or we can´t afford to buy data from specific dataset).

As collecting data (evidence) is closely connected with the research methods used (desk research/field research) we should consider the aspect of accessibility directly linked with the design of the research (for detail see Module 3 Research phase).

We should ask following questions regarding accessibility of data:

What time will be needed to collect the data using anticipated methods?

What resources (personal, financial) will be needed to collect the data using anticipated methods?

What knowledge/competences will be needed to collect the data using anticipated methods?

Is the effort worth the benefits? Do we really need this data? What will they tell and what we will miss without them (see criterion of completeness)?