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Introduction

How to use

The Basics

Collecting

Spreadsheets

Data Managing

Visualising

Sharing

Soft Skills

This guide is intended as a quick read for anyone who has or is going to be working in information management in a humanitarian context.

Many of the tips given will hopefully be obvious, but do address repeated mistakes encountered in this sector.

Well managed and accurate data are key to making informed decision within the humanitarian sector. Information management can help to shed light on foreign or rapidly changing environments providing context to decision makers. Good and well managed information flows can make organisations more responsive and efficient leading to increased effectiveness

Connect with the community of Information Managers working in the area

In most instances where humanitarian work is taking place there will be other organisations working on similar projects. By attending local meetings and joining relevant Skype groups you can make contact with other information managers. By sharing knowledge and collaborating on solving problems work can be completed quickly and efficiently.

Save Often

This is a lesson quickly learnt by most through practical experience. Computers can be temperamental things and it can be soul destroying watching your computer crash and losing an hours worth of work. Save the anguish and save often!

Save Multiple Versions

You might regret that big change you made to your work last week. It's best to save multiple versions as you progress so that you can easily revert any changes you have made.

Use sensible file names

There are numerous attributes that you could include in a file name. The most important aspect is to make sure it is understandable to yourself, but also to others who might use your file without the full context. Some suggested components:

• Date - YYYYMMDD
• Description
• Your Initials
• Version Number

Check whether data already exists

It is worth reaching out to the information management community and the government in the area to check that the information has not already been collected by someone else. There is no need to duplicate work that has already been done.

Know how your data will answer your questions

There have been many assessments carried out where most of the data collected was never used. By deciding how you will use your data before you start, you can reduce the amount of redundant questions and make sure the right ones are asked.

Design your data template before you collect it

By designing your data template before collecting data it can give guidance to designing surveys and collecting data from multiple people. If you want to know the damage in each area instead of asking each person an open ended question, providing a template ensures that the data will be collected consistently.

Consistent variable naming

If you are carry out more than one round of surveys make sure that the variable names used in the data are consistent with the previous surveys. Otherwise it can be very difficult for the person analysing the data to quickly match the questions together.

Use secondary data reviews

The data you want may already exist only not in a clean single source. Consider whether it is possible to pull this data together through reviewing and collating other data sources.

An example of this is the Red Cross creating a data set of Ebola Treatment centres from different news articles that mentioned them to create a single consolidated data set which did not already exist.

Check meta data of data

If you are using or referring to other data make sure to check the meta data on how, when, where and by who the data was collected. This will give an indication as to how reliable the data is and in which ways the data can be used.

Understand the difference between quantative data and qualative data.

Qualitative data refers to stories which are intentionally gathered and systematically sampled, shared, debriefed, and analyzed. It will help you understand the context, produce insights and think about which decisions have to be made.

Quantitative data refers to information that can be measured and written down with numbers, standardised and normalised. It will enable you to use metrics to make sound decisions.

Only one piece of information per cell

Having more than one piece of data in a single spreadsheet cell prevents the ability to filter, sum or process a component of the list in any way. One way to resolve this is to duplicate the line for each component of the list.

Record data at a granular level and use pivot tables to aggregate up and create reports

Many times people organise their data in the form it will be reported in. However by aggregating up it restricts possible ways the data can be organised in the future if a new need appears. It is always better to record data in the most basic possible format.

Do not merge cells in a spreadsheet

This can break some functionality in spreadsheets such as pivot tables and filters. An alternative method is to repeat the cell value or use colour to indicate the range.

Keep data types consistent in columns

Try to make sure that columns do not contain mixed data types such as numbers and words.

By making sure all the data types are the same it means that data operations (e.g. sum) can be carried out over the columns.

Keep data names consistent

Consistent data naming means that when a spreadsheet is visualised or summarised that all the correct instances of the data are picked up. Below we have the same organisation spelt different ways and a simple filter may not pick them all up.

Keep all similar data in one sheet or data set

By placing data in separate sheets it hinders the process of aggregation. Below is one spreadsheet with one tab for each district. It could have been put into one table with a column for district as in column A in the second image. If a report is needed for one district a pivot table can be used to generate this.

Do not use colour to represent data

When a machine reads the data or it is copied to another sheet there is a chance that the formating is lost along with the data it represents. Create an extra column for the data attribute. Colour could still be used to highlight data.

Spot check your data

A spot check is a quick process where you pick 5 to 10 random lines of your data and check them thoroughly. It is especially important to do so with derived data.

It helps to check that your process is working consistently through the whole data set.

Check maximums, minimums and sums

When reviewing your data always carry out checks on the extreme. If you have someone over 200 years old in your data you can probably safely assume that something needs correcting in the process.

Sense Check

Does your data make sense? If you have more people affected than the population of the area, something has probably gone wrong in the process.

Check for duplicates

To quickly find and remove duplicates from your data make use of the sorting function on multiple columns. This will order duplicated rows next to each other.

Use official codes to represent regions and districts where possible

In many countries where humanitarians operations are being carried out there will be official codes from administration areas. As place names can be spelt in many ways especially where foreign characters are used it can be hard to compare and join datasets without these codes. Many hours of time can be saved by using them.

Check relationships

If you expect certain relationships between data such as an administration code only belongs to one place this can also be checked with pivot tables. By dropping both fields into the row columns it shows all the matches between the two data columns. Here we can see 524 2 05 25 has been used twice by accident.

Remove Visual Noise

By removing unnecessary visual elements it allows for easier intepretation of the data.

Alignment

Misaligning elements can make a product look distracting and hard for the user to follow. By aligning elements to a grid system you make the product more appealing and easier to comprehend.

Be aware of colour connotations

Colours have different meaning attached to them. If you colour areas on a map red, some people will assume that it may indicate an area of danger when this may not be your intent. It is worth being aware that different colours may have different meanings in various cultures.

Make Infographics and Dashboards

Your pivot table report may tell everything a manager or the public needs to know, however engagement of it will be low. By making infographics and dashboards it will help to get the key figures read.

Share your data in a spreadsheet not a PDF

If you want to share your data for others to use then a spreadsheet is better than a table in a PDF. Data tables in PDFs do not always copy well to a spreadsheet and hours can be wasted getting the data into a usable format. Consider also sharing the data behind maps and reports for other people to make use of.

Share open data on HDX

The Humanitarian Data Exchange is a data sharing platform for humanitarian data. By sharing data we allow more people to make informed data driven decisions.

Share reports and dashboards on Relief Web

By sharing your products on relief web others in the humanitarian community can find them and use them.

Relief Web

Use consistent web addresses for updates

A user may bookmark or directly link to your data set from another location. If you do not use the same web address for updated information this will be missed.

Embed meta-data in the document

Data often gets shared in ad hoc ways through emails and online services. If the meta data is not in the data document then the two can get separated.

Verbal Communication

While information management products can communicate the data and a message, an information manager will often find themselves in meetings and presentations. To be able to verbally communicate the data and to simplify complex ideas is a powerful tool.

Listen

Listen and be patient while understanding the needs of the users of your IM products. Find out their contraints and resources. Summarise what you think they want and get them to agree. Don't build what you think they need, make what they actually need. Follow the steps on the listening wheel below to help.

Distill the questions

The question the user may originally pose or product that the user may ask for might not always be what they actually want. Sometimes people make their own intepretation of solving a problem. By discussing the problem and ideas with them better solutions may be found.

Don't make assumptions about the user

When talking to users or producing products for the user make no assumptions about what they already know. Listen to their constraints and knowledge.

Take breaks and get good sleep

Humanitarian Response can be stressful and exhausting work. Give yourself regular breaks and make sure you get enough sleep!

Get Involved

This is an open source project so anybody can add tips and resources to make it more comprehensive.

Contact Simon Johnson for more details.

This project is hosted on Github.

Thanks To...

Andrew Braye

Heidi El Hosaini

Robert Banick

Jean Mège

Jagoda Pietrzak

Shruti Grover