Your hard work and endless hours will result in conclusions that are only as valid as the data you use to get to them. Because of the importance of data in your research, you want to ensure everything you use is accurate and can hold up to the highest standards of rigor. One small error can destroy months or years of effort.

The thing is, you’re probably using information you assume is accurate. But the amount of data available, and the different storage methods utilized to store that data, continue to increase, while the ability to control what is stored and provided to researchers becomes more complicated to police. As the researcher, you must be the final judge of traditional and non-traditional data, and whether it’s reputable or not. Along the way, it’s essential that you avoid other errors, like these five common mistakes made by researchers as they compile data.

Five Common Errors to Avoid

So how does one end up in a situation where they’re using invalid data? It’s not something that happens to the average researcher paying attention to all aspects of their work. Errors frequently occur due to these five typical causes, and if you understand and recognize them, you can prevent mistakes in your work.

 Procrastination - Research projects can’t be rushed. You may create a timeline and assume your work is going to take you in a specific direction at a set pace, but there are so many variables involved, and any one of them can throw this timeline off course. Most of the unknowns occur in field data collection and analysis, so you should budget a lot of buffer time in this part. However, if you procrastinate and skip the planning aspects, you may be tempted to rush your data collection, which skews the results. Consider the factors that could cause delays and allow leeway for things such as financial delays (i.e., the funds weren’t released in time for your trip), environmental changes (for example, is it raining when you’re supposed to be outside collecting dry data), operational problems (maybe your assistant got sick when you needed help the most), or legal delays (for instance, your permission to enter someone else’s property was not granted timely). Keep Murphy’s Law in mind and plan for anything that can go wrong to go wrong, and move forward happily when it doesn’t.

1. Lack of training - How well you are trained from your past experiences, and how well your team is trained before moving forward in the field, will play a major role in the accuracy of your data collection. This falls partly under the “procrastination” aspect. If you plan ahead with plenty of time, you can train your team thoroughly, or ensure you aren’t rushed as you look for someone with the skills you need to work with you.
   
2. Improper equipment - During the planning process, part of your organization should be listing and procuring the right equipment you’ll need for data collection and analysis. You may have to request to borrow this from other institutions and labs, which can take time. There could be a budget issue in this part of the project, as well, if something vital is more expensive than you planned for. With enough time, you can adjust the funding elsewhere to accommodate this necessary piece of equipment. Using inferior equipment or the wrong types often results in errors in the collection and/or analysis.
   
3. Rushing the schedule - Here’s a common scenario: You planned for the out-of-town aspect of your data collection to take two days. You booked your flight, accommodations, and other travel plans for that period. But during that time, flight delays or other problems reduced your time in the field, and you weren’t able to do the thorough job you planned. To avoid this type of problem, always leave more time in your schedule, even if it costs a little extra. Ultimately, it will save you money.
   
4. Over collecting - In the opposite vein, collecting too much information can be just as dangerous as not collecting enough. Yes, you need metadata and all of the vital information that can or could help you in your research. However, every little piece of data is not necessary, and you’ll be spending precious time later sifting through it all to judge its relevance.
   

See How Your Published Research is Stacking Up With Impactio

Now that you’ve avoided those common pitfalls and gotten your manuscript published, how is it performing in your targeted industry? Check your impact analysis results with Impactio’s free tools.

Impactio is the number one platform for scientific networking and impact analytics in America. Professionals like you head to Impactio to connect with others, conduct CV profiling, and find the right research team members to work with on future projects. When you’re ready to check out your work’s impact or put together a team for your next project, Impactio has all the tools to move you to the next level.