 Once you have found a dataset that is potentially suitable for your project, you will need to evaluate its usefulness. You can find most of the necessary information to do this from the catalogue entry. To find this page from the catalogue search, simply click the name of the dataset you want to evaluate or explore. This will take you directly to the catalogue page for this dataset. Once you have found the catalogue page, here are a few suggested steps you can take to start to get to know your data. Firstly, make a note of the full name of the study and the study number. You can use these to easily refind your data in the catalogue and to navigate back to this page at any time. Next, you should read the first few sections of the catalogue page to get a general overview of your data. The details in this section will tell you the full title and any alternative titles of the study, the study's access level and information on who created, collected, deposited and sponsored the data. A couple of key points to check for in this section. Is the year that the data relates to clear in the title? And is the data collection part of a series? Scrolling further down, the topics section helps indicate the general topics covered, whereas the abstract provides more detailed information about the data collection, such as how the study was run and its aims. The contents of the abstract may vary between different datasets. You'll also need to take a look at how the data was collected. The coverage and methodology section includes detailed information about this. The dates of field work tell you when the data were collected. If unclear before, check the data is from the right time period. Now look at the country and population sections. Does the sample relate to the population you're interested in? For example, is it the whole of the UK or in England? Are any groups excluded? Next, does the data have the right observation unit? That is, the unit of analysis, and is this useful for your work? For example, this may be individuals or households. The number of units section tells you the sample size. There are no set rules about what sample size will be sufficient, but a larger sample will generally give more precise results and you'll need a larger sample if you're examining small population subgroups such as ethnic minorities. What data collection methods are used? You should consider how methods of data collection have different strengths and weaknesses and how these relate to your project. Time dimension. Is there any time dimension to the survey and is this suitable for your needs? For example, if you wanted to look at change over time, you would need a study that took a longitudinal or repeated cross-sectional approach. Sampling procedures. This section tells you the sampling method for the data. If you are looking for data to make inferences about a wider population, you will typically need data collected through random sampling. Finally, what kind of data? The UK data service provides access to varied forms of data, including data from smaller-scale qualitative studies. Most data collections can be fruitfully used in secondary data analysis, but may require different methods. Finally, you'll also need to think about whether the data set contains variables that are suitable to help you address your research question. Does it contain variables that measure your key concepts? To think about this, you can examine the documentation, which can be found under the Documentation tab. This tab usually contains the user guide for the data, as well as other useful files such as the interview schedule. Again, this varies by data set, but a good place to start when examining your variables is the data dictionary, which lists all variables contained in the data set. This video has shown you some of the ways you can evaluate data and its suitability for your project. For further guidance with this, please see our dissertation pages on the UK Data Service website.