ISO 16439-2014 pdf free download.Information and documentation – Methods and procedures for assessing the impact of libraries.
In library practice. comhrned methods may also be applied in an iterative process where the results of one study are followed up by another to gain better understanding of issues and impact.
User surveys are a prime example. Survey results provide both quantitative and qualitative data which may be followed up with interviews or focus groups to assess impact. Preparation for a new user survey may also include interviews or focus groups to identify specific user concerns that can be used in developing quest Ions.
5.6 Quantitative and qualitative data
5.6.1 General
The findings of the different methods can be differentiated into quantitative and qualitative data, but most methods produce both types of data.
5.6.2 Quantitative data
5.6.2.1 General
Quantitative data are numeric and are usually expressed in measurement units. e.g. number of loans, percentage of interviewees visiting the library.
Much of the information that libraries have traditionally collected and reported — usage counts, purchases, collection size, staff size, budgets – is quantitative. Institutional and community data will also often be quantitative, e.g. socio’economic data, data of student and research performance.
Quantitative data can be collected via all methods mentioned in £.Z to £4. Methods for soliciting user input such as interviews and surveys also provide data that can be analysed quantitatively.
5.6.2.2 Data from different sources
Quantitative data from different sources can be set in relation to each other, and to qualitative data. for better insight into the possible impact of the library. Depending on the reliability and validity of the data, a range of statistical analyses can be performed to Identify key relationships, correlation and significance. One of the most effective approaches is to compare library use data with appropriate individual and institutional data to ascertain whether there is a statistical relationship between library use and performance. Even though there may be a statistically significant relationship, this does not necessarily mean that there i.s a causal rebtionship. Other factors or variables, including those outside the library, may play a substantial role as well. The services of a skilled data analyst may be needed to clarify the nature of these relationships.
5.6.2.3 Data mining
Data mining is a computational process that identifies potentially significant patterns by categorising and analysing quantitative data from different perspectives and dimensions, and summarizing potential relationships and impacts. Data Sets can be analysed using statistical analysis software to determine relationships and significance. Data mining can also show longer term trends.
Most library statistical data deal with use of services, facilities and collections. Data mining can look at relationships between different sets of library data such as user training lessons and the quality of catalogue searches. Data that exist outside the library can be equally or more important in demonstrating Impact. Data mining can be used to determine possible relationships between a library activity and performance in coursework or research, when quantitative data from the library are compared with other data from Inside or outside the library.ISO 16439 pdf download.