2.4.2: Tools & Technology For Your Research

Tools and Technology for Your Research 

As you define your methodological approach, you’ll also want to think about identifying and acquiring the tools you will need for working with any data you collect and analyze so you can plan a research workflow. In Table 2, you can see some suggested tools for working with different types of data, as well as factors to think about in terms of managing your data.

There are both licensed and free-to-use software for most data-related research tasks.

Some factors to consider as you decide on tools or technology:

• Licensing and technology access:
  • Will everyone on the research team have access to the technology, even if they are at different institutions?
  • Are licenses for this project perpetual or time-limited?
  • Does the software work on the types of computers used by members of the research team?
  • Can I export data from this tool to other programs, or am I limited to using this software?
  • Where is the data stored when I use this technology? If it’s a cloud-based program, does the data get shared with the provider?
• Learning a new technology
  • What kind of support is provided by the software vendor?
  • What community-developed resources are available (such as online tutorials or spaces where I can pose questions to other researchers)
  • How long will it take to learn this software?

Table 2: Data Types and Tools for Collection and Analysis (with example tools, free-to-use tools bolded)

This table shows some of the common types of data you will use in LISLibrary and Information Science An interdisciplinary field that examines how physical and digital information is organized, accessed, collected, managed, disseminated and used, particularly in library settings.-based research projects and notes examples of both proprietary and free-to-use programs you might consider.

Data type	Collection (Example Tools)	Analysis (Example Tools)	Data ManagementData management The ways a researcher collects, organizes, stores, and accesses data they collect for research. Creating a data management plan allows a researcher to know what data they will be collecting and how they will store and organize it during the research project. Considerations
Surveys	– Survey collection software such as Qualtrics or Google Forms – Paper forms	– Spreadsheet software (Excel, Google Sheets) – Statistical analysis programs (SPSS, Stata, PSPP, R) – Open-ended questions may be analyzed using spreadsheet programs or programs associated with qualitative data (see below).	Data collected from human subjects requires protection in accordance with an IRBInstitutional Review Board A group that is charged with overseeing and approving research projects. The group ensures that research projects are ethical, meet regulations and standards, and protect any human subjects involved in the research.-approved protocol and your own agreements with participants about how you will protect their data and identity or share data outside of your research team.
Interviews, focus groups, or oral histories  Photos or videos	– Video or audio recording hardware  – Online meeting software (Zoom, Teams)  – Transcription software (Otter.ai, Trint)  – Archival images	– Word processing software Spreadsheet software (Excel, Google Sheets)  – Paper and marking materials  – Qualitative data analysis software (QDAS) (NVivo, Atlas.ti, MAXWDA, Taguette)  – Image management and organization (Tropy)
Large text or numerical data sets	– Content databases (e.g. Lexis Nexis)  – Web scraping tools  – Social media APIs  Provided by organizations, governments, or universities	– Text analysis software or languages (Leximancer, Voyant, R) – Data cleaning tools (Excel, OpenRefine) – Statistical analysis software or languages  (SPSS, Stata, PSPP, Python, R) – Visualization programs (ArcGIS StoryMaps, Tableau, Gephi)   Mapping (ArcGIS)	IRBs differ in whether they require approval for social media data or for re-use of secondary data. It’s a good idea to check with them as soon as you’re able.  Large volumes of data may require computer hardware of sufficient power and/or time to complete analyses.  Data produced on proprietary networks or provided by a software vendor may require purchase or licensing.
Field, ethnographic, or observation notes	– Video or audio recording hardware  – Your favorite writing implements (digital or otherwise)	– Qualitative data analysis software (QDAS) (NVivo, Atlas.ti, MAXQDA, Taguette, QualCoder)  – Printed data and tools for marking up and cutting apart data.	Researchers’ notes may not be considered formal data in all projects but care must still be taken to protect the privacy of any participants.