17.7 Documents and other artifacts
Learning Objectives
Learners will be able to…
- Identify key considerations when planning to analyze documents and other artifacts as a strategy for qualitative data gathering, including preparations, tools, and skills to support it
- Assess whether analyzing documents and other artifacts is an effective approach to gather data for your qualitative research proposal
Qualitative researchers may also elect to utilize existing documents (e.g. reports, newspapers, blogs, minutes) or other artifacts (e.g. photos, videos, performances, works of art) as sources of data. Artifact analysis can provide important information on a specific topic, for instance, how same-sex couples are portrayed in the media. They also may provide contextual information regarding the values and popular sentiments of a given time and/or place. When choosing to utilize documents and other artifacts as a source of data for your project, remember that you are approaching these as a researcher, not just as a consumer of media. You need to thoughtfully plan what artifacts you will include, with a clear justification for their selection that is solidly linked to your research question, as well as a plan for systematically approaching these artifacts to identify and obtain relevant information from them.
Obtaining your artifacts
As you begin considering what artifacts you will be using for your research study, there are two points to consider: what will help you to answer your research question and what can you gain access to. In addressing the first of these considerations, you may already have a good idea about what artifacts are needed because you have done a substantial amount of preliminary work and you know this area well. However, if you are unsure, or you need to supplement your existing knowledge, some general sources can include: librarians, historians, community experts, topical experts, organizations or agencies that address the issue or serve the population you will be studying, and other researchers who study this area. In considering access, if the artifacts are public the answer may be a straightforward yes, but if the documents are privately held, you may need to be granted permission – and remember, this is permission to use them for research purposes, not just to view them. When obtaining permission, get something in writing, so that you have this handy to submit with your IRB application. While the types of artifacts you might include are almost endless (given they are relevant to your research question), Table 18.4 offers a list of some ideas for different sources you might consider.
| Newspapers | Films | Meeting Minutes |
| Organizational Charts | Autobiographies | Blogs |
| Web Pages | Text Message Discussions | Pieces of Art |
| Objects in a Special Collection of a Museum | Pamphlets | Dance Recitals |
| Speeches | Historical Records | Letters |
Artifact analysis skills
Consistent with other areas of research, but perhaps especially salient to the use of artifacts, you will require organizational skills. Depending on what sources you choose to include, you may literally have volumes of data. Furthermore, you might not just be dealing with a large amount of data, but also a variety of types of data. Regardless of whether you are using physical or virtual data, you need to have a way to label and catalog (or file) each artifact so that you can easily track it down. As you collect specific information from each piece, make sure it is tagged with the appropriate label so that you can track it back down, as you very well may need to reference it later. This is also very important for honest and transparency in your work as a qualitative researcher – documenting a way to trace your findings back to the raw data.
In addition to staying organized, you also need to think specifically about what you are looking for in the artifacts. This might seem silly, but depending on the amount of data you are dealing with and how broad your research topic is, it might be hard to ‘separate the wheat from the chaff’ and figure out what is important or relevant information. Sometimes this is more clearly defined and we have a prescribed list of things we are looking for. This prescribed list may come from existing literature on the topic. This prescribed list may be based on peer-reviewed literature that is more conceptual, meaning that it focuses on defining concepts, putting together propositions, formulating early stage theories, and laying out professional wisdom, rather than reporting research findings. Drawing on this literature, we can then examine our data to see if there is evidence of these ideas and what this evidence tells us about these concepts. If this is the case, make sure you document this list somewhere, and on this list define each item and provide a code that you can attach when you see it in each document. This document then becomes your codebook.
However, if you aren’t clear ahead of time what this list might be, you may take an emergent approach, meaning that you have some general ideas of what you are seeking. In this event, you will actively create a codebook as you go, like the one described above, as you encounter these ideas in your artifacts. This helps you to gain a better understanding of what items should be included in your list, rather than coming in with preconceived notions about what they should be. There will be more about tracking this in our next chapter on qualitative analysis. Whether you have a prescribed list or use a more emergent design to develop your codebook, you will likely make modifications or corrections to it along the way as your knowledge evolves. When you make these changes, it is very important to have a way to document what changes you made, when, and why. Again, this helps to keep you honest, organized, and transparent. Just as another reminder, if you are using predetermined codes that you are looking for, this is reflective of a more deductive approach, whereas seeking emergent codes is more inductive.
Finally, when using artifacts, you may also need to bring in some creative, out-of-the-box thinking. You may be bringing together many different pieces of data that look and sound nothing alike, yet you are seeking information from them that will allow you tell a cohesive story. You may need to be fluid or flexible in how you are looking at things, and potentially challenge your preconceived notions.
Capturing the data
As alluded to above, you may have physical artifacts that you are dealing with, digital artifacts or representations of these artifacts (e.g. videos, photos, recordings), or even field notes about artifacts (for instance, if you take notes of a dramatic performance that can’t be recorded). A large part of what may drive your decisions about how to capture your data may be related to your level of access to those artifacts: can you look at it? Can you touch it, can you take it home with you, can you take a picture of it? Depending on what artifacts we are talking about, some of these may be important questions. Regardless of the answers to these questions, you will need to have a clearly articulated and well-documented plan for how you are obtaining the data and how you will reference it in the future.
Exercises
What types of artifacts might you have access to that might help to answer your research question(s)?
Tips
- These could be artifacts available at your field placement, publicly available media, through school, or through public institutions
- These can be documents or they can be audiovisual materials
- Think outside the box, how can you gather direct or indirect indications of the thing you are studying
Generate a list of at least 3
- _
- _
- _
Again, drawing on Creswell’s (2013) suggestion of capturing ‘descriptive’ and ‘reflective’ aspects in your field notes, Table 18.5 offers some more detailed description of what to include as your capture your data and corresponding examples when focusing on an artifact.
| Areas to capture | Aspects to consider in each area | Example |
| Demographic Info | What details help to frame the logistics of the interaction
|
Date: 1/22/19
Artifact: Moved to Tears by Nieves Dominguez, Photo Exhibit Source: NY Arts for Action Studios Source Information: Studio is a non-profit that hosts artistic work and events that are intended to raise consciousness and produce change for groups experiencing inequality and oppression Nieves is a world-renown photographer who specializes in capturing the experience of immigrant journeys and is a vocal advocate for immigrant rights |
| Descriptive Aspects | What you observe externally
|
As you begin moving through the exhibit, you first encounter a number of photographs of people in tears. There are pictures of people crying alone, crying in groups, wailing, subdued, appearing joyous, appearing sorrowful…
The room is silent. Despite the hall being quite crowded, you can hear a pin drop. Based on proximity to each other, it generally seems that people are attending in small groups (3-6). A few single people appear to be viewing, as well. |
| Reflective Aspects | What you observe internally
|
I want to know more about the focal point of the photographs. While all of these initial photos contain someone in tears, they rarely seem to be the focus of the picture. I don’t know if this is meant to convey the often hidden sufferings and joys of these subjects or perhaps the many and varied forces that influence their lives. |
Resources to learn more about qualitative research with artifacts.
Bowen, G. A. (2009). Document analysis as a qualitative research method.
Rowsell, J. (2011). Carrying my family with me: Artifacts as emic perspectives.
Hammond, J., & McDermott, I. (n.d.). Policy document analysis.
Wang et al. (2017). Arts-based methods in socially engaged research practice: A classification framework.
A few exemplars of studies utilizing documents and other artifacts.
Casey, R. C. (2018). Hard time: A content analysis of incarcerated women’s personal accounts.
Green, K. R. (2018). Exploring the implications of shifting HIV prevention practice Ideologies on the Work of Community-Based Organizations: A Resource dependence perspective.
Sousa, P., & Almeida, J. L. (2016). Culturally sensitive social work: promoting cultural competence.
Secondary data analysis
I wanted to briefly provide some special attention to secondary data analysis at the end of this chapter. In the past two chapters we have focused our sights most often on what we would call raw data sources. However, you can of course conduct qualitative research with secondary data, which is data that was collected previously for another research project or other purpose; data is not originating from your research process. If you are fortunate enough to have access and permission to use qualitative data that had already been collected, you can pose a new research question that may be answered by analyzing this data. This saves you the time and energy from having to collect the data yourself!
You might procure this data because you know the researcher that collected the original data. For instance, as a student, perhaps there is a faculty member that allows you access to data they had previously collected for another project. Alternatively, maybe you locate a source of qualitative data that is publicly available. Examples of this might include interviews previously conducted with Holocaust survivors. Finally, you might register and join a research data repository. These are sites where contributing researchers can house data that other researchers can view and request permission to use. Syracuse University hosts a repository that is explicitly dedicated to qualitative data. While there are more of these emerging, it may be a challenge to find the specific data you are looking for in a repository. You should also anticipate that data from repositories will have all identifiable information removed. Sharing data you have collected with a repository is a good way to extend the potential usefulness and impact of data, but it also should be anticipated before you collect your data so that you can build it into any informed consent so participants are made aware of the possibility.
Computer Assisted Qualitative Data Analysis Software (CAQDAS)
Some qualitative researchers use software packages known as Computer Assisted Qualitative Data Analysis Software (CAQDAS) in their work. These are tools that can aid researchers in managing, organizing and manipulating/analyzing their data. Some of the more common tools include NVivo, Atlas.ti, and MAXQDA, which have licensing fees attached to them (although many have discounted student rates). However, there are also some free options available if you do some hunting. Taguette Project is the only free and open source CAQDAS project that is currently receiving updates, as previous projects like RQDA which built from the R library are not in active development. Taguette is a young project, and unlike the free alternatives for quantitative data analysis, it lacks the sophisticated analytical tools of commercial CAQDAS programs.
It is unlikely that you will be using a CAQDAS for a student project, mostly because of the additional time investment it will take to become familiar with the software and associated costs (if applicable). In fact the best way to avoid spending money on qualitative data analysis software is to do your analysis by hand or using word processing or spreadsheet software. If you continue on with other qualitative research projects, it may be worth some additional study to learn more about CAQDAS tools. If you do choose to use one of these products, it won’t magically do the analysis for you. You need to be clear about what you are using the software for and how it supports your analysis plan, which will be the focus of our next chapter.
Resources to learn more about CAQDAS.
Maher et al. (2018). Ensuring rigor in qualitative data analysis: A design research approach to coding combining NVivo with traditional material methods.
Woods et al. (2016). Advancing qualitative research using qualitative data analysis software (QDAS)? Reviewing potential versus practice in published studies using ATLAS. ti and NVivo, 1994–2013.
Zamawe, F. C. (2015). The implication of using NVivo software in qualitative data analysis: Evidence-based reflections.
As you continue to plan your research proposal, make sure to give practical thought to how you will go about collecting your qualitative data. Hopefully this chapter helped you to consider which methods are appropriate and what skills might be required to apply that particular method well. Revisit the table in section 18.3 that summarizes each of these approaches and some of the strengths and challenges associated with each of them. Collecting qualitative data can be a labor-intensive process, to be sure. However, I personally find it very rewarding. In its very forms, we are bearing witness to people’s stories and experiences.
Key Takeaways
- Artifact analysis can be particularly useful for qualitative research as a means of studying existing data; meaning we aren’t having to collect the data ourselves, but we do have to gather it. As a limitation, we don’t have any control over how the data was created, since we weren’t involved in it.
- There are many sources of existing data that we can consider for artifact analysis. Think of all the things around us that can help to tell some story! Artifact analysis may be especially appealing as a potential time saver for student researchers if you can gain permission to use existing artifacts or use artifacts that are publicly available.
- Artifact analysis still requires a systematic and premeditated approach to how you will go about extract information from your artifacts.
Exercises
Reflexive Journal Entry Prompt
Here are a few questions to get you thinking about the role that you play as you gather qualitative data.
- What are your initial thoughts about qualitative data collection?
- Which of these data collection strategies are you drawn to?
- Why might that be?
- What excites you about this process?
- What worries you about this process?
- What aspects of yourself will strengthen or enhance this process?
- What aspects of yourself may hinder or challenge this process?
Exercises
Decision Point: How will you go about qualitative data collection?
- What approach(es) will you use to collect your qualitative data?
- Justify your choice(s) here in relation to your research question and availability of resources at your disposal
- What steps will you need to put in place to ensure a high quality, systematic process for data collection?
- who will be collecting data
- what will be involved
- how will it be safely stored and organized
- how are you protecting human participants
- if you have a team, how is communication being established so everyone is “on the same page”
- how will you know you are done
- What additional information do you need to know to use this approach?
- Harris, M. and Fallot, R. (2001). Using trauma theory to design service systems. New Directions for Mental Health Services. Jossey Bass; Farragher, B. and Yanosy, S. (2005). Creating a trauma-sensitive culture in residential treatment. Therapeutic Communities, 26(1), 93-109. ↵
The analysis of documents (or other existing artifacts) as a source of data.
unprocessed data that researchers can analyze using quantitative and qualitative methods (e.g., responses to a survey or interview transcripts)
A code is a label that we place on segment of data that seems to represent the main idea of that segment.
A document that we use to keep track of and define the codes that we have identified (or are using) in our qualitative data analysis.
starts by reading existing theories, then testing hypotheses and revising or confirming the theory
when a researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences
analyzing data that has been collected by another person or research group
in a literature review, a source that describes primary data collected and analyzed by the author, rather than only reviewing what other researchers have found
Data someone else has collected that you have permission to use in your research.
These are sites where contributing researchers can house data that other researchers can view and request permission to use
These are software tools that can aid qualitative researchers in managing, organizing and manipulating/analyzing their data.