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Digital Data Management - Archaeology Module

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[Slide 1]

Bringing Digital Data Management Training into Methods Courses for Anthropology

Archaeology:Principles and Practices of Digital Data Management

Lindsay Lloyd-Smith

2016

[Slide 2]

Recommended citation:

Lloyd-Smith, Lindsay. “Archaeology: Principles and Practices of Digital Data Management.” In Bringing Digital Data Management Training into Methods Courses for Anthropology, edited by Blenda Femenías. Arlington, VA: American Anthropological Association, 2016.

http://www.americananthro.org/methods

© American Anthropological Association 2016

This work is licensed under Creative Commons Attribution-NonCommercial 4.0 International License.

Bringing Digital Data Management Training into Methods Courses for Anthropology is a set of five modules:

General Principles and Practices of Digital Data Management
Archaeology: Principles and Practices of Digital Data Management
Biological Anthropology: Principles and Practices of Digital Data Management
Cultural Anthropology: Principles and Practices of Digital Data Management
Linguistic Anthropology: Principles and Practices of Digital Data Management

Project support: National Science Foundation, Workshop Grant 1529315; Jeffrey Mantz, Program Director, Cultural Anthropology

 

[Slide 3]

Organization

  1. Review of material from “General principles and practices” module
  2. Managing digital research data in a graduate project
  3. Research data and ethical codes of conduct
  4. Digital data in archaeology
  5. Why digitize physical data?
  6. Why deposit digital data?
  7. Data lifecycles and management plans
  8. Exercises
  9. Instructor notes
  10. References
  11. Acknowledgments
 

[Slide 4]

Review of material from “General principles and practices” module

What are data?

[Slide 5]

Managing digital research data in a graduate project

Why learn data management?

 

[Slide 6]

Research data and ethical codes of conduct

 

[Slide 7]

Research data and ethical codes of conduct

Archaeological Institute of America,
Code of Professional Standards

3. Archaeologists should anticipate and provide for adequate and accessible long-term storage and curatorial facilities for all archaeological materials, records, and archives, including machine-readable data, which require specialized archival care and maintenance.

4. Archaeologists should make public the results of their research in a timely fashion, making evidence available to others if publication is not accomplished within a reasonable time.

5. All research projects should contain specific plans for conservation, preservation, and publication from the very outset, and funds should be secured for such purposes.

https://www.archaeological.org/news/advocacy/132

 

[Slide 8]

Research data and ethical codes of conduct

Society for American Archaeology,
Principles of Archaeological Ethics

Principle No. 7: Records and Preservation:

Archaeologists should work actively for the preservation of, and long term access to, archaeological collections, records, and reports. To this end, they should encourage colleagues, students, and others to make responsible use of collections, records, and reports in their research as one means of preserving the in situ archaeological record, and of increasing the care and attention given to that portion of the archaeological record which has been removed and incorporated into archaeological collections, records, and reports.

http://www.saa.org/AbouttheSociety/PrinciplesofArchaeologicalEthics/tabid/203/Default.aspx

 

[Slide 9]

Digital data in archaeology
Data types

 

[Slide 10]

Digital data in archaeology
Data types

Data: “A reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing.” Digital Curation Centre (http://www.dcc.ac.uk/)

Digital data are everything created or manipulated on a computer:

[In-class exercise: Discuss data types]

 

[Slide 11]

Digital data in archaeology
Issues and risks with digital data

Ethical and legal issues include:

Practical issues

Photograph by L. Lloyd-Smith

 

[Slide 12]

Why digitize physical data?

Archaeologists study material remains, so why should they digitize physical data?

 

Hand-drawn field data needs digitising.
Photograph by L. Lloyd-Smith

 

[Slide 13]

Why deposit digital data?

“The single best thing people can do to improve their data management is to plan for the re-use of the data in the future.”
The Archaeology Data Service, http://archaeologydataservice.ac.uk/

 
 

Archives des députés allemands.
Photograph by Hamadryades. www.flickr.com/photos/hamadryades/2549161782/

 

[Slide 14]

Why deposit digital data?

Reasons and benefits for depositing digital data properly: Ask yourself, who will be interested in re-using archived data in the future?

 

[Slide 15]

What to do with my research data?
“I’ll deal with sorting out my data when I retire….”

 

[Slide 16]

What to do with my research data?
Rolling data management plans for on-going research

 

[Slide 17]

Data lifecycles and management plans
Data management is not about being an IT geek!

 

[Slide 18]

Data lifecycles and management plans

 

[Slide 19]

In-class exercise: Discussing data

Is your research:

How will these factors affect your data management?

What types of archaeological data will you collect, create, and analyse?

 

[Slide 20]

In-class exercise: Discussing data

Accompanied by Handout A, Discussing Your Digital Data

Spend 10–15 minutes writing answers to the questions below and on the handout. Discuss your answers with other students.

  1. Are you working on your own or as part of a group?
  2. Who is funding the work?
  3. Is the work with a Native American or Indigenous Community?
  4. Is the work part of community or public archaeology project?
  5. What data can or will be archived?
  6. Do you have authority to deposit these data?
  7. To archive the data, what steps will you need to carry out?
 

[Slide 21]

In-class exercise: Handout A

Discussing your Digital Data

  • When considering the Data Management questions below, it is important to bear in mind the following:
  • What are the key research questions of the project?
  • Where (physically) are the data under study (museum, library, laboratory, archaeological site, published materials, etc.)?

Data Management Questions:

Data Types

Existing Data:
Published or Archival

Who ‘owns’ the data?

What types of existing physical data are you planning to analyse?

     

What types of physical data are you planning to create?

     

What types of existing digital data are you planning to use?

     

What types of digital data will you create?

     
   

Where might the digital data created through your project be deposited?

 

What potential ethical issues are there concerning data creation, management, archiving, and future re-use?

 

What legal issues are there concerning data creation, management, archiving, and future re-use?

 

Can you think of any other data management issues concerning this project?

 
 

[Slide 22]

Outside-class exercise: Creating a graduate data management plan

Key questions to bear in mind:

 

[Slide 23]

Outside-class exercise: Creating a graduate data management plan

Accompanied by Handouts B and C

A good way to start drafting a plan for looking after your own research data is to think of the plan in reverse order:

By working towards this goal from the outset you will organise your data with this in mind as you progress with your work.

Building upon what you jotted down in the class discussion, the questions in this second short exercise lead you in reverse order into drafting your data management plan.

Spend 20-30 minutes writing a short paragraph in answer to each of these questions:

Talk with your academic supervisor / tutor about where and how best archive the digital data from your project. The sooner you do this, the better!

 

[Slide 24]

Outside-class exercise: Handout B-1

Graduate projects: File structure and naming

Researcher:

Project Title:

Project Duration:

Project Context:

1. File Structure
[When completing this form on a computer please delete this and write as much as you need to in each of the sections – do not worry about keeping the form to a single page]

2. File Naming

Signed:

Version:

Date Created:

Date Amended:

 

[Slide 25]

Outside-class exercise: Handout B-2
Graduate projects: File structure and naming prompt sheet

Researcher: Name

Project Title: Provisional dissertation or thesis title

Project Duration: Dates of graduate project

Project Context:
Where is the research being carried out, and what is under study?
Is the research individually based, part of a larger project, or being carried out in agreement with a group(s) or institution(s), e.g., Native American, First Nation or indigenous community(s), Cultural Resource Management company, a museum(s), a state/regional authority, or other community group(s)?

1. File Structure
Describe the organisation of computer folders for your post-graduate research project.
Does the file structure follow conventions from a host project, laboratory or institution?
List the primary folders, and then summarise the organisation of their sub-folders.
How will the computer folders for your graduate research be distinguished from other research projects and work that you might be involved with?

Good Practice
Use a system that is logical to you, but simple and self-explanatory to others.
Avoid using the same name for sub-folders as this may lead to the over-writing of their contents.
Avoid the over-use of folders.

2. File Naming
Describe the logic behind the file naming system for your graduate research.
Does the file naming follow conventions from a host project, laboratory or institution?
Give examples of the file names, from different types of digital data used in your research.
How will the file names in your post-graduate research be distinguished from files in other research projects and work that you might be involved with?
If a coding or numbering system is used to name files, where will the explanation of this system be saved?

Good Practice
Use underscores instead of spaces.
If the date is included, write this in numbers: year-month-date, e.g., 2011-01-10.
If numbering files, consider how many files are potentially needed: 001, 002, will order files up to 999.
DO NOT WRITE ENTIRE FILE NAME IN CAPITALS AS THIS IS HARD TO READ.

Signed:

Version:

Date Created:

Date Amended:

 

[Slide 26]

Outside-class exercise: Handout C-1 Data management plan for graduate research projects When filling in on a computer, the whole form should be 2 pages maximum

Researcher:

Project Title:

Project Duration:

Project Context:

1. What Data will be Produced?

2. How will the Data be Documented and Described?

3. Has a ‘File Structure/Naming Form’ been completed? (see separate form)

Date Created:

Date Amended:

Version no.

4. Deposition of Digital Copy of Dissertation / Thesis: delete as appropriate,
A. Intend to deposit an e-thesis with …[fill in]…with open access.
B. Intend to deposit an e-thesis with …[fill in]… with a time-limited embargo on open access.
C. Do not intend to deposit an e-thesis.

Give Reasons:

5. What are the plans for data sharing and access after submission of the thesis?

6. What are the plans for long-term archiving of the digital data supporting the thesis?

Signed:

Version:

Date Created:

Date Amended:

 

[Slide 27]

Outside-class exercise: Handout C-2 Data management plan for graduate research projects: Prompt sheet

Researcher: Name

Project Title: Provisional dissertation / thesis title

Project Duration: Dates of graduate project

Project Context:
Where is the research being carried out, and what is under study?
Is the research individually based, part of a larger project, or being carried out in agreement with a group(s) or institution(s), e.g. Native American, First Nation or indigenous community(s), Cultural Resource Management company, a museum(s), a state/regional authority, or other community group(s), etc.?

1. What Data will be Produced?
What physical data will you study? And what digital data will be captured/derived from these? (field notes, images, measurements, spreadsheets, survey data, etc.).
What data will be ‘created’ digitally (images, some analytical and survey data, etc.)?
Describe the methods/standards for data creation?
What file formats and software will you use?
Consider how many individual files you expect to make, anticipated file sizes, and total storage volume.

2. How will the Data be Documented and Described?
Think about what contextual information is required to make the data understandable to others:
What standards will be used to record the data?
What information on the data collection methods, standards, and context (‘metadata’) will be recorded for each data type/set?
Where will the metadata for each data type/set be located? (e.g. within the data file and/or as separate metadata text document, and/or in method chapter/appendices in the thesis)

3. Has a ‘File Structure/Naming Form’ been completed? (see separate form)

Date Created:

Date Amended:

Version no.

4. Deposition of E-Thesis: delete as appropriate and state reasons:
A. Intend to deposit e-thesis with …[fill in]…with open access.
B. Intend to deposit e-thesis with …[fill in]… with a time-limited embargo on open access.
C. Do not intend to deposit e-thesis.
Give Reasons:
Intended publication of articles or book after submitting thesis (three years is the standard length of an embargo)
Agreement with sponsoring body, community group, or institution to embargo e-thesis.
NB. If you intend to deposit your thesis with a digital repository agreement must be sought with all concerned third-parties (museums etc), particularly for use of any copyright material.

5. What are the plans for data sharing and access after submission of the thesis?
Who, if any, are the anticipated future users of any digital data / resources from the research?
Will any of the digital data supporting the thesis (e.g. organised project archive folders with images, drawings, spreadsheets, databases, etc) be made available to others on request or open access?
(e.g. to the host project, research lab/community, museums, or open-access web-based organisation)
Are there any ethical issues (e.g. personal data, site locations) that need to be taken into account? If so, what actions will safe guard these data?
Are there any funding body / institutional requirements regarding re-use of, or open-access to, data?

6. What are the plans for long-term archiving of data supporting the thesis?
Where will the digital data be archived?
What arrangements are there to archive the digital data with a laboratory or institution?
Will a copy of the digital data be archived with the physical data (in a laboratory / institution)?
If no institutional archiving is possible, how will the data be safe guarded by the individual? (e.g. personal computer, external hard drive, future use of institutional server back-up during employment)

Signed:

Version:

Date Created:

Date Amended:

 

[Slide 28]

Instructor notes: Managing digital research data in a graduate project (Slide 5)

Good data underpins high quality research, supporting credible and—importantly—verifiable interpretations. To be able to go back and check other researchers’ interpretations in the future, take work further and re-use old data, the long-term preservation of data—and increasingly this means digital data—is of central importance.

The production of well managed and accessible data sets can help an anthropologist scholar gain academic and professional recognition.

The importance of looking after research data is recognised by major funding bodies, and one of the conditions of receiving grants is the provision for good practice in data management, preservation, and archiving.

Producing well managed data also aids with one immediate concern of graduate students: to finish a project on time.

 

[Slide 29]

Instructor notes: Issues and risks with digital data (Slide 11)

Two main concerns with digital data are:

Ethical and legal issues

Practical issues

The last issue brings us back to the beginning: what we decide to keep and archive must be understandable to others in the future. Not only must we record how the data were created, but we must also document why the data were produced and what information they contain. For example, when were digital photographs taken, why they were taken, and what do they show?

 

[Slide 30]

Instructor notes: Why digitize physical data? (Slide 12)

Archaeology deals with a vast range of physical data. In addition, many archaeologists still work, at least in part, with traditional paper records: hand-written field notes and record sheets, hand-drawn field drawings and artefact illustrations. The paper archive is still in many peoples’ eyes the primary archive, and provision has to be made for the location where these physical data, along with artefacts, animal bones, soil samples, and other materials, will be archived.

Digitisation of field documentation should be a routine procedure. Like everything that is tedious and routine it really helps to get this out of the way as soon as possible after the production of the paper material. Ideally one should input field data into a computer during field work. If it cannot be done until after fieldwork is completed, make a full digital copy of your physical documentation as soon as you can.

Reasons for digitizing the paper archive: it helps you tidy up your field notes; enables analysis providing searchable spreadsheets and databases; and makes data portable, easy to share, and easy to re-use in the future. As part of data analysis, interpretation, and presentation, we digitize most, if not all, of the paper documentation. All publication preparation is digital.

The digital archive provides a back-up of the paper archive. However, the original material should not be discarded. In terms of volume of shelf space, field notebooks, drawings, and photographs do not pose a serious threat to storage space.

 

[Slide 31]

Instructor notes: What to do with my research data? (Slides 15, 16)

Unfortunately, researchers commonly believe that they will “deal with sorting out my data when I retire…,” at the end of a life time of on-going work:

Research data starts accumulating on a hard-drives from the beginning, if not prior to, graduate projects. Hopefully we get a job, or even if not, we might continue to do research independently and our hard-drives get fuller and fuller. The rate of data accumulation increases as we work on more and more projects at the same time.

Before we know it we’re about to retire and we’ve a mountain of old research data to worry about. And this is the good story.

The nightmare scenario is when a researcher passes away unexpectedly and takes with them a lot of the background information with which to make sense of their undocumented data.

 

[Slide 32]

Instructor notes: Data lifecycles and management plans (Slides 17, 18)

See also Outside-class exercise, and accompanying Handout B.

A data lifecycle model divides the research process into a number of tasks: project planning; data collection; data analysis; data distribution and archiving; data discovery and re-use; leading to data re-analysis, and so on and so forth. Thinking of data in terms of a life cycle helps to:

And what documentation we will need to provide so that the data are re-usable in the future.

And all a Data Management Plan is, is a project document that works through each of these stages around the lifecycle and answers each of these questions:

At this point some data may be re-cycled, re-analysed, and feed back into the management process. Or, new data may be required. The remaining parts of the management plan address the questions:

A possible analogy to a Data Management Plan is a Risk Assessment Form, completed before we carry out any fieldwork, in which we think through all the possible things that could go wrong, the procedures in place to mitigate the risks, and finally the actions that will be taken if something does go wrong. In a similar way the purpose of a Data Management Plan is to think through and explicitly define the data that will be created, how it will be looked after, and what data will end up where.

 

[Slide 33]

References

Clarke, Mary E. “The Digital Dilemma: Preservation and the Digital Archaeological Record.” Advances in Archaeological Practice 3 (2015): 313-30. DOI: 10.7183/2326-3768.3.4.313

Pryor, Graham. “Librarians doing data—a paradox?” Paper presented at the conference, Libraries@Cambridge, Cambridge, England, 6 January 2011. http://www.dcc.ac.uk/webfm_send/319

Sheehan, Beth. “Comparing Digital Archaeological Repositories: tDAR Versus Open Context.” Behavioral and Social Sciences Librarian 34 (2015): 173-213. DOI:10.1080/01639269.2015.1096155

Web resources

The Archaeology Data Service (UK): http://archaeologydataservice.ac.uk/

DataTrain. Open Access Post-Graduate Teaching Materials in Managing Research Data in Archaeology. http://archaeologydataservice.ac.uk/learning/DataTrain

The Digital Archaeological Record (tDAR). A service of Digital Antiquity. http://www.tdar.org/about/

Digital Curation Centre, United Kingdom. http://www.dcc.ac.uk/

National Science Foundation. Arch-DDRI, Archaeology, Doctoral Dissertation Research Improvement Awards. http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505076&org=BCS&from=home

National Science Foundation. Archaeology and Archaeometry Program.
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=11690&org=BCS&from=home

 

[Slide 34]

American Anthropological Association

Advancing Knowledge, Solving Human Problems

Acknowledgments

Modules: Writers, Arienne M. Dwyer, Blenda Femenías, Lindsay Lloyd-Smith, Kathryn Oths, George H. Perry; Editor, Blenda Femenías

Discussants:
Workshop One, February 12, 2016: Andrew Asher, Candace Greene, Lori Jahnke, Jared Lyle, Stephanie Simms
Workshop Two, May 13, 2016: Phillip Cash Cash, Jenny Cashman, Ricardo B. Contreras, Sara Gonzalez, Candace Greene, Christine Mallinson, Ricky Punzalan, Thurka Sangaramoorthy, Darlene Smucny, Natalie Underberg-Goode, Fatimah Williams Castro, Amber Wutich

American Anthropological Association:
Executive Director, Edward Liebow
Project Manager, Blenda Femenías
Research Assistant, Brittany Mistretta
Executive Assistant, Dexter Allen
Professional Fellow, Daniel Ginsberg
Web Services Administrator, Vernon Horn
Director, Publishing, Janine Chiappa McKenna



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