Guides, Help and FAQs

TLCMap is funded by a 1 year grant for rapid development to make it easier for humanities researchers to work with digital maps. This involves making existing functionality that is difficult or requires software developers easier as well as developing new functionality. Two key areas identified at the outset were 'time' (to view change over time, in various ways, not limited to timelines) and 'layers' (or 'deep maps'). To help us provide what is most useful, please contribute to our survey.

This presents some challenges, such as how to find commonality among diverse and changing needs to obtain the most benefit for most people while still allowing for those idiosyncrasies which are so often essential to humanities, without trying to create a 'one stop shop' that 'reinvents the wheel' or tries to be all things to all people and fails to do anything well. We aim also to find the balance between infrastructure that is a 'solution looking for a problem' and projects that produce software that is not re-usable because it was designed only to get a research outcome for a paper. In research we often don't know what we will find as we go and so adhering to a strict set of agreements and specifications from the outset, as is common in IT generally and in the commercial world, is not helpful.

The approaches we have adopted to deal with these complex problems are:

  1. Identify 6 broad themes which digital mapping in humanities activity generally focuses on. These are not mutually exclusive but help make sense of an otherwise confusing mass of projects and software.
  2. To develop with existing systems and standards that do what they do well.
  3. Identify gaps in functionality and develop in those areas.
  4. Identify gaps in functionality and develop enhancements to existing systems.
  5. Ensure all these systems work together with interoperability standards, and TLCMap conventions, such that information created in one can be exported and imported to another. This ensures a coherent, holistic infrastructure or software ecosystem that meets different needs, rather than a set of disparate research and development projects.
  6. Ensure no 'infrastructure' (software, data format, etc) is developed without a project to demonstrate usefulness, and no project is undertaken unless it produces 'infrastructure' in the form of re-usable and compliant software.
  7. A rapid prototyping development style allows for changes in priority, while still ensuring we produce working software and useful outcomes.

This means there isn't a single 'TLCMap' to log in to. Rather we hope to direct you to what you need. You can access through the 'themes', or these FAQs. In some cases, because we don't want to duplicate existing functionality these will simply direct you to good solutions, sometimes involving TLCMap software and projects. As development occurs over 2019 and 2020 the FAQs, systems and solutions will be added to as we go.

Digital Mapping In Humanities Tutorial

Self paced Intro to Digital Mapping for Humanities

FAQs

We aim to answer all the following questions over 2019-2020. In some cases we know there are answers but haven't yet documented them, or we need to do more research. In some cases we will simply give direction to easy solutions that already exist, while in others we will develop solutions. Questions we have not yet documented solutions for are greyed out.

General

There's a few places you could start digital mapping. Whatever you use, make sure if you put any work into using a system, you can get that work out again, such as by saving or downloading the data in a standard format, such as CSV, KML, KMZ, GeoJSON or other standard spatiotemporal file formats. These are essential file formats for moving data from one system to another in order to access the different capabilities of those systems, and in order to deposit research data in archives.

Google My Maps

Google My Maps is a great place to start. In a matter of minutes you can get a web map going, and in so doing learn a few basics about web mapping. Do tutorials or look at the documentation, or better still, just log in and start playing. With Google My Maps you can add points, lines and shapes to a map and add information to them. You can import data, and you can export your map as a KML file. You can also embed the map in a web page.

Google Earth

Google Earth is a desktop application, so its main drawback is that you cannot share your work so easily on the web, unless you export a KML file and add that to a web mapping system. Nonetheless it is a very powerful tool for doing your map related research. It enables putting points, lines and shapes on a map, with information about them, with other features such as 3D visualisations, and a time slider if your data has time associated with it. Whatever other system you use it's always handy to have Google Earth to open and manipulate KML files and to easily use 3D visualisations.

Quickly putting a few points on a map might be all you need, and even a simple map can have a powerful impact and make a point clear for teaching or research. If not, by trying to build your map in Google My Maps you will quickly learn its limitations and so get a clear idea of what you want to do. You may quickly run into the limitations of systems like Google My Maps and want to do more or different things, but there is a bewildering array of different software systems available, each for different purposes - how can you choose?

TLCMap Themes

We have found most digital mapping in humanities focuses on one of 6 themes (on our home page). These are not mutually exclusive and many overlap, but they are a convenient way to make sense of the vast amount of information about mapping software. These themes also provide access to systems we are developing that cater specifically to humanities needs - either making common tasks quicker and easier, or developing new functionality.

Tinker Geospatial Tool

Tinker provides a question and answer tool to help you find the right digital mapping software for the needs of your digital mapping project.

Digital Mapping In Humanities Tutorial

Self paced Intro to Digital Mapping

The TLCMap projects provide examples using TLCMap systems.

Anterotesis provides a long list of geohumanities projects generally: http://anterotesis.com/wordpress/mapping-resources/dh-gis-projects/

Digital Mapping is always one of the main streams at the international Digital Humanities conference, so you can have a look through the abstracts: DH2019

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

The proposed ‘Time Layered Cultural Map (TLC Map)’ is intended to be infrastructure. An apt definition of infrastructure is “Infrastructure can be described as that which creates the conditions of possibility for certain kinds of activities.”1 TLC Map will provide and improve the conditions of possibility for digital mapping in the humanities.

This includes basic mapping functionality with modifications for humanities researchers, a suite of re-usable tools and features, with ongoing development, driven by the needs of humanities research projects. Features relating to time will be a crucial factor for humanities enabling us to study and illustrate patterns across time as well as space.

There are some fundamental institutional problems that we can’t solve with a 1 year grant. We none the less need to acknowledge these problems and find tactical solutions to the make the best use of this rare opportunity and maximise the benefit of public money.

In short, yes, one way or another, but as with any system, make sure you export and back up your information, and deposit research data in an official repository.

An adequate longevity plan is difficult in the absence of institutional support or commitment to post project maintenance for eResearch generally, including digital humanities, even though this would be a small cost to protect thousands or millions of dollars in investment. This absence appears to be the across the tertiary research sector. There are legitimate concerns that new systems won't last long or that effort put in and data might be lost. We address these concerns in a variety of ways, and recommend actions you can take to be confident your research and work survives any eventuality. Ideally more funding would be available through further grants, partnerships and institutional support but we know this might not happen, so we have the following strategies to ensure work remains whether 'TLCMap' continues to exist or not:

Data

Sometimes in humanities we much prefer long form writing and avoid 'data', or may be interested in the possibilities of IT and data but without any background in that area don't know where to start. This Guide to Structured Data is for absolute beginners.

CSV files aren't specifically for spatiotemporal data, but because they are a widespread format for spreadsheets that are easy to read across many different systems, they are often used for also used for spatiotemporal data. A CSV file may be created by saving an Excel file as filetype 'csv'. 'CSV' stands for 'comma separated value'.

KML is a standard goecoding XML format. This means it can be processed by a computer easily, and can also, to some extent, be read and modified by a human. Because KML is a standard format for geodata, it can usually be imported into other systems. One of our main aims is not to try to build one system that does all things, but to allow for and further the parallel development of different systems independently. Interoperability, then, is key. How this works in practice is often by making data produced in one system available to another in a standard format. Sometimes this is as simple exporting a KML file from one system and importing it into another. Another common format for geodata is GeoJSON. A good tip is to make sure you can get the effort you put into your system out of it again in some standard format.

GeoJSON is another standard for spatial data, but written in JSON, which is a popular way of structuring data for the web.

All of these data formats are stored as plain text, so they can be read and edited by a computer or human.

How to create KML files:

How to create GeoJSON files:

How to create GeoJSON files:

Convert a CSV file to KML or GeoJSON

Often we have data in a spreadsheet, or that may be exported from a database in tabular form as a CSV file, that has columns for latitude and longitude.

An Excel spreadsheet can be 'saved as' in .csv format.

You can convert CSV to KML by importing it into Google MyMaps or Google Earth.

Alternatively you can find converters on the web by Googling 'convert CSV to KML' or similar, such as CSV to KML or MyGeoData Converter

Although not all data should be open for ethical reasons, TLCMap advocates Open Data and Creative Commons licensing.

Depositing data in a repository can help researchers and other find it. Some repositories are indexed by major search engines.

Based on advice from Alexis Tindall (ARDC):

Depositing Data In More Than One Location

Based on advice from Tom Honeyman (ARDC)

Having materials deposited in more than one archive/repository can be a good thing for ensuring the preservation of materials. The best way to resolve this is to talk to both repositories/archives about their requirements, and to let them know the datasets will be mirrored. They should be able to advise what they prefer in this scenario. The institutional repository is quite likely to say go with the other one.

If duplicating datasets, the data and the metadata captured against them (including identifiers) should be identical. In practice though, requirements for metadata and the form of the datasets may differ between the two.

Humanities researchers often need to deal with information that is in some way vague or uncertain. For example, we may want to map a diary entry which says, '3 days north of the bend in the river' or 'late Spring' but these need to be translated into specific coordinates and times in order to be placed on a map. Simply placing information on the map may give viewers the false impression that it is accurate or certain. This can have major implications if people use the information in an an appeal to authority (eg: the University says it was here at this time) to prove some case, potentially with legal implications. In other situations, users may misinterpret mapped information as complete such that gaps on the map seem to indicate nothing there, rather than no research done or data gathered there yet. In any case a common requirement requested by humanities researchers is the ability to represent vagueness in some way.

This involves many questions that could be handled with different data structures:

All of these need to be considered and balanced against each other and the needs depend on the circumstances. Often simple answers are the best, and practicality dictates we don't want to overcomplicate data entry, we don't have time and money for extra detail, we need to work within/around and adapt established formats rather than create new systems, and we want users not to have to read manuals to interpret visualisations. At a base level, we could:

None the less there is some research investigating nuances of representation of vagueness, eg:

There are several metadata standards for spatial information, sometimes overlapping and sometimes with more or less than seems needed. We will aim to ensure that any metadata standard used can at least be transformed into another common standard.

AURIN has already done work to establish this guide: https://aurin.org.au/legal/metadata-record-guide/ including a metadata tool based on an extended version of ISO 19115, which was used in the creation of the AS/NZS version ). AURIN’s original metadata standard work was funded under demonstrator projects with ANDS https://projects.ands.org.au/id/AP31

Dublin Core is also a good, well established standard to follow for set of basic metadata https://dublincore.org/

There may be any number of reasons. Here's a few common problems:

Coordinates are back to front. Coordinates often appear as a pair, like this: -32.914154, 151.800702. Some systems assume latitude first and longitude second, while others expect the coordinates to be the other way around. Even within Google mapping systems they are expected in one way, and in other Google system another way.

Coordinates are in an unexpected format. Coordinates can be expressed in different ways: as decimal numbers, as degrees, minutes, seconds and so on. Check your data is in the correct format. If not, convert it using a conversion tool.

An invalid character or other glitch may be the problem. Computers are temperamental and very literal. Sometimes a whole system might not work because of a full stop in the wrong place. A single letter in a coordinate field that is assumed to be a number might make some systems fail. The only way to deal with this is to hunt down the problem and correct it.

To find and fix problems, try working with just a very small example of your data. If it doesn't work, it will be easy to find issues and try different approaches. If the problem doesn't occur, you can keep adding chunks of your data till you narrow down where the problem might be occuring.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

Time

There are many ways we think and talk about time. We aim to make available ways to structure temporal information and visualise it for different circumstances such as:

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on. (canoe time)

To be researched and documented. This may be an area we can improve on.

Processing and Metrics

We are improving on features in Recogito which uses Named Entity Recognition (NER) to automatically identify places and people in texts and produce maps of the places, see: Recogito

See 'How can I get statistics and metrics on spatiotemporal data?'

To be researched and documented. This may be an area we can improve on.

'Close' compared to what? Handling statistics on elipsoid surfaces, and with time too.

To be researched and documented. This may be an area we can improve on. (least cost techniques etc)

Images, Virtuality and Visualisation

The following provide georeferencing tools that are free to some extent:

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on. HuNI, M2M.

To be researched and documented. Omeka, WordPress, ArcGIS Storymaps, Google MyMaps, etc etc.

You can find tutorials on the web explaining how to do this. Here's a few examples. We haven't yet checked the effectiveness of any of these, so find one that suits your style and give it a go.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

To be researched and documented. This may be an area we can improve on.

  1. Brown, Susan; Clement, Tanya; Mandell, Laura; Verhoeven, Deb; Wernimont, Jacque Creating Feminist Infrastructure in the Digital Humanities DH2016 2016-03-06 http://dh2016.adho.org/static/data-copy/531.html