This is a field report of efforts to develop a plan for low cost, digital data collection. Here’s what I have tried, what worked well, what did not and how those limitations were addressed.
First a description of the conditions. We live in two locations in Ecuador. The first is the field center established and currently run by Maria Masucci, Drew University. It has many of the conveniences needed for digital data collection, such as reliable electricity, surge protectors, etc. It does not have internet nor a strong cellular data signal. We are largely here only on weekends. During the week, we reside in rather cramped conditions in rented space in a much more remote location, where amenities (digital and otherwise) are minimal. There is limited cellular data signal (if you stand on the water tower, which is in the center of town and the highest point even though it is only one story tall, you can get a weak cellular data signal; enough for texts and receiving emails, but not enough for internet use or sending emails) and there is no other access to internet. We also take minimal electronic equipment into the field for the week (e.g. my laptop does not travel). So, everything needs to be set up prior to arrival in the field. The idea, therefore, is to largely use minimal electronic equipment in the field; I tried to use only one device (while also experimenting with others) for this reason. My device of choice (or honestly by default) is my iPhone 5s.
The central component of this attempt at digital data collection is Kobo Toolbox (see my earlier posts for more details… here, here, here and here), an open-source and web-browser based form creation, deployment and collection tool. Kobo Toolbox’s primary benefit is that, because it is browser-based, it is platform independent. You can use an iPad or an iPhone just as well as an Android device or a Mac or PC computer. This means that data can be collected on devices that are already owned or that can be bought cheaply (e.g., a lower level Android device v. an iPad). The form is created through their online tools and can create fairly elaborate forms with skip logic and validation criteria. Once the form is deployed and you have an internet connection, the user loads the form into a browser on your device. You need to save the link so that it can be used without a data connection. On my iPhone 5s, I simply saved the link to the home screen. A couple of quick caveats are important here. I was able to load the form onto an iPhone 4s (but only using Chrome, not Safari), but was unable to save it, so lost it once the phone was offline. I was unable to load the form at all on an iPhone 4 (even in Chrome). Therefore, although ideally the form should work in any browser, the reality is that it makes use of a number of HTML5 features that are not necessarily present in older browsers. Of course, as time goes on, phones and browsers will incorporate more HTML5 components and therefore, this will be less of an issue.
Once the form is deployed and saved on your device, you can collect data offline. When the device comes back online, it will synchronize the data you have collected with Kobo’s server (note that you can install Kobo Toolbox on a local server, but at your own risk). Then, you can download your data from their easy-to-use website.
For the first week, I set up a basic form that collected largely numerical, text and locational data. We were performing a basic survey and recording sites. Outside of our normal methods of recording sites and locations, I recorded sites with Kobo Toolbox in order to determine its efficacy under rather difficult “real-world” conditions. I collected data for 5 days and Kobo Toolbox worked like a dream. It easily stored the data offline and, once I had access to a data signal, all the queued data was quickly uploaded. I had to open the form for this to occur. I was unable to upload with a weak cellular data signal. It only completed uploaded once I had access to WiFi (late on Friday night). However, it synchronized nicely and I was able to then download the data (as a CSV file) and quickly pull it into QGIS.
The single biggest problem that I discovered in the field was that I needed to be able to see the locations of the sites recorded with Kobo Toolbox on a dynamic map. Although Kobo Toolbox recorded it nicely, you cannot see a point on the map, so I had to use another method to visualize what I was recording. The only way to see the recorded data is by downloading from the Kobo Toolbox, but a data connection is required. You can see and edit the data only if you submit as a draft. Once the data is submitted however, you cannot edit it in the field (this was true of other field collection systems that I have used, e.g. Filemaker Go). Yet, I still needed a way to visualize site locations (so I could determine distances, relationships to geographic features and other sites, etc. while in the field).
For this purpose I used iGIS, an free IOS app (see below for limitations; subscriptions allow additional options). Although this is an IOS app with no Android version, there are Android apps that function similarly. With this app, I was able to load my own data as shapefiles (created in QGIS) of topographic lines, previous sites and other vector data, as well as use a web-based background map (which seemed to work, even with very minimal data connection). Raster data is possible, but it needs to converted into tiles (the iGIS website suggests MapTiler, but this can also be done in QGIS). Although you can load data via multiple methods (e.g., wifi using Dropbox) I was able to quickly load the data using iTunes into the app. Once this data is in the app on the phone, an internet connection is no longer needed. As I collected data with Kobo Toolbox, I also collected a point with iGIS (with a label matching the label used in Kobo), so that I could see the relationship between sites and the environment. Importantly, I was also able to record polygons and lines, which you cannot do with Kobo Toolbox. Larger sites are better represented as polygons, rather than points (recognizing the c. 5-10m accuracy of the iPhone GPS). The collection of polygons is a bit trickier, but it works. Polygons and lines can later be exported as shape files and loaded into a GIS program. By using equivalent naming protocols between Kobo Toolbox and iGIS, one can ensure that the data from the two sources can be quickly and easily associated. The greatest benefit of iGIS is seeing the location of data points (and lines and polygons) in the field and being able to load custom maps (vector and raster) into the app and be able to view without a data connection. Although this is possible with paper maps (by printing custom maps, etc.), the ability to zoom in and out increases the value of this app greatly. Getting vector data in and out of iGIS is quite easy and straightforward. iGIS is limited in a couple of ways; nearly all of which are resolved with a subscription, which I avoided. Here’s a brief list of limitations:
– All points (even on different layers) appear exactly the same (same size, shape, color; fully editable with subscription). This can make it very difficult to distinguish a town from a site from a geographic location
– Like points, all lines and polygons appear the same (also remedied with a subscription). I was particularly difficult to tell the difference between loaded the many uploaded topolines and collected polygons.
– Limited editing capabilities (can edit location of points, but not nodes of lines; can edit selected data).
– Limited entry fields ( remedied with subscription, but, perhaps this is not necessary, if it can be connected to data collected with Kobo Toolbox).
– Unable to collect “tracks” as with a traditional GPS device (Edit- OK, so I was wrong about this! You can collect GPS tracks in iGIS, even though this is not as obvious as one might like).
The final limitation of iGIS was not something that was originally desired, but became incredibly useful in collecting survey data, especially negative results (positive results were recorded with the above). Our survey employed a “stratified opportunistic” strategy. We largely relied upon local knowledge and previous archaeological identification to locate sites, but also wanted to sample the highest peaks, mid-level areas and valley bottoms. In order to do this, we also used three different strategies. First, we utilized knowledgeable community members to take us to places they recognized as archaeological sites. Second, we followed selected paths (also chosen by local experts). Third, we chose a few points (especially in the higher peaks c. 200-300 meters above the valley floor). One of the most important aspects of this type of survey was recording our “tracks” so that we would know where we had traveled. This is commonly done with GPS units, but I was able to collect these using MotionX-GPS with the iPhone already in use. The GPS “tracks” (which are really just lines) as well as “waypoints” (i.e., points) were easily exported and loaded into QGIS. This allows for an easily collected data about where surveys traveled, but did not find archaeological sites. (Edit- Note that you can use iGIS for this function! MotionX GPS is not needed, therefore. It is great for recording mountain biking and hiking, however!).
One final comment will suffice here. I just discovered a new app that may be able to replace iGIS. QField is specifically designed to work with the open source GIS program QGIS. Although it is still new and definitely still in development, it promises to be an excellent open source solution for offline digital data collection- though limited to Android devices!