Introduction

Nowadays, 30 years is not old. In science, however, 30 years can be ten lifetimes. Everyday research expands our horizon of knowledge, and technology is paving the way to visualising patterns through data. Modern techniques and practices are becoming more productive, more reliable, and ultimately safer. We are in the middle of a technological revolution!

This innovation is continuously adapted and translated. To be used in every industry and spilling over onto everyday devices, such as mobile phones. Modern smartphones and tablets are now capable of so much more. They have become a promising, viable and platform for mobile data collection. Capturing images, data, or measurements electronically opens up the door to more straightforward, shareable, reliable data collection.

This guide aims to open up and clarify the potential of mobile data collection (MDC). Specifically, how and why to use these MDC apps, how to convert from paper-based forms, the best practices for offline data collection, query management and lastly the power of real-time analytics. 

Who is this guide for?

This guide is for academic researchers, humanitarian workers, NGOs and commercial organizations that are interested in implementing secure, scalable, and effective data collection. While this knowledge is optimal for use with the Teamscope app, the concepts and benefits of using mobile data collection are widely applicable.

Choosing an app

7 Mobile Data Collection Apps for Field Research

What is Electronic Data Capture (EDC)?

Electronic Data Capture (EDC) is a computerised system for the collection and storage of research data in an electronic form. EDC was first introduced in the early 1980s (Hyde, 1998) to address the many shortcomings of paper-based forms, such as increased errors through transcription and late detection of inaccuracies. The first of these EDC systems to become widely adopted where Microsoft Access and MySQL. With the turn of the century came the cloud, which expanded any web browser into a platform to visualise and complete forms. This innovation was the big bang of the paper-less movement. 

Despite the advances in web-based data collection systems, historically field researchers and clinical teams working on the go have still suffered from the burden of paper-based data gathering. This is due to a simple reason: web-based data collection tools become useless when there is no internet. Although smartphone adoption in the world has skyrocketed in the last five years, internet access has not increased at the same speed, and so much of the world today remains offline. 


Offline data collection

The solution to capture data on-the-go, and often offline, are mobile applications with the capability of storing forms and data locally and synchronising it afterwards once a connection is available. As researchers today see the immense advantages of using mobile data collection apps over paper-based forms, the number of EDC options grows. With this article, we hope to answer the question of which of these options may suit your research purposes best. Interested in learning what are the best practices for offline data collection? Check out this article.


Longitudinal vs cross-sectional research

When looking into data collection tools for research, it is essential to acknowledge that studies differ in their design and purpose. Thus the platform of choice should be flexible enough to be used for a range of different data, as well as in potentially disconnected areas.

One crucial distinction between different research projects is the time frame. Will the data only be captured from subjects once, in other words, cross-sectional? Or does the research require measurements at multiple moments across time, in other words, longitudinal? 

Cross-sectional study: Research that involves recording data at a single one point in time, a so-called, snapshot of a population is a cross-sectional study. This data is only collected once. Often, these studies do not collect personally identifiable information (PII) as there is no need for a follow-up on the study subjects. These types of studies are always observational, wherein researchers record information about their subjects without manipulating the study environment. Examples of cross-sectional studies are patient registries or household surveys.

Longitudinal study: For these studies, researchers collect specific data at multiple time points (i.e. cross-sections) for each individual subject.  Changes in data over time can then be compared and analyzed. These analyses can be for a particular case or the study population as a whole. 


With an ever-increasing saturation of mobile data collection apps, we researched the best ones to date. We aimed to investigate their range of utility - for both cross-sectional and longitudinal studies-, their suitability for offline research, and their further services that set them apart.  



1. Teamscope

Teamscope is a secure and easy-to-use data collection platform, specially designed for sensitive data and clinical research. 

In a field where most tools are web-only and useless without an internet connection, Teamscope offers a unique approach at on-the-go and secure data collection. With it’s offline-first Android and iOS app, Teamscope allows researchers to create powerful mobile forms, collect data offline and visualize it with a few clicks.

Teamscope sets data security as its highest priority. Data is stored encrypted on mobile devices and users, apart from requiring a username and password to login, must create a four digit passcode to unlock the app. All sessions on it’s mobile app time out after 30 seconds of inactivity or once the app has been closed, to access the app a user must reenter their Teamscope passcode.  

When conducting a longitudinal study, researchers can make use of Teamscope’s longitudinal mode. This function allows them to create cases for individual subjects, share them with other users in their project, and upload data for their cases in multiple moments

With a dedication to enabling collaboration and communication within and between studies, Teamscope has recently released Open Research. This new and unique feature of an open database of planned, ongoing and completed studies which utilize Teamscope, aims to facilitate discussions and connections between researchers. 

Teamscope has three subscription plans, and the first one, Open Research, allows users to use the platform for free with up to 5 users, unlimited form submissions and storage. The other options, "Team" and "Enterprise" plans, expand on the Open Research plan through longitudinal research options and electronic Patient-Reported Outcomes (ePRO).

Features: Study builder, offline data capture, longitudinal data collection, data analytics, customer support

Cost: Free for up to 5 users

Availability: iOS and Android


2. Open Data Kit

Open Data Kit (ODK) is open-source software for collecting, managing and using data in resource-constrained environments. The goal of ODK is to offer open-source and standards-based tools which are easy to try, easy to use, easy to modify and easy to scale (ODK website). 

Open Data Kit allows multiple types of data - from text to pictures to location - to be entered and collected in line with the researchers need.

To make these tools widely accessible and functional, ODK is supported in multiple languages and further works offline. They allow teams to use ready-to-use mobile, desktop or server devices or customise them to suit their needs. More specifically, the Open Data Kit community offers two suites of software; ODK and ODK-X. The former provides access to simple tools that have a proven history of large scale deployment for mobile data collection. This suite of software is appropriate for common cases. The later suite of software, ODK-X, offers tools for more complex workflows. For this software, Javascript customisation allows a very flexible suite which further features longitudinal data collection, bi-directional synchronization, and on-device data management. 

Open Data Kit further has an immense and highly active community. The ODK forum (https://forum.opendatakit.org) is a space where ideas on mobile data collection can be shared and discussed. Here users can also find assistance on the ODK software. 

Features: Study builder, offline data capture, community

Cost: Free, open source

Availability: Android


3. KoboToolbox

KoBoToolbox is a free, open-source tool for mobile data collection developed by the Harvard Humanitarian Initiative. KoBo Toolbox is widely used for data collection in humanitarian organizations like the International Rescue Committee (IRC), United Nations Office for the Coordination of Humanitarian Affairs and Save the Children. 

Data entry may be done via the web browser or on Kobo Toolbox’s Android application called KoboCollect. KoboCollect supports offline data entry with on both Android phones and tablets.

The KoBoToolbox software can be installed on any computer or server, and there are two servers available that allow for free usage: http://bit.ly/2KeHxOK

To visualize, analyze, share, and download your collected data, researchers may use KoBoToolbox’s web application. Advanced users can also install their KoBoToolbox instance on a local computer or server. 

Features: Study builder, offline data collection, open source, community

Cost: Free, open source

Availability: Android and Web.


4. REDcap

REDCap is a secure web application for building electronic case report forms and managing databases. 

REDCap was created in 2004 at Vanderbilt University. At that time, most Electronic Data Capture (EDC) platforms were geared towards large clinical trials. These, however, were too expensive for academic biomedical researchers in need of a data collection tool that met HIPAA and ICH-GCP compliance standards. The objective of this project thus was to empower the researchers by allowing them to single-handedly manage their databases, without the need for any programming or technical knowledge.

In April of 2015, REDcap released its iOS and Android application, which extended the functionality of the platform into smartphones and tablets and enabled data collection in places with slow or no internet. 

REDcap is used in over 130 countries by more than 3.600 institutions. 

Non-profit organizations can join the REDcap consortium and receive a free license of the software, which allows them to install and manage REDcap on their own IT infrastructure. 

Features: Longitudinal data collection, offline forms, randomization, on-premise hosting

Cost: Free for nonprofits

Availability: Android, iOS and Web.


5. Magpi

Magpi is a mobile data collection app that allows users to create electronic forms both on and offline within minutes. Its use extends through the health, agriculture, environment and industry sectors, where rapid and low-cost conduction of mobile surveys enables scalable and straightforward research. 

Various functions of Magpi include offline entries, automatic updates, photos and GPS stamping. Further integrated workflows allow feeding user’s data into almost any web-accessible system, including Google spreadsheet, Salesforce account or SQL databases. 

Magpi aims to make the most out of mobile data collection apps by reducing accidental errors through logic branching, eliminating wasteful paper use and benefiting from fast input and automatic analysis of modern-day smartphone capabilities.

With four easy steps from setting up an account, to creating a form, and downloading the app, you can start collecting data. This simplicity and efficiency mean you are already running within minutes. 

Features: Offline data collection, SMS notification, Interactive voice response (IVR) data collection, Zapier integration

Cost: Free basic accounts, paid pro and enterprise plans available

Availability: iOS and Android 


6. Jotforms mobile

Jotforms, a reputable simple online form builder, has expanded its range with a new mobile data collection app called Jotforms mobile. 

This app allows users to collect various types of data, such as voice recordings, barcodes, geolocations and electronic signatures and then build, view, access, sort, fill out, share, and organise all this data in a single place. The utility of using a mobile data collection app, in this case, enables it to function offline and utilise iOS and Android push notifications to alert the user of new respondents or changes in data. PDF copies of submitted information can even be downloaded or shared. 

With ever-increasing sizes of studies and research groups, Jotforms mobile further enables collaboration between team members. Forms can be created and assigned to individual researchers who will then collect data even in areas with limited or no connection to the internet. Once respondents have filled in the forms, you can view the data, and act quickly on the information you have received. 

The continuing development of JotForms mobile makes this very useful and scalable mobile data collection app. 

Features: Mobile form builder, Offline data collection, Kiosk Mode.

Cost: Free basic accounts, paid pro and enterprise plans available

Availability: iOS and Android 

7. Survey CTO

Survey CTO is a reliable, secure and scalable mobile data collection app for researchers and professionals. This app expanded on the Open Data Kit (ODK) software to increase its scale, utility and power. 

The application allows users to design a variety of complex survey forms with either an intuitive spreadsheet format or a drag-and-drop form. Data can further be pre-loaded and streamed between datasets. The data can also be collected offline with the SurveyCTO Android app or using an online web interface. The data is kept secure through multiple layers of encryption and redundancy and is further GDPR compliant. The researcher or professional is further able to monitor all incoming data using review and corrections workflow, automated quality checks, and data classification systems. Visualisation of the data is almost instant through a built-in tool, and further analysis of the data is done using external analytical tools. 

The platform itself consists of four components; the server console which functions as a host for both empty and filled-in forms. Here the forms are further designed, tested and reviewed. The second component is the android app used for collecting the data. From here it is either uploaded to the server console or synchronised over local wi-fi networks. The third component of SurveryCTO is SurveyCTO sync, a desktop application, responsible for downloading, transporting, exporting, and processing the data. The last element is the data explorer; here, the data can be monitored, reviewed, and visualised. 

SurveyCTO has further built up a large community of users over 165 countries that aim to offer advice and information on various projects: https://www.surveycto.com/product/users/.

Features: Data encryption, Monitoring and visualization, Online training course

Cost: $198 per team per month

Availability: Android and Web 


Conclusion

Mobile data collection apps are becoming integral to secure, reliable and scalable research. The efficiency and dependability of these electronic data capture apps, even in offline settings, open doors to new research possibilities. It begins with the freedom and adaptability of designing research-specific forms that work even in the most challenging environments; it continues with secure and collaborative data collection, and ends with faster data analysis and visualisation. 

Data in research is always bound by ethical and technical dilemmas. Data should be reusable, findable, accessible, and interoperable according to the FAIR principles (Wilkinson et al., 2016). These dictate that data should be licensed and provide accurate information, have a persistent and unique identifier, be understandable and stored securely, and have broadly applicable language for knowledge representation, respectively (Cavalli, 2018). Although any digital form may suffice for the purpose of data collection, not every data collection system may be used for sensitive, clinical or research data.

We believe that Teamscope stands out in the mobile data collection landscape and is the best choice for research purposes. No other application combines data encryption, passcode lock, cross-device compatibility with iOS and Android, support for both cross sectional and longitudinal studies, like Teamscope does. Moreover, the availability of a free plan (Open Research), enables this technology to any researcher in the world.

Are you planning on launching a new study soon? Register for a live demo today

References: 

Cavalli, Valentino. “Open Consultation on FAIR Data Action Plan.” LIBER, 13 July 2018, http://bit.ly/2Ymffdv.

“Because Your Data Is Worth It.” SurveyCTO, www.surveycto.com/

“Data Collection App for Research: Get Started for Free.” Teamscope, www.teamscope.co/.

“Data Collection Tools for Challenging Environments.” KoBoToolbox, www.kobotoolbox.org/

“Easy Mobile Forms, Anywhere On Any Device.” Magpi, www.home.magpi.com/

Epesito, Emily, and Matthew Guey. “The 5 Best Data Collection Tools in 2019: The Best Apps for Gathering Data in the Field.” Zapier, Apr. 2019, www.zapier.com/learn/forms-surveys/best-data-collection-apps/

Hyde, A.W. (1998). "The Changing Face of Electronic Data Capture: From Remote Data Entry to Direct Data Capture". Therapeutic Innovation & Regulatory Science. 32 (4): 1089–1092. doi:10.1177/009286159803200429.

Moriki, Darin. “Top 6 Mobile Data Collection Apps You Need to Try: The JotForm Blog.” Jotform Blog, 4 June 2019, www.jotform.com/blog/top-free-mobile-data-collection-apps/.

“Open Data Kit.” Open Data Kit, 1 Mar. 2018, www.opendatakit.org/

“REDCap.” REDCap, www.project-redcap.org/

Wilkinson, M. D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. doi:10.1038/sdata.2016.18

Getting started

How to Convert your Paper Form into a Mobile App

What is mobile data collection?

Mobile data collection is the method of capturing any information electronically using a mobile device, such as a smartphone or tablet. Switching from paper forms to digital forms is proven to improve data accuracy by 47.5% and reduce the cost of research by 75%.

In settings where there is a fast internet connection and the availability of a computer, an online survey or Electronic Data Capture (EDC) like REDcap or Castor EDC is a powerful resource. But what if you or team will be working on-the-go, moving from location to location and perhaps in settings where there is slow or no internet connection? The solution is a mobile data collection app.

Once you know what information or data you will like to collect comes the task of choosing a data collection mobile app. Here are 7 mobile data collection apps that allow you to build mobile forms and capture data from a tablet or smartphone, even when you are offline. 

Mobile data collection apps will allow you and your team to collect data offline and afterwards uploaded to a server. Capturing data offline requires certain precautions to mitigate the risk of data loss, check out this previous blog post on the best practices for offline data collection.


How to implement a mobile-friendly form?

Once you have chosen a mobile data collection app comes the challenge of converting your paper form or building it on a data collection platform. The following tips have Teamscope app in mind, yet this advice applies for other mobile data collection tools. 

1. Less is more.

Specific changes and challenges are inherent to the conversion of a paper data collection form into a mobile one. Especially for smartphones, smaller screen size and slower typing speed on mobile keyboards may hinder the clarity of the form and the rate of data entry, respectively. 

Furthermore, scrolling endlessly or having to type long answers with a mobile keyboard can be tedious and demotivate your team.  By minimizing the number of fields and data that need to be collected, you can improve the user experience and avoid long unnecessary responses.

In other words, keep your form as short as possible and consider dividing a single questionnaire into multiple ones.

In terms of scale for your research; the minimal file size of data entries means you can store hundreds or even thousands of entries on a single device while working offline.


2. When in doubt, use branching logic

Branch logic is a feature that changes what question or page a respondent sees next based on how they answer the current question. When using a mobile app, this freedom allows you to show/hide specific fields based on previous data inputs. We utilize branch logic to improve the readability of your form as well as make it as visually lean as possible. After all, less is more.

An illustration of multiple field being connected via branching logic



3. Split tables or grids into individual fields

Certain data requires tables or grids. On mobile apps, however, these tables may bring about a series of challenges. If the table has too many columns or a device's horizontal space is too narrow, it may be tedious to scroll horizontally to enter data.

The best solution to this is to think of each cell on a table as an individual form field. For example, if you have the following 2x3 grid, when you build that table for mobile data collection, you will end up with 6 form fields, instead one a single table: 

An example of a grid that has two rows and three columns, being converted into 6 individual fields on a mobile form for better data collection

4. Create sections with titles

When completing a mobile form, especially long ones, users may lose track of where they are within the questionnaire. Helping them know where they will help them reduce mistakes and have an easier time entering data. To support further understanding and clarity within your form, we suggest you use as many titles as possible, and these will automatically create sections for you on Teamscope.   


5. Use an additional text field when requiring "please specify".

Asking to "please specify" when the answer is other is a standard method to expand the universe of answers in single and multiple-choice questions. On paper forms, the space to define will be a dotted line alongside the choice "other". 

On mobile forms, however, the dotted line to specify must be a field in itself.  To achieve this, we suggest you make use of an additional text field that is only displayed when a user selects "other".

6. Consider implementing checklists as a multiple-choice field

Checklists are a great way to go through procedures and serve as great reminders. One of the essential building blocks of mobile forms is multiple-choice questions, so if you need a checklist within your form, you can use a multiple-choice field. Teamscope further supports calculated fields; which means you can have an additional field right below the list that displays the percentage of completion. 


7. Try out emojis within your forms

Mobile forms can quickly become monotonous, and with that, it increases the possibility for mistakes in data collection. A great way to make a form more visual and user-friendly is to use emojis. Emojis can be used within titles as a visual aid to know what section you are in and on scales (e.g. pain) to support the interviewee.


Conclusion

Data collection forms are the fundamental building blocks of clinical and field research. Switching from paper-based data collection to Electronic Data Capture (EDC) is a direct way to reduce project costs, collect data faster and with fewer mistakes. When researching challenging settings, researchers may find that traditional web-based data capture solutions are less handy and thus resort back to paper forms. 

With the help of data capture mobile applications, like Teamscope, researchers can effectively collect data while on-the-go and even in offline settings. Although smartphones and tablets are becoming a more powerful tool from year to year, researchers must also recognize their limitations. These deficiencies are in regards to screen size, data entry speed, and mitigating the risk of data loss in offline locations.

working offline

How to Capture Data without an Internet Connection?

Losing data can be catastrophic to a clinical or field study. Data collection is the means to a higher end. We rely on data to measure and evaluate a project, develop a new treatment or make decisions that can improve the lives of others.

Replacing paper forms with electronic data capture allows us to take higher precautions with our data. Data collected digitally can be instantly validated, analyzed and provided to stakeholders.  

One of the concerns that researchers have when considering replacing paper questionnaires with a digital tool is, will it work anywhere, even if there is no internet connection? The answer is yes, but please don’t skip this guide as there are significant limitations to that initial answer that could affect the integrity of your data operations. 

What is offline data collection?

Offline data collection is referred to data that is gathered in environments with slow or no internet access. Examples of such settings can be remote villages or large buildings with poor WIFI coverage. Offline data collection is made possible by tools that can store data temporarily in the memory of a smartphone, tablet or computer, and once an internet connection is gained, upload it to a server. 

According to the International Telecommunications Union (ITU), the developing world is far from reaching the levels of connectivity the developed world has reached. More than 4 billion people have no access to the internet in more than 20 countries.

Platforms like the ones described in the first chapter of this guide 7 Mobile Data Collection Apps for Field Research will allow you to store data without a connection and then upload it to a server.


Offline data collection for a needs assessment study in Bosaso, Somalia


5 considerations when collecting data offline

By understanding the limitations and capabilities of any tool we can make the most out of it. Here are 5 considerations to keep in mind if you know you will be doing data collection in a setting that has slow or no internet.

1. Synchronize your data as soon as you can.

Consider offline data always at risk of being lost. Just like a suitcase with hundreds of paper records, a smartphone with valuable research data that is not yet uploaded to the cloud is a liability to a research team. All it takes is for that mobile device to be lost or damaged for valuable information to be lost. 

To mitigate the risk of data loss, synchronize your data as soon as possible. Establish a standard operating procedure (SOP) with your field team and minimize the risk of offline data being lost by scheduling periodical moments when data will be synchronized with your server. 

2. Don't clear 'app data' or reinstall the app otherwise offline data may be lost.

Deleting a mobile app can permanently remove any data that is associated with it. Only delete an app once you are sure that all of the local data has been uploaded to a server.

App developers will periodically provide updates of an app. This can be to fix bugs or release a new feature. Some apps will delete local data when an update is installed. Make sure you read the release notes of your data collection app to see if data must be synchronized before updating.  

Teamscope Reminder
At Teamscope we work hard in improving our platform. We are regularly releasing new versions of our Android and iOS app. When installed an app update, offline data will not be lost. Deleting our app though will permanently delete any data that you have stored, including offline data entries.

3. When uploading a batch of offline form entries, check for the fastest connection.

Depending on your internet connection and the amount of data in those form entries, it can take seconds or up-to minutes to fully upload all of your data.

Check what is the fastest connection available around you. You can download the Speed Test app on your mobile device and see what is your fastest connection available.


4. Don’t use mobile notifications that require an immediate reaction.

Mobile notifications, also known as push notifications, allow apps to notify users without them having to open an application. They are a powerful way to instantly refer patients or remind us to complete task. A downside of mobile notifications is that they are not guaranteed to be delivered if the device has low-to-no connectivity.

If your team will be working mostly in an offline setting it’s best that you don’t implement notifications that will require them to take urgent actions.

5. Design a patient referral workflow that is resilient to connectivity issues

Medical and humanitarian teams will often implement task-shifting to maximize resources. A child might be screened in a village by Community Health Worker (CHW) using an algorithm and if the patient is sick or requires treatment, will be referred to a medical center.  

Mobile data collection can improve the effectiveness of task-shifting interventions by allowing both parties to share data on cases that require further treatment or followup.

Since connectivity can be an issue in challenging environments, design a task-shifting workflow with this limitation in mind. The CHW can store the patient data digitally on a mobile data collection platform and additionally provide the patient a paper copy of the referral information.

Conclusions

Regardless if your are conducting a clinical study in a remote village in Kenya or in a hospital in the Netherlands you are not assured to have a stable internet connection at all moments. This is why our platform has been offline-first since day one, hundreds of researchers collect offline data everyday around the world using that functionality of our Android and iOS applications. We are continuously looking for ways to help you work seamlessly without the need for internet and we are happy to hear from you on how we can further improve this feature.

data security

5 Ways to Keep your Data Secure

When doing data collection, efficiency, cost management and data integrity are of paramount importance. Researchers strive to reduce possible data errors in data collection and minimize the cost of transcribing paper data.

Mobile data collection is the use of smartphones and tablets to capture study data electronically. Mobile devices can empower a research team by eliminating the use of paper forms and enhancing the study workflow with robust data validation, branching logic and decision support.

Although mobile data collection can be a powerful instrument, it opens the door to potential security shortcomings. For example, what happens in the unfortunate event that a team member loses a device with research data or has it stolen, can someone access that sensitive information?

Alternatively, how can we trust that as we enter data on a mobile device, it is safe from tampering?

In this article, we will answer those questions and address what features to look for when building or choosing an available app for mobile data collection.

What is sensitive data?

When doing field and clinical studies, researchers often will need to collect, store and analyze sensitive information from their participants.

The term sensitive data is used to refer to data that reveals the identity of a study participant or subject, commercially sensitive information that if disclosed could cause economic harm to any person, data on rare or endangered species, and data that poses a threat to others or have a negative public impact.

Access to sensitive data should be safeguarded, and researchers are obliged to obtain informed consent from their participants and use best practices when gathering and storing this type of information.

Although researchers can use any mobile form app to create forms and collect information from their study participants, not every mobile app is designed to handle research data.

How to keep your data secure

The following are security features that distinguish a mobile data collection that can be used for research purposes from a general survey tool.

1. Data encryption

When data is saved using an electronic form, it is transferred and stored in a database. This database can be hosted on a cloud server or in the case of a mobile data collection app, a smartphone or tablet may also act as a storage medium.  


Data at rest vs. Data in transit

Data protection is vital at two pivotal moments: when it is communicated across the network, data in transit, and once is stored in a database, also known as data at rest.

Data at rest is data that is inactive and stored physically in any digital format, for example, a computer server, an external hard drive, or the memory of a mobile device.

Data in transit is data that is in movement and transmitted through the internet.


Plaintext vs. Encrypted

Regardless if it is at rest or in transit, data can have two forms: plaintext or encrypted. Plaintext data is at a higher risk as anyone with the capability of intercepting it in transit (i.e. man in the middle attack) or with physical access to a server, may be able to obtain and tamper the data.

For a platform to mitigate the risk of interception, theft, or tampering of data in transit, it must communicate using robust security protocols, such as Transport Layer Security (TLS).

Mobile data collection adds a new layer of complexity to data at rest. Mobile Data Collection apps can store data in two locations, on a cloud server and also in the local memory of the smartphone or tablet. Since mobile devices have a sizable risk of them being stolen or lost, mobile data collection apps must also encrypt the data that is at rest on the memory of the device, especially if it is sensitive data.

Teamscope encrypts data at rest on our iOS and Android app using 256-bit AES. Data at rest on our servers is also stored encrypted using AES-256 and keys are stored encrypted in Amazon’s Keys Management System using a process called envelope encryption.

2. Audit trails

The standard functionality of a data collection application is to allow for saved data to be changed or modified. A user might need to edit data on a completed form to correct a data entry mistake or add additional information.

A secure data collection application has to be able to transparently show the complete history of data creation and changes and attribute them to a user. Researchers often refer to this functionality as an audit trail or a revision history.

An audit trail record will contain details that include the date, time, and user information associated and what action was taken by that user, for example, “edited a form”.

An audit trail helps to maintain accountability across a research team, identify areas of non-compliance or possible issues in how a data collection form has been set up.

When doing mobile data collection, an audit trail is fundamental.

Teamscope automatically tracks all data creation and modifications with its audit trail feature.

3. Access management

Research is a collaborative effort; it requires teamwork from start to finish. A project team might be split up into different functions, levels of responsibility and geographic areas. Some team members will be doing the day to day work of collecting data while others only data analytics.

Teams can also be dynamic; a study manager might add new team members to speed up data collection or perhaps remove someone that has left the organization.

How can we ensure that proper access is maintained and controlled even if members of a team have left?

How do you ensure that proper access is maintained and that if you choose to remove someone from your team, they no longer are capable of accessing your project or study data?

This is solved by implementing an access management system.

An access management system ensures that the proper people in an organization or team have the appropriate access to a specific resource. Access management systems in a data collection platform identify, authenticate and authorize individuals whenever they wish to complete a mobile form or view previous data.

A robust access management system should have the capability of assigning granular permissions to each user based specific privileges, for instance, “view data” or “export”.

4. Session timeout and App Passcode

Android and iOS users can help secure their phone or tablet by setting a screen lock. Each time a user turns on a device or wakes it up, the device will become unlocked with a PIN, pattern or password.

More modern devices may even require a bio-password such as a fingerprint scan or facial recognition.

Users can choose whether they want to have an automatic screen lock on their mobile device or not. However, what happens if a device is stolen or lost and the owner had not enabled a screen lock? Then anyone can swipe to activate the device and access any stored sensitive data, including valuable research data.

It is for this reason that a mobile data collection app, similar to banking or password storage apps, must time out if the user is inactive for a short period and grant access only after entering a valid password, PIN or fingerprint again.

5. Data backups

Data backup is a process of duplicating data and saving it in another location for retrieval in case of a data loss event, natural disaster, or other kinds of emergency. A robust data collection system should have a periodic, ideally automatic, data backup procedure that ensures that data is secure and protected from loss or damage.

Additionally, a standard operating procedure (SOP) should be in place, describing how Backups are retrieved.

Conclusion

Mobile data collection is a practical way to reduce costs and collect better data in clinical and field research; however, one must be conscious of the potential risks that come associated.

Not every app that supports mobile form creation and data entry are suitable for capturing and storing sensitive research data. Researchers must be aware of the risks involved when storing sensitive information on a mobile device.

Teamscope is a secure and easy-to-use Mobile Data Collection app for clinical and field research.

With Teamscope, researchers can build powerful mobile forms and benefit security-specific features, such as the ones described above. Through this, they are improving the quality of their research data and can rest assured that they are adhering to the highest standards.

Planning on starting a new clinical or field study soon? Schedule a live demo here.

Cover image: Axel Fassio/CIFOR (CC BY-NC-ND 2.0)

Reference:

“Dealing with sensitive data,” University of Bristol, http://bit.ly/30Aj0cJ

Data Validation

How to Ensure Data Accuracy with Query Management

Is data being collected according to the protocol design? Are there any data errors or fields that are being left empty? Which of my sites or team members are generating the most invalid data? These are the usual worries that every researcher has when conducting a clinical study yet most are only capable of answering them once data collection has ended, and they are performing data analysis. Correcting invalid data months after it's collected can be a nightmare and extremely consuming. Dirty data leads to weaker conclusions and sometimes the need to redo part, or all, of the data collection. Is there any way that a researcher can identify and resolve problems in their data while it's gathered?

The answer to this is a query management system (QMS). After reading this blog post, you should have a clear understanding of what queries are in clinical research and why automatic query management is a researcher's best friend.

What are Data Queries?

A data query is an error or discrepancy generated when a validation check, either done manually or by a computer program, detects a problem with the data. A query management system is a tool that tracks data queries so they can be adequately individualized and resolved. QMS substantially minimizes and even eliminates the risk of invalid data being unnoticed. When a data query (e.g., data issue) is created it should be persistent, which allows it to be tracked over time, and only be resolved in the following ways:

  • by correcting the error, in other words entering a new value that is valid
  • by marking the data in conflict as correct

Implementing a query management workflow

Clinical data collection may be done in different ways, some researchers use paper forms, excel while more experiences one's Electronic Data Capture, here we expose how query management can be set up with different data collection methods:


Paper Case Report Forms (CRFs)

When collecting data with paper Case Report Forms (CRFs) the task of transcribing the data from paper to a database software may be carried out by a separate team. This team is responsible for confirming that data has been correctly collected and will often do this twice in a process called double data entry, to minimize the possibility of mistakes being unnoticed and new errors being of created during data transcription. Any discrepancies that may be found during double data entry may be kept on a separate Excel file, so they are tracked and resolved by contacting the person that originated that issue. Collecting research data with paper forms is not only prone to mistakes with handwriting interpretation but also makes the task of validating data extremely time-consuming. We have published an article specifically on why researchers should not use paper forms.

Example of a paper CRF (Bellary S, et al. 2014)

Online survey tools.

Creating data validation rules with online questionnaires like Qualtrics and Survey Monkey is possible. Validation rules may be established to force or remind a user that a field is required or that a value is out of range. Data validation minimizes the possibility of errors and required fields being left empty. Although data validating can be automatic, isolating data issues with an online survey tool needs manual filtering and a high level of attention to assure no data problems are unnoticed.

Spreadsheets

Excel is often used for research data collection. Researchers value the fact that Excel is almost as ubiquitous as a computer and that it works without the need for internet. Excel’s data validation is very powerful; you can use formulas that nest arithmetic calculations and combine multiple fields or variables.

As mentioned above, data validation is only the first step in a query management workflow, and since Excel does not generate reports of data issues, to raise and resolve queries one has to rely on manual and time-consuming work.

Electronic Data Capture

Electronic Data Capture (EDC) is software specially designed for the collection of clinical data in electronic format, often for use in human clinical trials. EDCs, like Teamscope, have built-in query management and comply with Good Clinical Practice (GCP). We recommend to always use a validated EDC for collecting sensitive and research data. EDC eliminates the need for paper forms and drastically simplifies data monitoring.

How queries work on Teamscope

Teamscope’s query management is built on top of our data validation system.

Your first step is to add a Condition to any data field:

Data queries are automatically generated when a value is invalid, matches warning criteria or is required and has been left empty:

From Teamscope Web you can see:

  • Who in your team created this data query
  • When it was originated
  • The data that caused
  • The condition that triggered it: Invalid, Warn or Required
  • The status: Open or Resolved

By clicking on the status of a query you may change from Open to Resolved, and vice versa.

Alternatively, whenever the data issue is fixed, the platform automatically ✨changes the status of the query from Open to Resolved:

Conclusion

When a researcher finds out months or weeks after data collection that there are issues with his/her data, this not only means the studies’ outcome will be weaker but potentially data collection will have to be redone. The best way to mitigate this risk is to use an Electronic Data Capture system that has the capability of not only validating data as its inputted but most importantly keeping track of the data entries that have issues. A query management system (QMS) automatically isolates data issues and allows researchers to react to them immediately, giving them full control of data quality and accuracy.

Teamscope’s Query Management System is fully automated and easy to use. Want to have a custom demo with one of our specialists? Sign up here.

Reference:

  1. Wikipedia contributors. (2018, October 3). Clinical data management. In Wikipedia, The Free Encyclopedia. Retrieved 20:36, January 2, 2019, from https://en.wikipedia.org/w/index.php?title=Clinical_data_management&oldid=862284831
  2. Bellary S, Krishnankutty B, Latha M S. Basics of case report form designing in clinical research. Perspect Clin Res 2014;5:159-66
Data analytics

How to get started with Data Visualization

A person pointing to a data dashboard on a laptop computer.

Seeking Answers

When doing research, we generally divide our work into distinct stages: planning, gathering, analysing and publishing. As researchers, we are moved by curiosity to gain a deeper understanding of the  world around us. We may even dream that our research can improve the lives of others. For example, clinical or field studies often seek to gain new insights on diseases or the effectiveness of new interventions. 

"The goal is to transform data into knowledge and knowledge into insight."

New insight may cause us to reexamine existing conventions and challenge the status quo. Or, it may even open the door to further research. Yet how do we gain this insight? With which aim must we set out and which paths must we follow? 

The Cambridge dictionary defines insight as: (the ability to have) a clear, deep, and sometimes sudden understanding of a complicated problem or situation. 

To begin, we must possess the ability to gain insight. Perhaps through experience, through learning, or through research. While the former 2 are vital, we would like to focus on the later. Insight through research often requires us to aggregate data, to make sense of it and thus to obtain a unique understanding.

This data aggregation usually ends up as tabulated data, often in the form of intimidating massive spreadsheets. However, the whole is greater than the sum of its parts. Through data visualisation (the whole), these colossal spreadsheets (the parts) are refined, organised and displayed in an understandable manner. The challenge of grouping, analysing and sorting the data falls on the shoulders of the computers, while the researchers capture new insights.


What is Data Visualization?

Data visualization is the graphic representation of data (Wikipedia). It involves creating images that contextualize information and help see the relationships among the represented data. By using graphical entities like charts, graphs, and maps, data visualization tools provide a convenient way to see and understand trends in data, outliers, and even tell a story.


How to implement a Data Dashboard?

To visualize data and convert a daunting spreadsheet into descriptive graphs, you first need to choose a data visualization solution and load your data on that tool. There are two ways to do this: by either exporting and importing as CSV/Excel file or by using a REST API.


What is a REST API?

A REST API is a web service that allows computer software to exchange information with each other, using communication standards, like JSON or XML. 

Using a REST API will require a certain level of technical expertise but has the benefit that once a researcher makes the connection between a data collection platform and data viz tool, that data viz tool will keep the data continuously updated.


3 data visualization tools to choose from

Power BI

Screenshot of PowerBI's website

Power BI is a business analytics software d by Microsoft. It provides an easy-to-use interface to build interactive reports and dashboards.

Power BI Desktop is free to download https://powerbi.microsoft.com/en-us/.


Tableau

Screenshot of Tableau's website

Tableau is a Business Intelligence tool for visually analyzing data. Users can create and share interactive dashboards, which depict the trends, variations, and density of the data in the form of graphs, charts and maps.

Tableau offers a free version called Tableau Public: https://public.tableau.com/en-us/s/


Google's Data Studio

Screenshot of Data Studios's website

Data Studio is a data visualization and business intelligence solution developed by Google. Data Studio allows users to connect data from a wide variety of sources, build interactive reports and dashboards and share them with the rest of the world. Data Studio is free to use: https://datastudio.google.com/


Does Teamscope have data visualization capabilities?

Learning how to use a data visualization platform can take time and having to export data and import into a data tool visualization each time a research team wishes to visualize results can be a hassle.

Luckily Teamscope allows project teams to visualize data without leaving the platform. Teamscope supports four different chart types: pie, bar, line and basic statistical analysis. Users can build a data dashboard that is automatically updated as data is collected.


Your graphs on Teamscope can be export any moment to various image formats like JPEG, PNG, SVG so you can customize them or use them in presentations or publications.


Conclusion

Our brain is drawn to perceive patterns. We can quickly distinguish colors and shapes and give them meaning. When we see a chart, our eyes  are drawn to finding trends and anomalies.

Gaining insights is only possible once information is put in context.

Data visualization should accompany researchers along their entire workflow, from planning, piloting, going live and finally in the analysis phase.

It is now easier than ever to build a visually-rich dashboard. Researchers can choose from a wide array of alternatives, and in the case of Teamscope, give life to data and allow it to begin telling a story from day one.


Reference

Wikipedia contributors, "Data visualization," Wikipedia, The Free Encyclopedia, http://bit.ly/2ZuL6c0