z-logo
open-access-imgOpen Access
Human Data Model
Author(s) -
Niko Mäkitalo,
Daniel Flores-Martín,
Huber Flores,
Eemil Lagerspetz,
François Christophe,
Petri Ihantola,
Masiar Babazadeh,
Pan Hui,
Juan M. Murillo,
Sasu Tarkoma,
Tommi Mikkonen
Publication year - 2020
Publication title -
acm transactions on computing for healthcare
Language(s) - English
Resource type - Journals
eISSN - 2691-1957
pISSN - 2637-8051
DOI - 10.1145/3402524
Subject(s) - computer science , scripting language , software , javascript , process (computing) , source code , data science , schedule , software engineering , world wide web , human–computer interaction , programming language , operating system
Today, an increasing number of systems produce, process, and store personal and intimate data. Such data has plenty of potential for entirely new types of software applications, as well as for improving old applications, particularly in the domain of smart healthcare. However, utilizing this data, especially when it is continuously generated by sensors and other devices, with the current approaches is complex—data is often using proprietary formats and storage, and mixing and matching data of different origin is not easy. Furthermore, many of the systems are such that they should stimulate interactions with humans, which further complicates the systems. In this article, we introduce the Human Data Model—a new tool and a programming model for programmers and end users with scripting skills that help combine data from various sources, perform computations, and develop and schedule computer-human interactions. Written in JavaScript, the software implementing the model can be run on almost any computer either inside the browser or using Node.js. Its source code can be freely downloaded from GitHub, and the implementation can be used with the existing IoT platforms. As a whole, the work is inspired by several interviews with professionals, and an online survey among healthcare and education professionals, where the results show that the interviewed subjects almost entirely lack ideas on how to benefit the ever-increasing amount of data measured of the humans. We believe that this is because of the missing support for programming models for accessing and handling the data, which can be satisfied with the Human Data Model.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom