3. Metodología
3.1 El sintetizador de Verbio Speech Technologies SL
Beside implementing the solutions to the usability problems we found in the summative evaluation (see Chapter 6, Section 6.7), we envision to conduct fu- ture research in the following directions:
• End-user development of physical mashups. The Internet of Things is a paradigm for the future Internet in which everyday objects are equipped with sensors and connected to the Internet. One of the emerging visions [15] corre- lated with this paradigm is the so called Web of Things [50]. The goal of this vision is to use Web standards and technologies to facilitate the connection and integration of everyday objects. Once these objects are exposed and accessible as Web APIs, they can be composed with other Web APIs that may or may not encapsulate physical objects. The resulting composition applications are called physical mashups [51] and provide added value across the Internet of Things. Physical mashups are similar to traditional Web mashups with the difference that they also compose physical Web APIs (i.e., Web APIs encapsulating physical objects). For example, a physical mashup can give insight into the efficiency of a home heating system by displaying weather information (e.g., from a weather Web API) alongside data from different sensors connected to the heating system. The development of physical mashups follows a long tail model, in which count- less situational and unique needs of users can drive the development of mashups. Therefore, EUD can be applied to enable the development of physical mashups in a “do-it-yourself” manner. So far, existing relevant studies have mainly focused on the engineering challenges, such as developing a unified interface for physical Web APIs[105] and designing a scalable architecture for the Web of Things [52].
114 8.2 Future Directions
We will build on these works and extend them if necessary. However, identifying and tackling the problem of self-service physical mashup development through an HCI perspective has previously received little research attention.
• Enterprise data integration using natural language programming. In the enterprise integration industry (e.g., Crossing Tech1), multiple actors such as business analysts, architects and developers are inevitably involved in the process of building an integration solution. These actors represent two groups known as functionals and technicals. There is a clear segregation between these two groups in terms of communication as they clearly don’t have the same exper- tise, don’t share the same goals and mostly don’t use the same terminologies. At the beginning of an integration project, the business analysts usually describe in a text document what they expect the solution to do and how the different enti- ties are going to be mediated. This business documentation is to be given to and analyzed by the architect to design an integration architecture. A new set of doc- umentation artifacts are created by the architect to describe in more details the diagram, the architecture and its components. This architecture documentation will then be provided to the developers who will implement the components. Nevertheless, the original business documentation is never delivered to the de- velopers. This situation often leads to misunderstandings as the communication gap is a serious issue between the business analysts and the developers.
This gap can be addressed through the lens of EUD. To be specific, we plan to study how to use a controlled natural language to model complex enterprise integration solutions, which are currently visualized using technical diagrams that seem to be difficult to understand for business users. The advantage of using an executable controlled natural language is that it is not only understandable by business users, but also as expressive as visual diagrams.
Usability Evaluation Forms
This appendix contains questionnaire forms used in the usability evaluations of NaturalMash: formative usability evaluation of iteration 2 (Chapter 5, Sec- tion 5.2), formative evaluation of iteration 3 (Chapter 5, Section 5.3), and sum- mative evaluation (Chapter 6).
A.1
Background Assessment Questionnaire
1. How often, if ever, do you use social networks (e.g., Facebook, Twitter,
Linkedin, etc.)?
Never 1 2 3 4 5 Very frequently
2. How often, if ever, do you check Web feeds, blogs, and podcasts? Never 1 2 3 4 5 Very frequently
3. Do you have a Website or blog? Yes
No
4. Which of the following services have you used? Flickr Facebook Twitter LinkedIn Last.fm 115
116 A.1 Background Assessment Questionnaire eBay Google Maps Google Search Google News Delicious Eventful BBC News SlideShare
5. How familiar are you with spreadsheet programs (e.g., Microsoft Ex-
cel)?
No familiarity 1 2 3 4 5 Expert
6. How familiar are you with editing wikis? (e.g., editing Wikipedia)? No familiarity 1 2 3 4 5 Expert
7. How familiar are you with Website builders? (e.g., WordPress, Wix,
Weebly, etc.)?
No familiarity 1 2 3 4 5 Expert 8. How familiar are you with HTML?
No familiarity 1 2 3 4 5 Expert
9. How familiar are you with XML?
No familiarity 1 2 3 4 5 Expert
10. How familiar are you with JavaScript? No familiarity 1 2 3 4 5 Expert
11. How familiar are you with Linux shell script? No familiarity 1 2 3 4 5 Expert
12. Please, write down the list of programming languages you speak.
13. Please indicate years of continuous experience in programming (the
learning period is also counted).
0-1 year 1-2 years 2-5 years 5-10 years 10+ years
14. Please indicate years of experience in industry (i.e., working as a de-
veloper in a company). 0-1 year 1-2 years 2-5 years 5-10 years 10+ years