scholarly journals Applying Design Thinking in Revising Data Curation of Taiwanese Herbaria

2018 ◽  
Vol 2 ◽  
pp. e25828
Author(s):  
Chihjen Ko ◽  
Lex Wang

Herbaria in Taiwan face critical data challenges: Different taxonomic views prevent data exchange; There is a lack of development practices to keep up with standard and technological advances; Data is disconnected from researchers’ perspective, thus it is difficult to demonstrate the value of taxonomists’ activities, even though a few herbaria have their specimen catalogue partially exposed in Darwin Core. Different taxonomic views prevent data exchange; There is a lack of development practices to keep up with standard and technological advances; Data is disconnected from researchers’ perspective, thus it is difficult to demonstrate the value of taxonomists’ activities, even though a few herbaria have their specimen catalogue partially exposed in Darwin Core. In consultation with the Herbarium of the Taiwan Forestry Research Institute (TAIF), the Herbarium of the National Taiwan University (TAI) and the Herbarium of the Biodiversity Research Center, Academia Sinica (HAST), which together host most important collections of the vegetation on the island, we have planned the following activities to address data challenges: Investigate a new data model for scientific names that will accommodate different taxonomic views and create a web service for access to taxonomic data; Refactor existing herbarium systems to utilize the aforementioned service so the three herbaria can share and maintain a standardized name database; Create a layer of Application Programming Interface (API) to allow multiple types of accessing devices; Conduct behavioral research regarding various personas engaged in the curatorial workflow; Create a unified front-end that supports data management, data discovery, and data analysis activities with user experience improvements. Investigate a new data model for scientific names that will accommodate different taxonomic views and create a web service for access to taxonomic data; Refactor existing herbarium systems to utilize the aforementioned service so the three herbaria can share and maintain a standardized name database; Create a layer of Application Programming Interface (API) to allow multiple types of accessing devices; Conduct behavioral research regarding various personas engaged in the curatorial workflow; Create a unified front-end that supports data management, data discovery, and data analysis activities with user experience improvements. To manage these developments at various levels, while maximizing the contribution of participating parties, it is crucial to use a proven methodological framework. As the creative industry has been leading in the area of solution development, the concept of design thinking and design thinking process (Brown and Katz 2009) has come to our radar. Design thinking is a systematic approach to handling problems and generating new opportunities (Pal 2016). From requirement capture to actual implementation, it helps consolidate ideas and identify agreed-on key priorities by constantly iterating through a series of interactive divergence and convergence steps, namely the following: Empathize: A divergent step. We learn about our audience, which in this case includes curators and visitors of the herbarium systems, about what they do and how they interact with the system, and collate our findings. Define: A convergent step. We construct a point of view based on audience needs. Ideate: A divergent step. We brainstorm and come up with creative solutions, which might be novel or based on existing practice. Prototype: A convergent step. We build representations of the chosen idea from the previous step. Test: Use the prototype to test whether the idea works. Then refine from step 3 if problems were with the prototyping, or even step 1, if the point of view needs to be revisited. Empathize: A divergent step. We learn about our audience, which in this case includes curators and visitors of the herbarium systems, about what they do and how they interact with the system, and collate our findings. Define: A convergent step. We construct a point of view based on audience needs. Ideate: A divergent step. We brainstorm and come up with creative solutions, which might be novel or based on existing practice. Prototype: A convergent step. We build representations of the chosen idea from the previous step. Test: Use the prototype to test whether the idea works. Then refine from step 3 if problems were with the prototyping, or even step 1, if the point of view needs to be revisited. The benefits by adapting to this process are: Instead of “design for you”, we “design together”, which strengthens the sense of community and helps the communication of what the revision and refactoring will achieve; When put in context, increased awareness and understanding of biodiversity data standards, such as Darwin Core (DwC) and Access to Biological Collections Data (ABCD); As we lend the responsibility of process control to an external facilitator, we are able to focus during each step as a participant. Instead of “design for you”, we “design together”, which strengthens the sense of community and helps the communication of what the revision and refactoring will achieve; When put in context, increased awareness and understanding of biodiversity data standards, such as Darwin Core (DwC) and Access to Biological Collections Data (ABCD); As we lend the responsibility of process control to an external facilitator, we are able to focus during each step as a participant. We illustrate how the planned activities are conducted by the five iterative steps.

2018 ◽  
Author(s):  
Alessandro Sanchez ◽  
Stephan Meylan ◽  
Mika Braginsky ◽  
Kyle Earl MacDonald ◽  
Daniel Yurovsky ◽  
...  

The Child Language Data Exchange System (CHILDES) has played a critical role in research on child language development, particularly in characterizing the early language learning environment. Access to these data can be both complex for novices and difficult to automate for advanced users, however. To address these issues, we introduce childes-db, a database-formatted mirror of CHILDES that improves data accessibility and usability by offering novel interfaces, including browsable web applications and an R application programming interface (API). Along with versioned infrastructure that facilitates reproducibility of past analyses, these interfaces lower barriers to analyzing naturalistic parent-child language, allowing for a wider range of researchers in language and cognitive development to easily leverage CHILDES in their work.


2014 ◽  
Vol 7 (3) ◽  
pp. 3595-3645 ◽  
Author(s):  
M. Bavay ◽  
T. Egger

Abstract. Using numerical models which require large meteorological data sets is sometimes difficult and problems can often be traced back to the Input/Output functionality. Complex models are usually developed by the environmental sciences community with a focus on the core modelling issues. As a consequence, the I/O routines that are costly to properly implement are often error-prone, lacking flexibility and robustness. With the increasing use of such models in operational applications, this situation ceases to be simply uncomfortable and becomes a major issue. The MeteoIO library has been designed for the specific needs of numerical models that require meteorological data. The whole task of data preprocessing has been delegated to this library, namely retrieving, filtering and resampling the data if necessary as well as providing spatial interpolations and parametrizations. The focus has been to design an Application Programming Interface (API) that (i) provides a uniform interface to meteorological data in the models; (ii) hides the complexity of the processing taking place; and (iii) guarantees a robust behaviour in case of format errors, erroneous or missing data. Moreover, in an operational context, this error handling should avoid unnecessary interruptions in the simulation process. A strong emphasis has been put on simplicity and modularity in order to make it extremely easy to support new data formats or protocols and to allow contributors with diverse backgrounds to participate. This library can also be used in the context of High Performance Computing in a parallel environment. Finally, it is released under an Open Source license and is available at http://models.slf.ch/p/meteoio. This paper gives an overview of the MeteoIO library from the point of view of conceptual design, architecture, features and computational performance. A scientific evaluation of the produced results is not given here since the scientific algorithms that are used have already been published elsewhere.


2020 ◽  
Vol 22 (3) ◽  
pp. 301-309
Author(s):  
Riovan Styx Roring

Implementation of technology that supports Society 5.0 needs to be done because the principal itself that focused towards technology implementation and not inclined emphasize to the technology development. Furthermore, 5.0 era also priotize technology implementation to all element of the society that could be used by diverse aspect in the community, such as: economics, education. Infrastructure, and community expertises. One of the support technology utilization is Costless Transportation Application Ojek GT base don Android Client and PHP: Hypertext Preporcessor (PHP) Web as server. This application designed using both of the platform above to fulfill the user’s need. Both of the platform are integrated using Application Programming Interface (API) as a data exchange medium to the database. The implementation of the software itself follows the Community Service Freedom Technology (CSFT) that designed as software development pattern which aims to push support technology utilization towards Society 5.0 era. In the future, this software is expected to be a simple of support technology utilization in Society 5.0 era that could be implemented to all the aspect in the community cope. Beside as a solution of costless technology utilization, Ojek GT could also be expected as Business Startup in the creative industry scope.


2020 ◽  
Vol 6 ◽  
pp. e302
Author(s):  
Olga Ogorodnyk ◽  
Mats Larsen ◽  
Ole Vidar Lyngstad ◽  
Kristian Martinsen

Injection molding is a complicated process, and the final part quality depends on many machine and process parameters settings. To increase controllability of the injection molding process, acquisition of the process data is necessary. This paper describes the architecture and development of a prototype of an open application programming interface (API) for injection molding machines (IMMs), which has the potential to be used with different IMMs to log and set the necessary process parameter values. At the moment, the API includes an implementation of EMI data exchange protocol and can be used with ENGEL IMMs with CC300 and RC300 controllers. Data collection of up to 97 machine and process parameters (the number might vary depending on the type of machine at hand), obtained from sensors installed in the machine by the manufacturer is allowed. The API also includes a module for the acquisition of data from additional 3d party sensors. Industrial Raspberry Pi (RevPi) was used to perform analog-to-digital signal conversion and make sensors data accessible via the API prototype. The logging of parameters from the machine and from sensors is synchronized and the sampling frequency can be adjusted if necessary. The system can provide soft real-time communication.


2019 ◽  
Vol 35 (20) ◽  
pp. 4147-4155 ◽  
Author(s):  
Peter Selby ◽  
Rafael Abbeloos ◽  
Jan Erik Backlund ◽  
Martin Basterrechea Salido ◽  
Guillaume Bauchet ◽  
...  

Abstract Motivation Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. Availability and implementation More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.


2021 ◽  
Author(s):  
Jan Range ◽  
Colin Halupczok ◽  
Jens Lohmann ◽  
Neil Swainston ◽  
Carsten Kettner ◽  
...  

EnzymeML is an XML–based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modelling tools, and databases. EnzymeML supports the scientific community by introducing a standardised data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An Application Programming Interface in Python and Java supports the integration of applications. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modelling using the modelling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.


10.2196/10725 ◽  
2018 ◽  
Vol 20 (7) ◽  
pp. e10725 ◽  
Author(s):  
Satchit Balsari ◽  
Alexander Fortenko ◽  
Joaquín A Blaya ◽  
Adrian Gropper ◽  
Malavika Jayaram ◽  
...  

2014 ◽  
Vol 7 (6) ◽  
pp. 3135-3151 ◽  
Author(s):  
M. Bavay ◽  
T. Egger

Abstract. Using numerical models which require large meteorological data sets is sometimes difficult and problems can often be traced back to the Input/Output functionality. Complex models are usually developed by the environmental sciences community with a focus on the core modelling issues. As a consequence, the I/O routines that are costly to properly implement are often error-prone, lacking flexibility and robustness. With the increasing use of such models in operational applications, this situation ceases to be simply uncomfortable and becomes a major issue. The MeteoIO library has been designed for the specific needs of numerical models that require meteorological data. The whole task of data preprocessing has been delegated to this library, namely retrieving, filtering and resampling the data if necessary as well as providing spatial interpolations and parameterizations. The focus has been to design an Application Programming Interface (API) that (i) provides a uniform interface to meteorological data in the models, (ii) hides the complexity of the processing taking place, and (iii) guarantees a robust behaviour in the case of format errors, erroneous or missing data. Moreover, in an operational context, this error handling should avoid unnecessary interruptions in the simulation process. A strong emphasis has been put on simplicity and modularity in order to make it extremely easy to support new data formats or protocols and to allow contributors with diverse backgrounds to participate. This library is also regularly evaluated for computing performance and further optimized where necessary. Finally, it is released under an Open Source license and is available at http://models.slf.ch/p/meteoio. This paper gives an overview of the MeteoIO library from the point of view of conceptual design, architecture, features and computational performance. A scientific evaluation of the produced results is not given here since the scientific algorithms that are used have already been published elsewhere.


2018 ◽  
Author(s):  
Satchit Balsari ◽  
Alexander Fortenko ◽  
Joaqu�n A. Blaya ◽  
Adrian Gropper ◽  
Malavika Jayaram ◽  
...  

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