scholarly journals Array programming with NumPy

Nature ◽  
2020 ◽  
Vol 585 (7825) ◽  
pp. 357-362 ◽  
Author(s):  
Charles R. Harris ◽  
K. Jarrod Millman ◽  
Stéfan J. van der Walt ◽  
Ralf Gommers ◽  
Pauli Virtanen ◽  
...  
Keyword(s):  
Materials Science ◽  
Application Programming Interface ◽  
Scientific Data ◽  
Central Position ◽  
Python Language ◽  
Programming Library ◽  
Higher Dimensional ◽  
Application Programming ◽  
Flexible Framework ◽  
Research Analysis

AbstractArray programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

Leveraging Web 2.0 technologies to add value to the IUPAC Solubility Data Series: development of a REST style website and application programming interface (API)

2015 ◽  
Vol 87 (11-12) ◽  
pp. 1127-1137
Author(s):  
Stuart J. Chalk
Keyword(s):  
Application Programming Interface ◽  
Scientific Data ◽  
Lessons Learned ◽  
Data Series ◽  
Representational State Transfer ◽  
Database Construction ◽  
Series Development ◽  
Application Programming ◽  
Rest Api ◽  
Program Interface

AbstractThis paper details an approach to re-purposing scientific data as presented on a web page for the sole purpose of making the data more available for searching and integration into other websites. Data ‘scraping’ is used to extract metadata from a set of pages on the National Institute of Standards and Technology (NIST) website, clean, organize and store the metadata in a MySQL database. The metadata is then used to create a new website at the authors institution using the CakePHP framework to create a representational state transfer (REST) style application program interface (API). The processes used for website analysis, schema development, database construction, metadata scraping, REST API development, and remote data integration are discussed. Lessons learned and tips and tricks on how to get the most out of the process are also included.

scholarly journals KIST-NOMAD - a Repository to Manage Large Amounts of Computational Materials Science Data

2020 ◽  
Vol 58 (10) ◽  
pp. 728-739
Author(s):  
Samuel Boateng ◽  
Kwang Ryeol Lee ◽  
Deepika ◽  
Haneol Cho ◽  
Kyu Hwan Lee ◽  
...  
Keyword(s):  
Large Scale ◽  
Materials Science ◽  
Application Programming Interface ◽  
Scientific Data ◽  
Dynamics Simulation ◽  
Data Repository ◽  
Science Data ◽  
Front End ◽  
Computational Material ◽  
Efficient Option

We introduce the Korea Institute of Science and Technology-Novel Materials Discovery (KISTNOMAD) platform, a materials data repository. We describe its functionality and novel features from an academic viewpoint. It is a data repository designed for computational material science, especially focusing on managing and sharing the results of molecular dynamics simulation results as well as quantum mechanical computations. It consists of three main components: a database, file storage, and web-based front end. The database hosts material properties, which are extracted from the computational results. The front end has a graphical user interface and an open application programming interface, which allow researchers to interact with the system more easily. KIST-NOMAD’s panel displays the searched results on a well-organized and research-oriented web page. All the open access data and files are available for downloading in comma-separated value format as well as zipped archives. This automated extraction function was developed by utilizing database parsers and JSON scripts. KISTNOMAD also has an efficient option to download simulation and computation results on a large-scale. All of the above functions are designed to satisfy academic and research demands, and make highthroughput screening available, while incorporating machine learning for computational material engineering. We finally stress that the repository platform is user-driven and user-friendly. It is clearly designed to follow the modern big-data architecture and re-use principles for scientific data, such as being findable, accessible, and interoperable.

scholarly journals Lightweight data management with dtool

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6562 ◽  
Author(s):  
Tjelvar S.G. Olsson ◽  
Matthew Hartley
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Application Programming Interface ◽  
Scientific Data ◽  
Consistency Checking ◽  
Peace Of Mind ◽  
Command Line Tool ◽  
Application Programming ◽  
High Level ◽  
Storage Technologies

The explosion in volumes and types of data has led to substantial challenges in data management. These challenges are often faced by front-line researchers who are already dealing with rapidly changing technologies and have limited time to devote to data management. There are good high-level guidelines for managing and processing scientific data. However, there is a lack of simple, practical tools to implement these guidelines. This is particularly problematic in a highly distributed research environment where needs differ substantially from group to group and centralised solutions are difficult to implement and storage technologies change rapidly. To meet these challenges we have developed dtool, a command line tool for managing data. The tool packages data and metadata into a unified whole, which we call a dataset. The dataset provides consistency checking and the ability to access metadata for both the whole dataset and individual files. The tool can store these datasets on several different storage systems, including a traditional file system, object store (S3 and Azure) and iRODS. It includes an application programming interface that can be used to incorporate it into existing pipelines and workflows. The tool has provided substantial process, cost, and peace-of-mind benefits to our data management practices and we want to share these benefits. The tool is open source and available freely online at http://dtool.readthedocs.io.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

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