Best Practices and Techniques in Building Data-Driven Websites

2013 ◽  
pp. 215-234
Author(s):  
Sandeep Chanda ◽  
Damien Foggon
Keyword(s):  
Best Practices ◽  
Data Driven

The vigorous development of data driven astronomy education and public outreach (DAEPO)

2019 ◽  
Vol 15 (S367) ◽  
pp. 199-209
Author(s):  
Shanshan Li ◽  
Chenzhou Cui ◽  
Cuilan Qiao ◽  
Dongwei Fan ◽  
Changhua Li ◽  
...  
Keyword(s):  
Best Practices ◽  
Rapid Evolution ◽  
Internet Technology ◽  
Data Driven ◽  
Public Outreach ◽  
Continuous Change ◽  
Astronomy Education ◽  
The Past ◽  
Education And Public Outreach ◽  
Science Educators

AbstractAstronomy education and public outreach (EPO) is one of the important part of the future development of astronomy. During the past few years, as the rapid evolution of Internet and the continuous change of policy, the breeding environment of science EPO keep improving and the number of related projects show a booming trend. EPO is no longer just a matter of to teachers and science educators but also attracted the attention of professional astronomers. Among all activates of astronomy EPO, the data driven astronomy education and public outreach (abbreviated as DAEPO) is special and important. It benefits from the development of Big Data and Internet technology and is full of flexibility and diversity. We will present the history, definition, best practices and prospective development of DAEPO for better understanding this active field.

scholarly journals A New Digital Approach to Strategic Activities

2020 ◽  
Vol 1 (2) ◽  
pp. 12-24
Author(s):  
Paolo Bongarzoni
Keyword(s):  
Best Practices ◽  
Return On Investment ◽  
Business Performance ◽  
Digital Technologies ◽  
Data Driven ◽  
Business Growth ◽  
Management Consultants ◽  
Strategy Process ◽  
High Return ◽  
Time Savings

As automation increasingly influences businesses, digitalization technologies and tools such as artificial intelligence, machine learning, etc., become essential to support the definition and implementation of strategy activities aimed at improving businesses' competitiveness in the digital, cloud-based, and data-driven world. Since this business growth corresponds to an enormous increase in the data volumes, it is fundamental for businesses to adopt several digital solutions in their strategy process together with a tailored digital strategy embedded in their strategic plan. The purpose of this article is to critically analyse the classic strategy activities' latest trends/needs and how they could be properly addressed by the available digital technologies. Finally, for every activity are mentioned some best practices tools and software, supported by management consultants, since they trigger a high return on investment in term of the time savings, less dedicated resources, and final business performance.

scholarly journals Automated Framework for Developing Predictive Machine Learning Models for Data-Driven Drug Discovery

2020 ◽  
Author(s):  
Bruno J. Neves ◽  
José T. Moreira-Filho ◽  
Arthur C. Silva ◽  
Joyce V. V. B. Borba ◽  
Melina Mottin ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Best Practices ◽  
Chemical Space ◽  
Biological Data ◽  
Data Driven ◽  
Learning Models ◽  
Structure Activity ◽  
Research Problems ◽  
Qsar Models ◽  
Machine Learning Models

In this manuscript we describe the development of an automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KNIME software. The workflow includes four modules: (i) dataset preparation and curation; (ii) chemical space analysis and structure-activity relationships (SAR) rules; (iii) modeling; and (iv) virtual screening (VS). As case studies, we applied these workflows to four datasets associated with different endpoints. The implemented protocol can efficiently curate chemical and biological data in public databases and generates robust QSAR models. We provide scientists a simple and guided cheminformatics workbench following the best practices widely accepted by the community, in which scientists can adapt to solve their research problems. The workflows are freely available for download in GitHub.

scholarly journals Practices and Infrastructures for ML Systems – An Interview Study

2021 ◽  
Author(s):  
Dennis Muiruri ◽  
Lucy Ellen Lwakatare ◽  
Jukka K. Nurminen ◽  
Tommi Mikkonen
Keyword(s):  
Machine Learning ◽  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Interview Study ◽  
The State ◽  
Data Driven ◽  
Software Systems ◽  
State Of Practice ◽  
Model Training

<div> <div> <div> <p>The best practices and infrastructures for developing and maintaining machine learning (ML) enabled software systems are often reported by large and experienced data-driven organizations. However, little is known about the state of practice across other organizations. Using interviews, we investigated practices and tool-chains for ML-enabled systems from 16 organizations in various domains. Our study makes three broad observations related to data management practices, monitoring practices and automation practices in ML model training, and serving workflows. These have limited number of generic practices and tools applicable across organizations in different domains. </p> </div> </div> </div>

Best Practices for Engaging Underserved Populations

2017 ◽  
Vol 61 (1) ◽  
pp. 130-134 ◽  
Author(s):  
Jacklin Stonewall ◽  
Katherine Fjelstad ◽  
Michael Dorneich ◽  
Linda Shenk ◽  
Caroline Krejci ◽  
...  
Keyword(s):  
Best Practices ◽  
Underserved Populations ◽  
Simulation Models ◽  
Community Planning ◽  
Research Topic ◽  
Data Driven ◽  
Cultural Norms ◽  
Urban Residents ◽  
Marginalized Populations ◽  
Disadvantaged Community

This work developed and applied a set of “best practices” when engaging marginalized populations to collect data, attitudes, and opinions around a research topic. To support city stakeholders making decisions to create more sustainable and equitable cities, data-driven simulation models are being developed. To ensure that these models are equitable, the needs of marginalized populations must be included. The challenge, however, in understanding these needs is that researchers have often struggled to reach and engage underserved populations. The best practices were developed by reviewing the literature from areas such as psychology, communication, and community planning. These best practices (Earn Trust Through Partnership, Be Multilingual & Inclusive, Communicate for Understanding, Respect Work Schedules and Cultural Norms, and Offer Something Useful) were then applied to the design of a data collection exercise for the study of weatherization decision making and behaviors of urban residents in an economically disadvantaged community. The results of the process were positive with high levels of participation and engagement. The use of the best practices allowed the researchers to better engage with the population, to the benefit of both groups. The development of these best practices will aid researchers in better engaging underserved populations across many areas of study.

Evidence-Based Guidelines for Management of Diabetic Macular Edema

2019 ◽  
Vol 3 (3) ◽  
pp. 145-152 ◽  
Author(s):  
Sophie J. Bakri ◽  
Jeremy D. Wolfe ◽  
Carl D. Regillo ◽  
Harry W. Flynn ◽  
Charles C. Wykoff
Keyword(s):  
Best Practices ◽  
Macular Edema ◽  
Diabetic Macular Edema ◽  
Disease Process ◽  
Underlying Disease ◽  
Data Driven ◽  
Microvascular Damage ◽  
Management Approaches ◽  
Perceived Relevance ◽  
Evidence Based Guidelines

Purpose: The purpose of this article is to provide a data-driven set of best practices to consider in the management of diabetic macular edema (DME). Methods: The current discussion and recommendations represent the authors’ interpretations of data from selected references based on perceived relevance and study design. Results: DME is a common cause of visual impairment globally. The underlying progressive retinal microvascular damage is associated with upregulation of VEGF and a multitude of other inflammatory pathways. Three clinically relevant subcategories of DME can be identified: central-involved DME (CIDME) with preserved visual acuity, CIDME with associated visual loss, and non-CIDME. Management approaches may include observation, laser photocoagulation, intravitreal pharmacotherapy with anti-VEGF agents or corticosteroids, or a combination of these, and may vary depending on the specific type of DME and associated severity of diabetic retinopathy. Additional factors to consider in the management of patients with DME include the appropriate use of imaging and recognition of the chronic nature of the underlying disease process in many eyes. Conclusions: DME management is complex. Intravitreal pharmacotherapies are the current cornerstone of treatment for CIDME and appear poised to remain so for the foreseeable future.

Optimising Well Times Through Drilling Connection Practices

2021 ◽  
Author(s):  
Faisal Mohd Mazlan ◽  
Ahmad Zhafran Ahmad Redzuan ◽  
Mohd Idzwan Amiruddin ◽  
Ahmad Faizal Ramli ◽  
Pete Slagel ◽  
...  
Keyword(s):  
Best Practices ◽  
Significant Risk ◽  
Data Driven ◽  
Drilling Performance ◽  
Change In Practice ◽  
Data Driven Approach ◽  
Drilling Operations ◽  
Historical Databases ◽  
Additional Costs ◽  
Time Savings

Abstract From an operator's perspective, many operational instructions are written implicitly that are not sufficiently detailed to optimize drilling efficiency. Upon a review of several partner operators’ drilling performance, it was noticed that there was a significant focus on the following aspects of technical limit drilling: ROP, tripping speeds, offline activities and connection times. One operator specifically reviewed Gulf-of-Thailand best practices and implemented them in Malaysia. One of the significant areas of improvement includes drilling connections. In the previous version, PETRONAS Malaysia Drilling Operations follows a conservative ERD connection method requiring to ream a single/stand, take a good survey a minimum 10m off bottom prior to making a connection and applied to all wells regardless of inclination or complexity. This was in response to risk of stuck pipe incidents happening during these critical static periods. A comparison of the connection times after their change in practice compared to PCSB practices given the same tools and well complexity indicated massive potential time savings with no additional costs. A change in the drilling connection practices could easily save almost half of this particular "flat time" with no significant risk, amounting to a possible saving of almost 26 hours in a well of around 3000m MDDF. This also led to a better understanding of the impacts of certain "rule-of-thumb" practices that needed to be questioned from time to time. This comparison coupled with many existing literatures available allowed a data-driven approach to improving well times. Some of this information is easily glossed over considering the only time-based data most wells refer to would be the Daily Drilling Report. This paper also emphasizes the importance of data collection and usage of historical databases to search for more opportunities in terms of safety, cost and time.

An Examination of Organization Learning and Data Driven Decision Making within Two University Enrollment Management Programs

2021 ◽  
Vol 8 (4) ◽  
pp. 150-168
Author(s):  
Barbara N Martin ◽  
J. D. Gragg
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Organizational Learning ◽  
Best Practices ◽  
Enrollment Management ◽  
Effective Means ◽  
Data Driven ◽  
Organization Learning ◽  
Data Driven Decision Making ◽  
Effective Strategies

This paper investigated the declining number of students in higher education institutions, and the effective strategies universities can use to recruit students who will graduate. From this research, it appeared that data-driven decision-making can be an effective means to create a successful enrollment management office. Through a practice of data-driven decision-making, organizational learning can happen, which will allow an organization to maintain success and build a culture that sustains that success. Three key themes emerged from the research that will help to inform best practices for other colleges and universities to implement ideas from this research. The three themes are: an organization must have good, usable data; an organization should strive to create a culture of teamwork to sustain success, and an organization needs a successful enrollment leader.

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