scholarly journals Time to change the data culture in geochemistry

2021 ◽  
Author(s):  
Katy J. Chamberlain ◽  
Kerstin A. Lehnert ◽  
Iona M. McIntosh ◽  
Dan J. Morgan ◽  
Gerhard Wörner
Keyword(s):  
Data Culture

Rasch Validation and Cross-Validation of the Health of Nation Outcome Scales for Monitoring of Psychiatric Disability in Traumatized Refugees in Western Psychiatric Care

Assessment ◽  
2016 ◽  
Vol 23 (6) ◽  
pp. 734-743 ◽  
Author(s):  
Sabina Palic ◽  
Michelle Lind Kappel ◽  
Guido Makransky
Keyword(s):  
Rasch Analysis ◽  
Cross Validation ◽  
Psychiatric Care ◽  
Psychiatric Disability ◽  
Psychiatric Clinic ◽  
Treatment Needs ◽  
Validation Data ◽  
Group A ◽  
Data Culture ◽  
The Rasch Model

There are no validated measures of psychiatric disability for traumatized refugees in Western psychiatric care. This is a serious shortcoming as it precludes monitoring of global treatment outcomes in this group, as well as appropriate matching of treatment needs to the disability levels. Using Rasch analysis, we evaluated the psychometrics of the Health of Nation Outcome Scales (HoNOS) in pretreatment data of consecutive refugee patients ( N = 448) from a Danish psychiatric clinic. Then, we carried out a cross-validation of the pretreatment HoNOS model on posttreatment data from the same group. A revised 10-item HoNOS fit the Rasch model at pretreatment and also showed excellent fit within the cross-validation data. Culture, gender, and need for translation did not exert serious bias on the measure’s performance. The results establish good monitoring properties of the 10-item HoNOS as the first validated measure of psychiatric disability for traumatized refugees in Western psychiatric care.

scholarly journals The data epic : Visualization practices for narrating life and death at a distance

2020 ◽  
Author(s):  
Jonathan Gray
Keyword(s):  
World War Ii ◽  
Data Visualization ◽  
World War ◽  
Nuclear Threat ◽  
Life And Death ◽  
Public Data ◽  
Data Culture

This chapter proposes the notion of the ‘data epic’, which is examined through two works of ‘cinematic data visualization’: The Fallen of World War II and The Shadow Peace: The Nuclear Threat. These pieces mobilize an aesthetics of distance to narrate life and death at scale, in past and possible global conflicts. While previous studies of quantification emphasize the function of distance in relation to aspirations of objectivity, this chapter explores other narrative and affective capacities of distance in the context of ‘public data culture’. The data epic can thus enrich understanding of how data are rendered meaningful for various publics, as well as the entanglement of data aesthetics and data politics involved in visualization practices for picturing collective life.

Data Journalism’s Ties With Civic Tech

2021 ◽  
Author(s):  
Stefan Baack
Keyword(s):  
Data Journalism ◽  
Data Culture

How data journalism overlaps with other forms of data work and data culture.

scholarly journals From a Smoking Gun to Spent Fuel: Principled Subsampling Methods for Building Big Language Data Corpora from Monitor Corpora

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 48 ◽  
Author(s):  
Jacqueline Tidwell
Keyword(s):  
Data Collection ◽  
Sampling Method ◽  
Evaluation Process ◽  
Spent Fuel ◽  
Social Scientists ◽  
Multiple Sampling ◽  
Language Data ◽  
Representative Model ◽  
Data Culture ◽  
Final Text

With the influence of Big Data culture on qualitative data collection, acquisition, and processing, it is becoming increasingly important that social scientists understand the complexity underlying data collection and the resulting models and analyses. Systematic approaches for creating computationally tractable models need to be employed in order to create representative, specialized reference corpora subsampled from Big Language Data sources. Even more importantly, any such method must be tested and vetted for its reproducibility and consistency in generating a representative model of a particular population in question. This article considers and tests one such method for Big Language Data downsampling of digitally accessible language data to determine both how to operationalize this form of corpus model creation, as well as testing whether the method is reproducible. Using the U.S. Nuclear Regulatory Commission’s public documentation database as a test source, the sampling method’s procedure was evaluated to assess variation in the rate of which documents were deemed fit for inclusion or exclusion from the corpus across four iterations. After performing multiple sampling iterations, the approach pioneered by the Tobacco Documents Corpus creators was deemed to be reproducible and valid using a two-proportion z-test at a 99% confidence interval at each stage of the evaluation process–leading to a final mean rejection ratio of 23.5875 and variance of 0.891 for the documents sampled and evaluated for inclusion into the final text-based model. The findings of this study indicate that such a principled sampling method is viable, thus necessitating the need for an approach for creating language-based models that account for extralinguistic factors and linguistic characteristics of documents.

Book review: Biruk, C. 2018: Cooking Data: Culture and Politics in an African Research World

2020 ◽  
Vol 20 (1) ◽  
pp. 86-88
Author(s):  
Natasha S.K.
Keyword(s):  
Duke University ◽  
Data Culture ◽  
Research World

Biruk, C. 2018: Cooking Data: Culture and Politics in an African Research World. Durham and London: Duke University Press. 277 pp. $26.95. ISBN: 9780822370895.

scholarly journals Incremental Innovation towards Business Performance: Data Management Challenges in Healthcare Industry in Indonesia

2018 ◽  
Vol 218 ◽  
pp. 04015 ◽  
Author(s):  
Muharman Lubis ◽  
Lubis Arif Ridho ◽  
Bastian Lubis ◽  
Asmin Lubis
Keyword(s):  
Data Management ◽  
Business Performance ◽  
New Technology ◽  
Incremental Innovation ◽  
Quality Data ◽  
Data Handling ◽  
Data Ownership ◽  
Fragmented Data ◽  
Data Culture ◽  
Business Flow

The Industry 4.0 indicate the increases in competitive pressures, the margins reduction, the availability of new technology and the marketing development techniques suggest making more complex decisions to make and sustain the success. Data management is essential for organizations because the administrative process, which data is acquired, validated, stored, protected and processed through its accessibility, reliability and timeliness ensures that the needs of data are met. It is also a process of developing data architectures, practices and procedures that address the data and then implement these aspects on a regular basis. All these process will ease and smoothen the business flow. Therefore, there are number of data management challenges to maintain sheer volume of data, taking reactive approach, lack of process and data handling, fragmented data ownership and driving a data culture. This study investigate the current issues in health industry to overcome through recognizing both the importance of quality data and having more sophisticated approach to manage data as the organization begin shifting to be more data centric model.

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