The role of domain analysis in prediction instrument development

Research output: Contribution to conferencePaperAcademic

28 Downloads (Pure)

Abstract

In order to develop prediction instruments that have sufficient predictive power, it is essential to understand the specific domain the prediction instrument is developed for. This domain analysis is especially important for domains where human behavior, politics, or other soft factors play a role. If these are not well understood, the predictive power of the prediction instrument would be severely affected. In this paper, we provide literature based reasons for the use of domain analysis for the development of prediction instruments, and we discuss the circumstances under which domain analysis is especially important. We present a structured literature review of the actual adoption of domain analysis for predictive analytics. That shows that few papers discuss how domain analysis was performed, and when it is discussed, the type of analysis often does not fit with the type of domain. As these papers do show adequate predictive power, we believe that the domain analysis in these papers was done implicitly. To make the process of prediction instrument development, including domain analysis more transparent, we present requirements for a method for prediction instrument development , and an outline for such a method based on those requirements.
Original languageEnglish
Number of pages10
Publication statusPublished - 29 Mar 2016
EventBig Data Interoperability for Enterprises (BDI4E) Workshop 2016 - Guimarães, Portugal
Duration: 29 Mar 201630 Mar 2016

Conference

ConferenceBig Data Interoperability for Enterprises (BDI4E) Workshop 2016
Abbreviated titleBDI4E
CountryPortugal
CityGuimarães
Period29/03/1630/03/16

Fingerprint

Predictive analytics

Keywords

  • METIS-318962
  • IR-102152

Cite this

van der Spoel, S., Amrit, C. A., & van Hillegersberg, J. (2016). The role of domain analysis in prediction instrument development. Paper presented at Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, Guimarães, Portugal.
van der Spoel, Sjoerd ; Amrit, Chintan Amrit ; van Hillegersberg, Jos. / The role of domain analysis in prediction instrument development. Paper presented at Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, Guimarães, Portugal.10 p.
@conference{9d5e30af497243468d9aa958281ded4c,
title = "The role of domain analysis in prediction instrument development",
abstract = "In order to develop prediction instruments that have sufficient predictive power, it is essential to understand the specific domain the prediction instrument is developed for. This domain analysis is especially important for domains where human behavior, politics, or other soft factors play a role. If these are not well understood, the predictive power of the prediction instrument would be severely affected. In this paper, we provide literature based reasons for the use of domain analysis for the development of prediction instruments, and we discuss the circumstances under which domain analysis is especially important. We present a structured literature review of the actual adoption of domain analysis for predictive analytics. That shows that few papers discuss how domain analysis was performed, and when it is discussed, the type of analysis often does not fit with the type of domain. As these papers do show adequate predictive power, we believe that the domain analysis in these papers was done implicitly. To make the process of prediction instrument development, including domain analysis more transparent, we present requirements for a method for prediction instrument development , and an outline for such a method based on those requirements.",
keywords = "METIS-318962, IR-102152",
author = "{van der Spoel}, Sjoerd and Amrit, {Chintan Amrit} and {van Hillegersberg}, Jos",
year = "2016",
month = "3",
day = "29",
language = "English",
note = "Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, BDI4E ; Conference date: 29-03-2016 Through 30-03-2016",

}

van der Spoel, S, Amrit, CA & van Hillegersberg, J 2016, 'The role of domain analysis in prediction instrument development' Paper presented at Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, Guimarães, Portugal, 29/03/16 - 30/03/16, .

The role of domain analysis in prediction instrument development. / van der Spoel, Sjoerd; Amrit, Chintan Amrit; van Hillegersberg, Jos.

2016. Paper presented at Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, Guimarães, Portugal.

Research output: Contribution to conferencePaperAcademic

TY - CONF

T1 - The role of domain analysis in prediction instrument development

AU - van der Spoel, Sjoerd

AU - Amrit, Chintan Amrit

AU - van Hillegersberg, Jos

PY - 2016/3/29

Y1 - 2016/3/29

N2 - In order to develop prediction instruments that have sufficient predictive power, it is essential to understand the specific domain the prediction instrument is developed for. This domain analysis is especially important for domains where human behavior, politics, or other soft factors play a role. If these are not well understood, the predictive power of the prediction instrument would be severely affected. In this paper, we provide literature based reasons for the use of domain analysis for the development of prediction instruments, and we discuss the circumstances under which domain analysis is especially important. We present a structured literature review of the actual adoption of domain analysis for predictive analytics. That shows that few papers discuss how domain analysis was performed, and when it is discussed, the type of analysis often does not fit with the type of domain. As these papers do show adequate predictive power, we believe that the domain analysis in these papers was done implicitly. To make the process of prediction instrument development, including domain analysis more transparent, we present requirements for a method for prediction instrument development , and an outline for such a method based on those requirements.

AB - In order to develop prediction instruments that have sufficient predictive power, it is essential to understand the specific domain the prediction instrument is developed for. This domain analysis is especially important for domains where human behavior, politics, or other soft factors play a role. If these are not well understood, the predictive power of the prediction instrument would be severely affected. In this paper, we provide literature based reasons for the use of domain analysis for the development of prediction instruments, and we discuss the circumstances under which domain analysis is especially important. We present a structured literature review of the actual adoption of domain analysis for predictive analytics. That shows that few papers discuss how domain analysis was performed, and when it is discussed, the type of analysis often does not fit with the type of domain. As these papers do show adequate predictive power, we believe that the domain analysis in these papers was done implicitly. To make the process of prediction instrument development, including domain analysis more transparent, we present requirements for a method for prediction instrument development , and an outline for such a method based on those requirements.

KW - METIS-318962

KW - IR-102152

M3 - Paper

ER -

van der Spoel S, Amrit CA, van Hillegersberg J. The role of domain analysis in prediction instrument development. 2016. Paper presented at Big Data Interoperability for Enterprises (BDI4E) Workshop 2016, Guimarães, Portugal.