eCite Digital Repository

Excemplify: a flexible template based solution, parsing and managing data in spreadsheets for experimentalists


Shi, L and Jong, L and Wittig, U and Lucarelli, P and Stepath, M and Mueller, S and D'Alessandro, LA and Klingmuller, U and Muller, W, Excemplify: a flexible template based solution, parsing and managing data in spreadsheets for experimentalists, Journal of Integrative Bioinformatics, 10, (2) Article 220. ISSN 1613-4516 (2013) [Refereed Article]


Copyright Statement

Copyright 2013 The Authors Licenced under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)

DOI: doi:10.2390/biecoll-jib-2013-220


In systems biology, quantitative experimental data is the basis of building mathematical models. In most of the cases, they are stored in Excel files and hosted locally. To have a public database for collecting, retrieving and citing experimental raw data as well as experimental conditions is important for both experimentalists and modelers. However, the great effort needed in the data handling procedure and in the data submission procedure becomes the crucial limitation for experimentalists to contribute to a database, thereby impeding the database to deliver its benefit. Moreover, manual copy and paste operations which are commonly used in those procedures increase the chance of making mistakes. Excemplify, a web-based application, proposes a flexible and adaptable template-based solution to solve these problems. Comparing to the normal template based uploading approach, which is supported by some public databases, rather than predefining a format that is potentiall impractical, Excemplify allows users to create their own experiment-specific content templates in different experiment stages and to build corresponding knowledge bases for parsing. Utilizing the embedded knowledge of used templates, Excemplify is able to parse experimental data from the initial setup stage and generate following stages spreadsheets automatically. The proposed solution standardizes the flows of data traveling according to the standard procedures of applying the experiment, cuts down the amount of manual effort and reduces the chance of mistakes caused by manual data handling. In addition, it maintains the context of meta-data from the initial preparation manuscript and improves the data consistency. It interoperates and complements RightField and SEEK as well.

Item Details

Item Type:Refereed Article
Keywords:knowledge management, systems biology
Research Division:Information and Computing Sciences
Research Group:Software engineering
Research Field:Software engineering not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the biological sciences
UTAS Author:Jong, L (Dr Lenneke Jong)
ID Code:102658
Year Published:2013
Deposited By:IMAS Research and Education Centre
Deposited On:2015-09-02
Last Modified:2018-02-16
Downloads:192 View Download Statistics

Repository Staff Only: item control page