----CrowdCorrect: A Curation Pipeline for Social Data Cleansing and Curationy-------------

Process and data are equally important for business process management. Data-driven approaches in process analytics aims to value decisions that can be backed up with verifiable private and open data. Over the last few years, data-driven analysis of how knowledge workers and customers interact in social contexts, often with data obtained from social networking services such as Twitter and Facebook, have become a vital asset for organizations. For example, governments started to extract knowledge and derive insights from vastly growing open data to improve their services. A key challenge in analyzing social data is to understand the raw data generated by social actors and prepare it for analytic tasks. In this context, it is important to transform the raw data into a contextualized data and knowledge. This task, known as data curation, involves identifying relevant data sources, extracting data and knowledge, cleansing, maintaining, merging, enriching and linking data and knowledge. To address thic challenge, we present CrowdCorrect, a data curation pipeline to enable analysts cleansing and curating social data and preparing it for reliable business data analytics.

DataSynapse Source: https://github.com/unsw-cse-soc/CrowdCorrect

Notice: We encourage researchers/developers to cite our paper if you have used our APIs, libraries, tools or datasets.

----License-----------------------

License: This software is licensed under the Apache 2.0 license, quoted below.

Copyright 2016 UNSW.CSE.SOC Research Group unsw.cse.soc@gmail.com

You may not use these APIs except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

----Contributors-----------------------

Amin Beheshti, Kushal Vaghani, Boualem Benatallah, Alireza Tabebordbar

-The University of New South Wales, Sydney, Australia.

-Macquarie University, Sydney, Australia