The value of Big Data in government: The case of 'smart cities'

The emergence of Big Data has added a new aspect to conceptualizing the use of digital technologies in the delivery of public services and for realizing digital governance. This article explores, via the ‘value-chain’ approach, the evolution of digital governance research, and aligns it with current developments associated with data analytics, often referred to as ‘Big Data’. In many ways, the current discourse around Big Data reiterates and repeats established commentaries within the eGovernment research community. This body of knowledge provides an opportunity to reflect on the ‘promise’ of Big Data, both in relation to service delivery and policy formulation. This includes, issues associated with the quality and reliability of data, from mixing public and private sector data, issues associated with the ownership of raw and manip- ulated data, and ethical issues concerning surveillance and privacy. These insights and the issues raised help assess the value of Big Data in government and smart city environments

Zapotec Language Activism And Talking Dictionaries

Online dictionaries have become a key tool for some indigenous communities to promote and preserve their languages, often in collaboration with linguists. They can provide a pathway for crossing the digital divide and for establishing a first-ever presence on the internet. Many questions around digital lexicography have been explored, although primarily in relation to large and well-resourced languages. Lexical projects on small and under-resourced languages can provide an opportunity to examine these questions from a different perspective and to raise new questions (Mosel, 2011). In this paper, linguists, technical experts, and Zapotec language activists, who have worked together in Mexico and the United States to create a multimedia platform to showcase and preserve lexical, cultural, and environmental knowledge, share their experience and insight in creating trilingual online Talking Dictionaries in several Zapotec languages. These dictionaries sit opposite from big data mining and illustrate the value of dictionary projects based on small corpora, including having the flexibility to make design decisions to maximize community impact and elevate the status of marginalized languages

VALUE CREATION THROUGH DATA TRACKING TECHNOLOGIES IN THE FOOTBALL INDUSTRY OBSTACLES AND DYSFUNCTIONAL EFFECTS

The use of Big Data has become an essential part of today’s business. Data is present wherever you turn your head, whether looking at new innovative business opportunities, optimization and automation of existing business models, or getting rid of old habits. Recently, different types of tracking technologies have been introduced in the professional football industry, which offers the coaches full insight into how far players run, where they run, their directional shift, pace, accelerations, and how often and how long the players stand still. This technology offers an opportunity to optimize the sporting conditions of the teams through digital transformation. By applying the framework ‘Multidimensional Value Categories’, this paper contributes to practice by suggesting how tracking technologies can contribute to business value in professional football organizations, and to theory, by identifying obstacles and dysfunctional effects related to this value creation

Evaluating the Impact of Data Placement to Spark and SciDB with an Earth Science Use Case

We investigate the impact of data placement for two Big Data technologies, Spark and SciDB, with a use case from Earth Science where data arrays are multidimensional. Simultaneously, this investigation provides an opportunity to evaluate the performance of the technologies involved. Two datastores, HDFS and Cassandra, are used with Spark for our comparison. It is found that Spark with Cassandra performs better than with HDFS, but SciDB performs better yet than Spark with either datastore. The investigation also underscores the value of having data aligned for the most common analysis scenarios in advance on a shared nothing architecture. Otherwise, repartitioning needs to be carried out on the fly, degrading overall performance

Competitiveness of Arabian gulf ports from shipping lines’ perspectives: Case of Sohar port in Oman

Purpose: The purpose of this article is to investigate the factors that encourage shipping lines to use port of Sohar, in Oman. Some selected factors were used to assess to what extent it affects the port choice from shipping lines companies’ perspective. These factors include infrastructure, hinterland, connectivity and port’s dues. Design/methodology/approach: for this study both quantitative and qualitative methodologies were used. Self-administered questionnaire used for collecting quantitative data while interviews were used to collect qualitative data. Secondary data was collected by reviewing academic literature and recent relevant articles and reports. Findings: Port of Sohar has a better opportunity to be the gateway of the Gulf Cooperation Council (GCC) States and all Cargo could have dropped in the port and transferred to other GCC States by road, rail and other transportation modes. This opportunity is gained by the strategic location of Sohar Port outside of the Strait of Hormuz. It can be concluded that port competitiveness can be improved through strategic location, improved hinterland conditions, port facilities, services cost, volume of cargo, connectivity to other ports and dwell time factor. Research limitations: The research was limited mainly by conducting it only at the port of Sohar because surrounding ports are too far away and it should involve more ports to gain comparative results. Limited number of stakeholders as Port Authority, Oman International Container Terminal (OICT) and shipping lines companies and agents is another limitation. Practical implications: The port can improve its competitive advantages and focus on the investigated factors. The government can also continue in working in the three big infrastructural projects; the new express roads, Sohar Airport and rail network connections with other GCC networks. Originality/value: the study used specific factors that expected to contribute to the shipping lines companies’ selection of ports in the gulf region. This could help the port to identify their competitive advantage and how they can use these competencies to improve their competitiveness in relation to other ports in the region.Peer Reviewe

Suggested Framework for Big Data Analysis of Enterprise Websites. A Case Study for Web Intelligence Network

[EN] Big Data gives an opportunity for the researchers and scholars to make surveys in various domains. In this paper we will concentrate on websites as a data source which can be used to provide lots of valuable information for enterprise statistics. In this field, Big Data allows to get various information, including the type of the enterprise (e-commerce etc.), whether the enterprise is present in social media, the frequency of updating the website etc. The main goal of the paper is to present what Big Data methods are the most efficient in acquiring and processing the information from websites. The discussion shows different variants of conducting the work, based on the case studies conducted as experimental statistics at European Union level over the last 6 years. This paper is based on the experience in processing the data from websites in ESSnet grants on Big Data I (2016-2018), Big Data II (2018-2020) and Web Intelligence Network (2021-2025). The process of getting enterprise data from websites can be divided into the following steps: (1) Defining the population of enterprise websites; (2) Web scraping; (3) Data processing (extracting); (4) Data validation (de-duplication, quality indicators); (5) Data analysis; (6) Data dissemination. Each of the steps needs additional validation, especially the first step in this process have an impact on the final results that may not be comparable to the official statistical data. The essential part is also the way the data will be extracted to find the interesting data. In this sense, we need to choose between text mining methods, e.g. machine learning and regular expressions, that gives different results according to the information which should be provided. The paper shows how the use of appropriate methods can increase the overall value of the analysis.Maślankowski, J.; Nowak, D. (2022). Suggested Framework for Big Data Analysis of Enterprise Websites. A Case Study for Web Intelligence Network. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 270-270. http://hdl.handle.net/10251/18971027027

Empirical Study on Big Data Analysis for Supply Chain Management

with globalization, outsourcing is reaching beyond continents. Design is done in one part of the world, manufacturing in another low-cost country and distribution to other countries in the world. Procurement is illuming as a central focus that requires to be synchronized with all other business functions. As a matter of course, a sizeable amount of a firm’s revenue goes for its supply chain that interprets the significance of the supply chain lays in a firm’s bottom-line. So, the supply chain has a tremendous opportunity to get used of data. Nowadays, the supply chain is attracting much and more attention because in terms of analytics it is behind other functions of a firm.  Specifically, this paper will (1) redefine, by research on scientific work, what BDA means in the context of Supply Chain Management, and how it differs and has evolved from analytics technologies; (2) evolve taxonomy of Big Data within SCM that identifies and classifies the different sources and types of data arising in modern supply chains and (3) suggest some applications of BDA and show the potential high value of this technology offers to solve intricate SCM challenges.  This research tries to explore how the behavior of Big Data can succor procurement and SCM in greater decision making. Big data can be a lightening of a resilient environment while managing suppliers in global SCM is a challenging task. Another studied aspect is having access to a greater pool of data and what kind of potential data can render benefit SCM. SCM professionals were interviewed to understand what they expect from their logistics, procurement and marketing systems and how Big Data can contribute to that. What type of transparency is needed? What requires to be automated? What delineation of data is useful? Furthermore, how Big Data can help with SCM risk management

Peranan Koperasi Dalam Pengembangan Sistem Agribisnis Kakao (Studi Kasus: Koperasi Perkebunan Kakao Bireuen)

There is still great potential for the development of cocoa plants in Kabupaten Bireuen is a great opportunity to improve cocoa agribusiness in a sustainable, one of them is through institutional roles. However, the Kabupaten Bireuen government still has several problems in running the cocoa agribusiness system starting from the upstream subsystem to support services. Problems in the upstream subsystem and farming, namely farmers have not been able to fully implement the frequent harvest system, pruning, sanitizing and fertilizing (PsPSP) as well as fermentation. Even though the Bireuen Cocoa Plantation Cooperative has provided trainings related to the PsPSP system and the fermentation. This study aims to determine the cocoa agribusiness system in Kabupaten Bireuen and to find out the role of the Cocoa Plantation Cooperative that has been carried out so far. The sample criteria in this study were 34 cocoa farmers who were active members of the Bireuen Cocoa Plantation Cooperative. Data analysis in this study used a qualitative descriptive method with data measurement using a Likert scale.  The  results  showed  that  the  cocoa  agribusiness  system  in  Kabupaten Bireuennot well integrated, while in general the role of cooperatives in the development  of  the  cocoa  agribusiness  system  is  large  with  an  index  value  of 69.92%.The role of cooperatives in aid distribution activities is categorized as large with an index value of 73.94%,training activities have a big role with the category 79.65%, mentoring activities have a big role with an index value of 67.12% and the collection of results has a small role with an index value of 58.97%