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There is no need to elaborate on the key position that petroleum has in our lives today. Everyone who reads this article is aware that it is the most important raw material energy resource in the United States at present. It will remain important for some time to come. Most readers are also aware that petroleum is the basic starting material for many industrial chemicals; but some may need to be reminded that it is, in fact, the principal raw material from which most of the synthetic chemical products made in the United States ultimately derive.

Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.

This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.

The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.

This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.

To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.

This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.

The purpose of this paper is to present an analysis of the development of a new graduate certificate course in Petroleum Data Management. The course was developed in response to an identified gap in skills and training in data management that was perceived to be a substantial risk in terms of: industry sustainability, efficiency and potentially wider implications of safety as assets are transferred between operators and for decommissioning. The aim of this paper is to critically reflect on how academia and industry can work together to support emerging professions in information management.

The paper draws on observations and interviews from key stakeholders involved in the course development.

The course development process was ultimately successful but also challenging and lessons have been learned which will be of interest to the wider professional and academic body. These include: securing resources and industry engagement for course development, negotiating cultural differences between academic and industry and managing stakeholder relationships throughout the lifecycle of the course development.

The paper demonstrates the challenges and opportunities of developing a university course in collaboration with industry partners. Oil and gas exploration and production is a data-intensive industry but it was only relatively recently that attempts have been made to set industry standards and roles of “data manager” or “data analyst” have been created to manage these. This paper has wider implications for understanding the professionalisation of the nascent data management disciplines and contributes to the ongoing dialogue around the changing library and information science profession.

This is the twelfth article on business and law (BSL) databases in a continuing series of articles summarizing and commenting on new database products. Two companion articles, one covering science, technology, and medicine (STM) appeared in Online & CD‐ROM Review vol. 22, no.4 and the other covering social science, humanities, news, and general (SSH) appeared in Online & CD‐ROM Review vol. 22, no. 5. The articles are based on the newly appearing database products in the Gale Directory of Databases. The Gale Directory of Databases (GDD) was created in January 1993 by merging Computer‐Readable Databases: A Directory and Data Sourcebook (CRD) together with the Directory of Online Databases (DOD) and the Directory of Portable Databases (DPD).

This paper presents results of a study on data managers' perspectives on the evolution of Designated Communities and the FAIR Principles using an example of a geological repository.

The study employed 10 semi-structured interviews with data managers at a state geological survey and qualitative analysis of the interview transcripts.

The Designated Community for a collection in this data repository has evolved from petroleum industry users to include academic researchers and the public. This change was accompanied by significant user interaction changes from in-person, reference interview-style conversations to anonymous digital, automated interactions. The main factors driving these changes were developments in technology which allowed the data managers to shift data discovery and access into the online environment. The online data portal has seen increasing non-expert use, driving the data team to develop additional services for these new communities. Repository data team participants varied in their familiarity with the FAIR Principles and their perceptions of the FAIRness of the data in the repository.

The study was limited to one organization in the United States. However, the results are applicable to other data environments working through the tensions between high-level global frameworks such as FAIR, and continuing to serve the day-to-day needs of their designated communities. Continued work on how to assess success in this complex space is needed.

This paper lies at the nexus of two digital preservation frameworks and contributes to a limited extant literature providing guidance on implementing the concept of a Designated Community in practice.

Two main activities of the EC FP7 Risk of Energy Availability: Common Corridors for Europe Supply Security (REACCESS) project applied a systematic approach to collect the main characteristics of energy supply corridors starting from mining activities in exporting regions up to the import infrastructures and capacities of EU27+countries. The aim of the present paper is to summarise identified information on import potentials and the possible corridors for the EU27+energy supply of the future. This information is used as new starting point for the energy system modelling in the REACCESS project.

Detailed information on existing, planned or potential developments derived from literature reviews and expert surveys, as well as from our own calculations, was compiled in a consistent database. By using suitable geographic information system (GIS) tools, all the identified energy supply routes were represented graphically and analysed with reference to their spatial characteristics.

The information collected was used to generate a comprehensive database of resources, production capacities and import routes. Together with further detailed information on technological and economic parameters (not shown in this paper), this database provides new complete and consistent input for the modelling of import corridors and associated risks regarding the energy systems in Europe.

The originality of the paper is the synthesis of a huge volume of information provided in the literature and own additional calculations in a consistent way. The resulting database provides the framework for the integration of security of supply aspects into energy scenario modelling, which is an important modelling challenge and one of the main tasks of REACCESS. The study considers oil, gas, coal and nuclear fuel as well as renewable imports of solar electricity and biomass, and also hydrogen as a possible new energy carrier.

The purpose of this paper is to trace the effects of both foreign direct investment (FDI) and external debt on economic growth and employment in Egypt over the 1985–2014 period.

The empirical analysis includes three stages: an aggregate time series analysis, a panel model that includes six economic sectors and a set of single-sector models. The “autoregressive distributed lag” approach is utilized either in the time series or in the panel models.

The empirical results of this research reveal that foreign investment exerts a weak positive effect on economic growth and employment in Egypt. External debt exerts an insignificant effect on economic growth and employment in the aggregate model. The sectoral analysis reveals that the effect varies greatly between sectors; the effect of FDI on output is positive in the financial, tourism and other service sectors, while it is insignificant in the agricultural, construction and manufacturing sectors.

It is important not to depend on external debt as an easy way to obtain capital. Greater efforts should be exerted to increase the absorptive capacity of the Egyptian economy so as to benefit from the positive spillover effect of foreign investment as much as possible.

With respect to Egypt, very limited studies have focussed on the role of external debt on growth and that of FDI and external debt on the employment level. There is no general agreement concerning the effect of FDI on economic growth. Therefore, this research explores the effect of FDI and external debt on the Egyptian economy utilizing both aggregate and sectoral data.

Conventional statistical forecasting methods typically need a large sample size or the use of overly confident hypotheses, like the Gaussian distribution of the input data. Unfortunately, these input data are frequently scarce or do no not follow a normal distribution law. A grey forecasting model can be developed and used to predict energy consumption for at least four data points or ambiguous data based on grey theory. The standard grey model, however, may occasionally result in significant forecasting errors.

In order to reduce these errors, this paper proposes a hybrid multivariate grey model (namely Grey Modeling (1,N)) optimized by Genetic Algorithms with sequential selection forecasting mechanism, abbreviated as Sequential-GMGA(1,N). A real case of Cameroon's oil products consumption is considered to demonstrate the effectiveness of the proposed forecasting model.

The results show the superiority of Sequential-GMGA(1,4) when compared with the results of competing grey models reported in the literature, with a mean absolute percentage error as low as 0.02%.

Without changing the model's basic structure, the suggested framework completely extracts the evolution law of multivariate time series. Regardless of data patterns, Sequential-GMGA(1,4) actively enhances all model parameters over the course of each predicted timeframe. Consequently, Sequential-GMGA(1,4) improves forecast accuracy by resolving the discrepancy between the model's least sum of squares of prediction errors and the parameterization approach based on grey derivative.

The purpose of this paper is to explore a range of perspectives on the relationship between research data and records and between recordkeeping and research data management.

This paper discusses literature in the field of research data management as part of preliminary work for the author’s doctoral research on the topic. The literature included in the review reflects contemporary and historical perspectives on the management and preservation of research data.

Preliminary findings indicate that records professionals have been involved in the management and preservation of research data since the early twentieth century. In the literature, research data is described as comparable to records, and records professionals are widely acknowledged to have skills and expertise which are applicable to research data management. Records professionals are one of a number of professions addressing research data management. However, they are not currently considered to be leaders in research data management practice.

Research data management is an emerging challenge as stakeholders in the research lifecycle increasingly mandate the publication of open, transparent research. Recent developments such as the publication of the OCLC report “The Archival Advantage: Integrating Archival Expertise into Management of Born-digital Library Materials”, and the creation of the Research Data Alliance Interest Group Archives and Records Professionals for Research Data indicates that research data is, or can be, within the remit of records professionals. This paper represents a snapshot of contemporary and historical attitudes towards research data and recordkeeping and thus contributes to this emerging area of discussion.