What Drove Saudi Arabia’s 2020 Fall in CO2 Emissions?

In June 2021, the energy data provider Enerdata released its initial estimates for Saudi Arabia’s 2020 carbon dioxide (CO2) emissions. The data indicate that the Kingdom’s CO2 emissions from fuel combustion decreased by 3.3%, from 508.3 million tonnes of CO2 (MtCO2) in 2019 to 491.8 megatonnes of CO2 (MtCO2) in 2020.

The indispensability of human interactivity in the context of the COVID-19 crisis

This article is particularly relevant in the context of the implementation of remote work regime and online studies. The fact that you can be at work or in the classroom in a domestic context is a special privilege. However, we cannot overlook some of the shortcomings of this type of experience. In the case of teaching, we must not interpret knowledge as a sum of data that needs to be delivered to the recipient. Currently, the problem of information interference has almost disappeared. Knowledge is more than a sum of data. The social context and human interaction reveal the meaningful dimension of knowledge, and once the meaning is grasped - and in the case of the learning process the student - will be able to understand the purpose and applicability of knowledge. The vivacity of the layer of meanings is maintained due to the interaction between people. The requirement to maintain effective communication in the distance learning regime is a real challenge, first of all, for the teacher. In these circumstances the teacher risks becoming a data provider.

Privacy Preservation for On-Chain Data in the Permission less Blockchain using Symmetric Key Encryption and Smart Contract

Blockchain technology provides several suitable characteristics such as immutability, decentralization and verifiable ledger. It records the transactions in a decentralized way and can be integrated into several fields like eHealth, e-Government and smart cities etc. However, blockchain has several privacy and security issues, one of them is the on-chain data privacy. To deal with this issue we provide a privacy-preserving solution for permission less blockchain to empower the user to take control of transaction data in the open ledger. This work focuses on designing and developing the peer-to-peer system using symmetric cryptography and ethereum smart contract. In this scheme, we create smart contracts for the interaction of the data provider, data consumer, and access control list. Data providers register authorized users in the access control list. Data consumers can check their validity in the access control list. After successful validation, data consumers can request the security key from data providers to access secret information. Based on successful validation, a smart contract that is created between the data provider and data consumer is executed to send a key to the data consumer for accessing the secret information. The smart contracts of this proposed model are modeled in solidity, and the performance of the contracts is assessed in the Ropsten test network.

Analisis Kualitas Layanan Penyedia Data di Indonesia Menggunakan Metode Servqual

<p>Tujuan utama penelitian ini untuk melakukan evaluasi kualitas layanan penyedia data serta mengukur tingkat kepuasan masyarakat pengguna data di Indonesia dengan menggunakan model SERVQUAL. Kualitas layanan diukur dari perspektif masyarakat pengguna data di wilayah Sumatera Utara, Jawa Timur, Sulawesi Selatan, Kalimantan Selatan, NTB, Maluku dan Papua Barat, sehingga dapat lebih mewakili kebutuhan para pengguna data di wilayah Indonesia. Kuisioner terdiri dari kuisioner persepsi dan harapan dengan menggunakan 5 dimensi SERVQUAL : Reliability, Tangibles, Responsiveness, Empathy dan Assurance. Hasil dari penelitian adalah bahwa kelima dimensi menunjukkan adanya nilai kesenjangan yang negatif, dengan nilai kesenjangan (gap) tertinggi pada dimensi Empathy. Hal tersebut menunjukkan ketidakpuasan pengguna data terhadap layanan penyedia data. Dapat diambil kesimpulan bahwa kualitas layanan penyedia data di Indonesia, belum memenuhi kebutuhan dan keinginan para pengguna data, sehingga perlu dilakukan upaya perbaikan terhadap setiap dimensi yang telah diukur agar dapat meningkatkan kualitas atas layanan.</p><p> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Abstract"><em>The main purpose of this research is to conduct a quality of service of data provider institutions for various business and research purposes as well as measuring the level of satisfaction of the user community in Indonesia using the SERVQUAL model. Measurement of service quality from the point of view of data user communities in the regions of North Sumatra, East Java, South Sulawesi, South Kalimantan, NTB, Maluku and West Papua, to represent user needs of data in Indonesia. The questionnaire consisted of a perception and expectation questionnaire using 5 SERVQUAL dimensions namely Reliability, Tangibles, Responsiveness, Empathy and Assurance. Results showed a negative gap value for all 5 dimensions, where the dimension of empathy has the highest gap. These findings indicate dissatisfaction with data provider services, the conclusion is the quality of data provider services in Indonesia, does not meet the users needs and desires, so it is necessary to make improvements to each dimension that has been measured (eliability, Tangibles, Responsiveness, Empathy and Assurance) in order to improve the quality of data provider services.</em></p><p class="Judul2"><strong><em><br /></em></strong></p>

Analisis Kualitas Layanan Penyedia Data di Indonesia Menggunakan Metode Servqual

<p>Tujuan utama penelitian ini untuk melakukan evaluasi kualitas layanan penyedia data serta mengukur tingkat kepuasan masyarakat pengguna data di Indonesia dengan menggunakan model SERVQUAL. Kualitas layanan diukur dari perspektif masyarakat pengguna data di wilayah Sumatera Utara, Jawa Timur, Sulawesi Selatan, Kalimantan Selatan, NTB, Maluku dan Papua Barat, sehingga dapat lebih mewakili kebutuhan para pengguna data di wilayah Indonesia. Kuisioner terdiri dari kuisioner persepsi dan harapan dengan menggunakan 5 dimensi SERVQUAL : Reliability, Tangibles, Responsiveness, Empathy dan Assurance. Hasil dari penelitian adalah bahwa kelima dimensi menunjukkan adanya nilai kesenjangan yang negatif, dengan nilai kesenjangan (gap) tertinggi pada dimensi Empathy. Hal tersebut menunjukkan ketidakpuasan pengguna data terhadap layanan penyedia data. Dapat diambil kesimpulan bahwa kualitas layanan penyedia data di Indonesia, belum memenuhi kebutuhan dan keinginan para pengguna data, sehingga perlu dilakukan upaya perbaikan terhadap setiap dimensi yang telah diukur agar dapat meningkatkan kualitas atas layanan.</p><p> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Abstract"><em>The main purpose of this research is to conduct a quality of service of data provider institutions for various business and research purposes as well as measuring the level of satisfaction of the user community in Indonesia using the SERVQUAL model. Measurement of service quality from the point of view of data user communities in the regions of North Sumatra, East Java, South Sulawesi, South Kalimantan, NTB, Maluku and West Papua, to represent user needs of data in Indonesia. The questionnaire consisted of a perception and expectation questionnaire using 5 SERVQUAL dimensions namely Reliability, Tangibles, Responsiveness, Empathy and Assurance. Results showed a negative gap value for all 5 dimensions, where the dimension of empathy has the highest gap. These findings indicate dissatisfaction with data provider services, the conclusion is the quality of data provider services in Indonesia, does not meet the users needs and desires, so it is necessary to make improvements to each dimension that has been measured (eliability, Tangibles, Responsiveness, Empathy and Assurance) in order to improve the quality of data provider services.</em></p><p class="Judul2"><strong><em><br /></em></strong></p>

Secure Automated File Exchange (SAFE) – Enabling More Efficient Transfers of Sensitive Data

IntroductionWith the explosion in data being collected and made available for research, linkage units receive an increasing amount of data. At the same time, researchers also expect access to more current data. This increase in the influx of data can create resource constraints for linkage units, which need to mobilise more staff time for data processing, as well as data custodians, who are required to provide data updates more frequently. Objectives and ApproachSA NT DataLink has designed the Secure Automated File Exchange (SAFE), in collaboration with the University of South Australia. SAFE provides a framework to safely transfer encrypted data from custodians into SA NT DataLink’s systems. A given custodian uses one private key to send personally identifying data via Secure File Transfer Protocol (SFTP). This data flows via the university’s IT infrastructure, where it is checked for encryption, directly into a Demilitarised Zone (DMZ) within SA NT DataLink’s Data Linkage Unit’s (DLU) highly protected environment. The same custodian then uses a separate private key to provide the corresponding encrypted anonymised content data, again via SFTP. Given the less sensitive nature of this data type, it is deposited on secure university on-site storage, from where it is manually transferred by Data Integration Unit (DIU) staff to SA NT DataLink’s Custodian Controlled Data repository (CCDR). ResultsSA NT DataLink considers implementing SAFE with one data provider as a trial project. After successful testing, a rollout to other data custodians is possible. In parallel, alternative technical solutions for automated data transfers are being evaluated. Conclusion / ImplicationsAutomated data transfer solutions will reduce effort by data custodians to send data and for linkage units to receive and process data updates. Moreover, by limiting manual intervention, they will limit vulnerability to data privacy breaches and the risk of introducing errors into the data. However, data workflow automation is dependent on data provider requirements and the availability of resources to process received data.

Is there a 'right' spatial scale? Improving pedological multi- scale modelling by optimizing input data grain size: A Case Study using Average Local Variance.

&lt;p&gt;Current soil mapping practitioners are faced with a plethora of choices of digital data for input to their modelling approaches; these data have local to global extents and are highly variable in their grain size. Deciding at what scale to represent individual covariates for a specific project, therefore, can be difficult and confusing. Moreover, a lack of accessible methodology and tools focused on determining an optimal input data scales (grain size) has led to the current status quo, which is to use data at the scale delivered by the data provider. Soil prediction models are typically applied using the grain size of the coarsest variable, scaling other data to match. In this study, average local variance was investigated as a method to determine optimal grain size(s) for input variables to a soil contaminant prediction model. The Meuse dataset was used, and heavy metal soil contamination was mapped using RandomForest. A Data Cube was employed to handle data inputs of varying grain size. Two scenarios were investigated for model prediction accuracy: (1) contaminant predictions made using data with optimized grain size, and (2) contaminant predictions made using input data where grain size was unchanged, &amp;#8220;as received&amp;#8221; from the data provider. Both model predictions were assessed using a cross-validation approach. Early results indicate that optimization of grain size based on average local variance can improve prediction accuracy and point toward the importance of understanding the spatial heterogeneity of an input variable and how it changes with different grain sizes prior to incorporation in a predictive model. This research lays a foundation for the creation of an automated approach practitioners can use to help untangle the relationship between the intrinsic spatial scale for a process of interest and how that process is represented in the scale of input data.&lt;/p&gt;

Analisis Metode Clustering Pada Wilayah Berdasarkan Jenis Pencemaran Lingkungan Hidup

This study uses a grouping model in determining areas based on the type of environmental pollution. This study is a special reference from the government in improving environmental sustainability. The data from this study was taken from the website of the government statistical data provider, BPS (Statistics Indonesia) www.bps.go.id. This research uses the K-Mens method and releases it with RapidMiner software to create 2 clusters, high and low level clusters and see what the contents of the cluster are. From the research results obtained by high cluster centroid data that is ((1527), (810.4), (5865), (6655.3), (323), (315.1)) low cluster namely ((139.25) , (122.5), (508,833), (919,222), (64,417), (94,444)). With this analysis, it is expected to be able to load and information for the government to pay more attention to regions whose income is still below average.

ANALISIS PENGUJIAN KECEPATAN AKSES DATA PROVIDER GSM PADA PENGGUNA SMARTPHONE ANDROID DI KOTA BATAM

Inovasi telekomunikasi saat ini berkembang dengan pesat. Hal ini terjadi karena adanya tuntutan zaman yang mengharuskan informasi ditransfer secara cepat. Smartphone merupakan ponsel yang dibekali dengan berbagai macam feature serta spesifikasi. Kemunculan smartphone bisa dibilang seperti sebuah komputer kecil dengan berbagai macam feature yang dapat membantu setiap orang dalam bekerja. Untuk mengetahui kualitas jaringan GSM harus dilakukan analisis parameter jaringan tersebut. Di lakukan pengukuran berdasarkan parameter kualitas jaringan pada infrastruktur jaringan seperti kecepatan akses dan kapasitas transmisi, dari titik pengirim ke titik penerima yang menjadi tujuan, parameter yang digunakan bandwidth, kuat signal, delay, packet loss, dan throughput. Dari hasil pengujian kecepatan akses data ketiga operator seluler masuk dalam kategori baik menurut standar TIPHON. Baik Telkomsel,Indosat, dan XL sangat bisa diandalkan. Berdasarkan hasil pengukuran Telkomsel lebih unggul dengan kecepatan akses download rata-rata 44,78 Mbps, kemudian disusul oleh Indosat 15,86 Mbps dan XL 9,92 Mbps. Tetapi pada kecepatan akses upload XL lebih unggul dengan kecepatan upload 43,5 Mbps, kemudian Indosat 23,55 Mbps, dan Telkomsel 7,2 Mbps.

Toward Reliable Biodiversity Dataset References

No systematic approach has yet been adopted to reliably reference and provide access to digital biodiversity datasets. Based on accumulated evidence, we argue that location-based identifiers such as URLs are not sufficient to ensure long-term data access. We introduce a method that uses dedicated data observatories to evaluate long-term URL reliability.From March 2019 through May 2020, we took periodic inventories of the data provided to major biodiversity aggregators, including GBIF, iDigBio, DataONE, and BHL by accessing the URL-based dataset references from which the aggregators retrieve data. Over the period of observation, we found that, for the URL-based dataset references available in each of the aggregators' data provider registries, 5% to 70% of URLs were intermittently or consistently unresponsive, 0% to 66% produced unstable content, and 20% to 75% became either unresponsive or unstable.We propose the use of cryptographic hashing to generate content-based identifiers that can reliably reference datasets. We show that content-based identifiers facilitate decentralized archival and reliable distribution of biodiversity datasets to enable long-term accessibility of the referenced datasets.