Open Web Resources Research Articles

An integrated approach to identifying sex-specific genes, transcription factors, and pathways relevant to Alzheimer's disease

BackgroundAge represents a significant risk factor for the development of Alzheimer's disease (AD); however, recent research has documented an influencing role of sex in several features of AD. Understanding the impact of sex on specific molecular mechanisms associated with AD remains a critical challenge to creating tailored therapeutic interventions. MethodsThe exploration of the sex-based differential impact on disease (SDID) in AD used a systematic review to first select transcriptomic studies of AD with data regarding sex in the period covering 2002 to 2021 with a focus on the primary brain regions affected by AD - the cortex (CT) and the hippocampus (HP). A differential expression analysis for each study and two tissue-specific meta-analyses were then performed. Focusing on the CT due to the presence of significant SDID-related alterations, a comprehensive functional characterization was conducted: protein-protein network interaction and over-representation analyses to explore biological processes and pathways and a VIPER analysis to estimate transcription factor activity. ResultsWe selected 8 CT and 5 HP studies from the Gene Expression Omnibus (GEO) repository for tissue-specific meta-analyses. We detected 389 significantly altered genes in the SDID comparison in the CT. Generally, female AD patients displayed more affected genes than males; we grouped said genes into six subsets according to their expression profile in female and male AD patients. Only subset I (repressed genes in female AD patients) displayed significant results during functional profiling. Female AD patients demonstrated more significant impairments in biological processes related to the regulation and organization of synapsis and pathways linked to neurotransmitters (glutamate and GABA) and protein folding, Aβ aggregation, and accumulation compared to male AD patients. These findings could partly explain why we observe more pronounced cognitive decline in female AD patients. Finally, we detected 23 transcription factors with different activation patterns according to sex, with some associated with AD for the first time. All results generated during this study are readily available through an open web resource Metafun-AD (https://bioinfo.cipf.es/metafun-ad/). ConclusionOur meta-analyses indicate the existence of differences in AD-related mechanisms in female and male patients. These sex-based differences will represent the basis for new hypotheses and could significantly impact precision medicine and improve diagnosis and clinical outcomes in AD patients.

Bigdata of National Medicine Registers

Currently, various databases of approved drugs are widely used in the development and application of computer-aided drug design for training sets and validating predicted models. Most of the freely available databases contain information on a limited number of drugs. This leads to reduction in the space of pharmacotherapeutic chemistry studied and used by researchers. Information on drugs developed and used locally, in one or two countries, can be obtained from relevant national medicine registries. We have identified and analyzed registries from more than 70 countries around the world that are accessible through open web resources on the Internet. In addition to lists of approved therapeutics, many web resources offer the opportunity to review official documents published by medical authorities after the approval process. These documents contain a wide range of information about drugs, including data on structural formulations, pharmacodynamics and pharmacokinetics, toxicity, etc. The compounds represented in the registries, both in terms of quantity and structural diversity, exceed the known widely used databases of approved drugs. Combined data from national drug registries represent an example of “Big Data” in the biomedical field, taking into account all the difficulties involved in their processing. Its use in computer-aided drug design will not only expand the pharmacotherapeutic chemical space studied, but also improve the quality of the original data.

Evaluating machine learning technologies for food computing from a data set perspective

Food plays an important role in our lives that goes beyond mere sustenance. Food affects behavior, mood, and social life. It has recently become an important focus of multimedia and social media applications. The rapid increase of available image data and the fast evolution of artificial intelligence, paired with a raised awareness of people’s nutritional habits, have recently led to an emerging field attracting significant attention, called food computing, aimed at performing automatic food analysis. Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. These technologies are broadly used to address emerging problems and challenges in food-related topics, such as food recognition, classification, detection, estimation of calories and food quality, dietary assessment, food recommendation, etc. However, the specific characteristics of food image data, like visual heterogeneity, make the food classification task particularly challenging. To give an overview of the state of the art in the field, we surveyed the most recent machine learning and deep learning technologies used for food classification with a particular focus on data aspects. We collected and reviewed more than 100 papers related to the usage of machine learning and deep learning for food computing tasks. We analyze their performance on publicly available state-of-art food data sets and their potential for usage in multimedia food-related applications for various needs (communication, leisure, tourism, blogging, reverse engineering, etc.). In this paper, we perform an extensive review and categorization of available data sets: to this end, we developed and released an open web resource in which the most recent existing food data sets are collected and mapped to the corresponding geographical regions. Although artificial intelligence methods can be considered mature enough to be used in basic food classification tasks, our analysis of the state-of-the-art reveals that challenges related to the application of this technology need to be addressed. These challenges include, among others: poor representation of regional gastronomy, incorporation of adaptive learning schemes, and reverse engineering for automatic food creation and replication.

Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies

BackgroundAs the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable.MethodsIn this study, we evaluate the expression profiles of six classical housekeeping genes (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues (AT) of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the expression stability of all genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database to identify sex-unbiased housekeeping genes (suHKG) suitable for use as internal controls. We perform a novel computational strategy based on meta-analysis techniques to identify any sexual dimorphisms in mRNA expression stability in AT and to properly validate potential candidates.ResultsJust above half of the considered studies informed properly about the sex of the human samples, however, not enough female mouse samples were found to be included in this analysis. We found differences in the HKG expression stability in humans between female and male samples, with females presenting greater instability. We propose a suHKG signature including experimentally validated classical HKG like PPIA and RPL19 and novel potential markers for human AT and discarding others like the extensively used 18S gene due to a sex-based variability display in adipose tissue. Orthologs have also been assayed and proposed for mouse WAT suHKG signature. All results generated during this study are readily available by accessing an open web resource (https://bioinfo.cipf.es/metafun-HKG) for consultation and reuse in further studies.ConclusionsThis sex-based research proves that certain classical housekeeping genes fail to function adequately as controls when analyzing human adipose tissue considering sex as a variable. We confirm RPL19 and PPIA suitability as sex-unbiased human and mouse housekeeping genes derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB.

Soil Erosion in the Central Russian Upland: A Review

This literature review analyzed more than 100 publications on soil erosion in the Central Russian Upland, one of the most erosion-prone regions of Russia. The selection of scientific papers was carried out from open web resources, domestic and international citation databases. The following parameters have been analyzed: time; geographical position; scale and methods of research; soil and geomorphological features; anti-erosion measures; type of erosion and rates of soil washout/accumulation; bibliographic information about the publication. There is a shortage of studies at the small-scale and medium-scale levels. The confinement of large-scale studies to the main watershed of the Central Russian Upland was revealed. There are discrepancies in the estimates of soil erosion by different authors, especially at different scale levels. An analysis of changes in soil erosion over time indicates a decrease in the rate of soil erosion in general on the Central Russian Upland, mainly due to climate change and a reduction in the area of arable lands. A lack of studies of rainfall, mechanical and wind erosion of soils in this area has been revealed.

Information system for extraction of information from open web resources

The purpose of the work is to develop a project of an information and reference system for finding answers to questions based on the highest degree of comparison using text content from open English- language web resources. Examples of such questions can be: “What is the best book ever?”, “What is the most popular IDE for Python”. The result of the functioning of the information and reference system is a ranked list of answers based on the frequency of appearance of each of the answer options. Also, a numerical characteristic of the probability of the preference of a particular answer over others is added to each element of the list. Based on this metric, the obtained results are ranked. This information and reference system works with questions to which there is no unequivocal answer, what differs it from classic information systems for finding answers to questions of the QA-system type. The latter have a hypothesis that there is only one true answer to the question, often such systems work with well-known facts. Examples of questions they answer can be, for example, the date of birth of a famous person, or the population of a certain country. Instead, the proposed information and reference system answers subjective questions, for example, “What is the best book in the fantasy genre?” or “What is the best programming language?”. The system is based on the popularity of one or another answer. Proper names based on the analysis of N-grams are also keywords for forming the answer to the question.

ГІБРИДНА ФОТОЕЛЕКТРИЧНА СИСТЕМА З АКУМУЛЯТОРНОЮ БАТАРЕЮ ДЛЯ ЛОКАЛЬНОГО ОБ’ЄКТУ З ЗАВДАННЯМ ПОТУЖНОСТІ, ЩО СПОЖИВАЄТЬСЯ З МЕРЕЖІ

The issues of increasing the efficiency of a hybrid photovoltaic system with a storage battery used to meet the own needs of a local object are considered. This is achieved in the case of a setting according to the forecast of power consumption from the grid, which ensures the formation of the necessary graph of the degree of charge of the battery. A technique for determining the parameters is substantiated when achieving the maximum reduction in the cost of electricity consumed from the grid for the accepted load schedule for the average monthly generation of a photovoltaic battery in summer. Implementation scenarios are proposed in accordance with the accepted billing of payment for electricity. The possibility of leveling the graph of power consumed from the network and reducing consumption during peak hours is shown. The invariance of control is confirmed under the conditions of load changes over time within a certain energy value at intervals in the daytime and in the evening. The possibilities of implementing the proposed control scenarios are confirmed by modeling energy processes in the daily cycle. At the same time, archival data on the generation of a photovoltaic battery from open web resources were used. The solutions obtained are the basis for the design of software control complexes for photovoltaic systems with batteries with improved energy efficiency.

Unveiling sex-based differences in Parkinson's disease: a comprehensive meta-analysis of transcriptomic studies

BackgroundIn recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson's disease incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in Parkinson’s disease as epidemiological and clinical features differ between males and females.MethodsTo study sex bias in Parkinson’s disease, we conducted a systematic review to select sex-labeled transcriptomic data from three relevant brain tissues: the frontal cortex, the striatum, and the substantia nigra. We performed differential expression analysis on each study chosen. Then we summarized the individual differential expression results with three tissue-specific meta-analyses and a global all-tissues meta-analysis. Finally, results from the meta-analysis were functionally characterized using different functional profiling approaches.ResultsThe tissue-specific meta-analyses linked Parkinson’s disease to the enhanced expression of MED31 in the female frontal cortex and the dysregulation of 237 genes in the substantia nigra. The global meta-analysis detected 15 genes with sex-differential patterns in Parkinson’s disease, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein–protein interaction networks, and transcription factors that differed by sex. While male patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. All results generated during this study are readily available by accessing an open web resource (http://bioinfo.cipf.es/metafun-pd/) for consultation and reuse in further studies.ConclusionsOur in silico approach has highlighted sex-based differential mechanisms in typical Parkinson Disease hallmarks (inflammation, mitochondrial dysfunction, and oxidative stress). Additionally, we have identified specific genes and transcription factors for male and female Parkinson Disease patients that represent potential candidates as biomarkers to diagnosis.

CAS Common Chemistry in 2021: Expanding Access to Trusted Chemical Information for the Scientific Community.

CAS Common Chemistry (https://commonchemistry.cas.org/) is an open web resource that provides access to reliable chemical substance information for the scientific community. Having served millions of visitors since its creation in 2009, the resource was extensively updated in 2021 with significant enhancements. The underlying dataset was expanded from 8000 to 500,000 chemical substances and includes additional associated information, such as basic properties and computer-readable chemical structure information. New use cases are supported with enhanced search capabilities and an integrated application programming interface. Reusable licensing of the content is provided through a Creative Commons Attribution-Non-Commercial (CC-BY-NC 4.0) license allowing other public resources to integrate the data into their systems. This paper provides an overview of the enhancements to data and functionality, discusses the benefits of the contribution to the chemistry community, and summarizes recent progress in leveraging this resource to strengthen other information sources.

Computational molecular characterization of p53 and Human TLRs interactions.

Toll-like receptors (TLRs) are one of the major sensors to regulate innate immunity. It is present in inactive form within immune cells. However, after recognizing the conserved region of the foreign body, it gets activated by the foreign body, such as bacteria, viruses, fungus, etc. Recently, it is reported that apart from participating in innate immunity, these TLRs also play an important role in apoptosis and cancer. Moreover, very few reported that it is cross-talk with p53 protein within the cell. P53 protein is a transcription factor for many cellular proteins involved in cellular transduction. It directly as well as indirectly regulates a wide variety of cellular processes such as apoptosis, senescence, cell cycle arrest, differentiation, and DNA repair and replication and cancer dynamics. Various studies reported genetic level interaction between p53 and TLRs. However, molecular interaction studies are still few reported. In the present work, we computationally characterized molecular interaction between p53 and toll-like receptors. We used open web resources for docking and analyzing the data. Our molecular docking and molecular dynamics simulation results suggest that there is a significant interaction between p53 and toll-like receptors. The study could important for the possible therapeutic intervention.

МОДЕЛЮВАННЯ ГІБРИДНОЇ ФОТОЕЛЕКТРИЧНОЇ СИСТЕМИ З АКУМУЛЯТОРНОЮ БАТАРЕЮ ДЛЯ ЛОКАЛЬНОГО ОБ’ЄКТУ У РАЗІ ЕНЕРГОМЕНЕДЖМЕНТУ З ВИКОРИСТАННЯМ ПРОГНОЗУ

The issues of increasing the efficiency of a hybrid photovoltaic system with a storage battery for a local object by improving energy management by forecasting with simulation of energy processes in the system are considered. It is proposed to combine the functions of ensuring the auxiliary needs of the object with the planned generation of energy to the grid for the day ahead during peak hours. In the absence of generation to the grid in the case of sufficient energy from the photovoltaic and storage batteries, the system operates in an autonomous mode. To reduce energy consumption from the network, it is proposed to switch to work with the grid with predicting the degree of battery charge and correcting the load power when the voltage decreases within acceptable limits. To study the efficiency of energy management according to the forecast, simulation modeling of energy processes in the daily cycle was used. The developed model with a block for predicting the degree of battery charge allows you to investigate the operation of the system under various weather conditions with an estimate of the cost of paying for electricity from the grid at multizone billing. In this case, the archived data of the forecast of the generation of a photovoltaic battery from open web resources were used. The simulation results confirm the efficiency of the proposed solutions and the possibility of reducing costs even in the absence of generation to the grid. The solutions obtained are the basis for the design of software control complexes for photovoltaic systems with batteries with improved energy efficiency

INTERNATIONAL PROJECTS AS A NEW FORM OF COLLABORATION IN THE SPHERE OF EXPERT ENSURING OF JUSTICE

In the article some statements ofIn the article the participation of the National Science Center «Hon. Prof. M. S. Bokarius Forensic Science Institute» in the bilateral research project was elucidated. It had been emphasized that the participation in the projects of the international cooperation is a new form of interaction of institutions of forensic activity that promote a development of the sphere of expert ensuring of justice. The regulatory and legal enactments of Ukraine and the Republic of Latvian, which regulate the participation’ question of scientists in fundamental and applied international research projects were analyzed. It is noticed that, Riga Stradins University and the National Science Center «Hon. Prof. M. S. Bokarius Forensic Science Institute» are participants of Joint Scientific Research Project. The content of the Ukrainian-Latvian project on the topic «Open Educational Resource: Forensic Science» is revealed that was devoted to the complex research of modern scientific approaches, the formation of theoretical regulations and practical summaries, related to the improvement of implementation of educational and scientific activity’s mechanisms of modern scientific approaches in the field of expert ensuring of justice Within the framework of the scientific project particular topical issues in forensic science are proposed to resolved. As a result of work on the project it is planned to publish scientific works, an open web-resource containing scientific, research and other materials, and also educational video presentations of work of the forensic expert with a possibility of their remote use is created. It was proved that the participation of domestic institutions within international projects assists the integration to European Higher Education Area and European Forensic Science Area.

An interpretable attraction recommendation method based on knowledge graph

The attraction recommendation systems not only filter out overwhelming irrelevant information for visitors but also identify potential customers for service providers. However, the current attraction recommendation methods such as content-based methods, collaborative filtering, or deep learning-based methods are either inaccurate due to data sparsity, or lack of interpretability, which results in the users suspicion on the recommendation results. To address the limitations of the current methods, we introduce a novel framework for preference propagation on knowledge graphs (KGs), which utilizes lots of parameters to capture the abundant semantics of existing KGs more comprehensively, and meanwhile explains the results through reasoning the link paths from users history to candidates on KGs. With a multi-view spatiotemporal analysis on real-world travel data, we investigate the geographical characteristics of human tour activities and build a tourism-oriented KG based on open web resources. Then, we propose a KG-aware attraction recommendation method named Geo-RippleNet and implement it with extensive experiments on large-scale datasets. It is argued that the framework for preference propagation on KGs not only absorb rich semantic information to achieve substantial performance gains in the attraction recommendation scenario but also enhance the interpretability of recommendation results with the support of abundant relational knowledge. Moreover, incorporating the spatiotemporal characteristics of human tour activities into the framework for preference propagation further makes the recommendation performance more aligned with the potential interests of visitors.

B(u)y the book: evaluation of a university initiative to provide students with funds to buy books

Purpose In the era of high student fees and intense market competition, many universities now buy books for their new students, and recently have incorporated student choice into the offer, enabling students to choose how to spend funds. Teesside University has successfully piloted such an approach with one academic School, the School of Social Sciences, Humanities and Law. The pilot has now been extended to all academic Schools, with all students receiving £100 per academic year to spend on reading list books. The scheme covers new full-time undergraduate students at the University, and is operated in collaboration with an external company, John Smiths. The purpose of this paper is to evaluate the Teesside University Advance scheme against baseline data of book borrowing and reservation patterns of reading list titles. The paper explores the impact upon the student experience and student perceptions of the Library. Design/methodology/approach The project used a mixed methods approach. The quantitative strand analysed book borrowing and reservation patterns data from library systems and from book purchasing patterns data provided by the online store supporting the scheme. Students were also surveyed about the scheme. The qualitative strand, via one-to-one interviews conducted by the student researcher, gained an insight into why students select certain titles to purchase; and what their expectations of the university library are for the supply of reading list titles. Findings Analysis revealed an overall decline in book borrowing from the library of the titles selected for purchase by students via the scheme. Student perceptions of the library were positive and demonstrated a strategic use of library resources alongside book purchases and open web resources. At early stages of university undergraduate study, students need guidance on most appropriate resources to use and why, from either reading lists or book bundles. Originality/value Teesside University scheme is unique in the UK in covering all new full-time undergraduates and letting them choose which reading list titles to buy with the university funds provided.

AMEND: Open Source and Data-Driven Oversight of Water Quality in New England

The advent of government transparency through online data publication should provide a transformative benefit to the information gathering practices of civic organizations and environmental advocates. However, environmental agencies and other reporters often disseminate this critical data only in siloed repositories and in technically complex, inconsistent formats, limiting its impact. We have developed a new open source web resource, the Archive of Massachusetts ENvironmental Data or AMEND, which curates information relating to federal, state, and local environmental stewardship in Massachusetts, focused on water quality. We describe the construction of AMEND, its operation, and the datasets we have integrated to date. This tool supports the development and advocacy of policy positions with published analyses that are fully reproducible, versioned, and archived online. As a case study, we present the first publicly reported analysis of the distributional impact of combined sewer overflows on Environmental Justice (EJ) communities. Our analysis of the historical geospatial distribution of these sewer overflows and block-level US Census data on EJ indicators tracking race, income, and linguistic isolation demonstrates that vulnerable communities in Massachusetts are significantly overburdened by this form of pollution. We discuss applications of this analysis to the state-level legislative process in Massachusetts. We believe that this approach to increasing the accessibility of regulatory data, and the code underlying AMEND, can serve as a model for other civic organizations seeking to leverage data to build trust with and advocate to policymakers and the public.

LCE: an open web portal to explore gene expression and clinical associations in lung cancer

We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

Atlas of the normal intracranial electroencephalogram: neurophysiological awake activity in different cortical areas.

mcgill.ca).

YEASTRACT: an upgraded database for the analysis of transcription regulatory networks in Saccharomyces cerevisiae.

The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT—www.yeastract.com) information system has been, for 11 years, a key tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in Saccharomyces cerevisiae. Since its last update in June 2017, YEASTRACT includes approximately 163000 regulatory associations between transcription factors (TF) and target genes in S. cerevisiae, based on more than 1600 bibliographic references; it also includes 247 specific DNA binding consensus recognized by 113 TFs. This release of the YEASTRACT database provides new visualization tools to visualize each regulatory network in an interactive fashion, enabling the user to select and observe subsets of the network such as: (i) considering only DNA binding evidence or both DNA binding and expression evidence; (ii) considering only either positive or negative regulatory associations; or (iii) considering only one set of related environmental conditions. A further tool to observe TF regulons is also offered, enabling a clear-cut understanding of the exact meaning of the available data. We believe that with this new version, YEASTRACT will improve its role as an open web resource instrumental for Yeast Biologists and Systems Biology researchers.

КОРЕГУВАННЯ СТАТИСТИЧНИХ ПОКАЗНИКІВ ПОГОДНИХ УМОВ ДЛЯ ЗИМОВОГО ПЕРІОДУ ЧИЩЕННЯ ВУЛИЧНО-ДОРОЖНЬОЇ МЕРЕЖІ З ВИКОРИСТАННЯМ ДАНИХ ВЕБ-РЕСУРСУ

Urgency of the research. Quality and timely cleaning of the road network of the city requires large financial and material costs. Detailed research and statistical adjustments weather conditions characteristic of Chernihiv city will reduce the cost of purchasing antiglaze materials.Target setting. Detailed study of statistical data on weather conditions of the maintenance of the street-road network with the help of archival information of open Web-resources.Actual scientific researches and issues analysis. Finding ways to reduce the cost of cleaning the city is carried out by many scientists from different countries of the world.Uninvestigated parts of general matters defining. An important factor in the city's readiness to clean the street-road network in the winter is the harvesting of anti-icing reagents, the need for which is determined by snow and ice data. In the absence of statistical information on weather conditions, you can use the data provided in the archives of weather Web services.The research objective. Adjustment of the statistical data on road weather conditions of the winter period in the city of Chernihiv.The statement of basic materials. The issue of refinement of statistical data on the weather conditions of the maintenance of the street-road network with the help of archival information of open Web-resources is considered. The updated information is obtained, which can serve as the basis for calculating costs and purchasing friction materials and reagents for the winter period. The mechanism of refinement of statistical weather data on the example of the city of Chernihiv is shown. The weather statistics for the maintenance of the streets and road network of the city of Chernihiv are calculated.Conclusions. The conducted analysis of weather factors in the winter period based on open data of Web resources indicates the need to adjust the statistical data for the Chernihiv region, which are given in the current normative documents.

How ARL Academic Libraries Present Open Web Resources — A Proposed Solution to Address Discoverability

Open web resources on the Internet have become increasingly important in the scholarly community and are being cited ever more frequently in scholarly articles. Academic librarians continue to assess and collect open web resources that are of value to the academic community in order to support research. With the questions of how ARL academic libraries collect, present, and make searchable open web resources, this paper analyzes all ARL academic libraries' websites and finds that all of them are collecting valuable open web resources and presenting these on research/subject guides. This paper also finds that some ARL academic libraries implement search boxes for the collected list of open web resources, but only descriptions or titles of the resources housed on the libraries' website are being searched. None of the libraries makes the content or full text of open web resources discoverable on the academic library websites. Based on the findings, this paper proposes a solution to address the discoverability issue of collecting open web resources and how to make the content or full text of the open web resources searchable.