This work aimed to transform raw data in high quality and well organized data for research studies addressing genetics and neurodevelopmental disorders. Information and relations between patients, cnvs, genes, GO terms, and diagnoses where passed through a very demanding quality check analysis before being inserted in the relational database in order to eliminate redundancies and enhance uniformity whenever possible. By using this data, researchers can start their work one step further by querying and identifying data suitable for analysis rather than spent time in tasks related to data cleaning and data pre-processing.

3 code files written in sql, java and xquery performing six queries on mysql, mongodb and eXist databases respectively described in the paper entitled "Examining database persistence of ISO/EN 13606 standardized Electronic Health Record extracts: relational vs. noSQL approaches"

TreeBASE is a relational database designed to manage and explore information on phylogenetic relationships. It includes phylogenetic trees and data matrices, together with information about the relevant publication, taxa, morphological and sequence-based characters, and published analyses. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, etc.

iRefWeb is an interface to a relational database containing the latest build of the interaction Reference Index (iRefIndex) which integrates protein interaction data from ten different interaction databases: BioGRID, BIND, CORUM, DIP, HPRD, INTACT, MINT, MPPI, MPACT and OPHID. In addition, iRefWeb associates interactions with the PubMed record from which they are derived.

The Data Management System (DBMS) market is experiencing robust growth, driven by the increasing volume and velocity of data generated across various sectors. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 12% through 2033. This expansion is fueled by several key factors. The digital transformation sweeping industries like Banking & Finance, Healthcare, and Telecom & IT necessitates sophisticated DBMS solutions for efficient data storage, processing, and analysis. The rising adoption of cloud-based DBMS, offering scalability and cost-effectiveness, further accelerates market growth. Furthermore, the increasing demand for real-time analytics and advanced data security features are pushing the adoption of advanced relational and non-relational database systems. While competitive pressures and the complexity of integrating new systems can pose challenges, the overall market trajectory remains positive. Segment-wise, the Banking & Finance and Healthcare & Life Sciences sectors are leading the adoption of DBMS, driven by stringent regulatory compliance needs and the crucial role of data in decision-making. The shift towards big data analytics and the growing use of artificial intelligence (AI) and machine learning (ML) in data-driven insights are also key factors. Geographically, North America currently holds a significant market share, followed by Europe and Asia Pacific. However, emerging economies in Asia Pacific are demonstrating significant growth potential, driven by increasing digitalization and expanding IT infrastructure. The diverse range of DBMS types, including relational and NoSQL databases, caters to specific industry needs and data structures. This diversity is fueling competition among major players like Oracle, IBM, Microsoft, MongoDB, and others, fostering innovation and driving down costs for consumers.

SABIO-RK is a relational database system that contains information about biochemical reactions, their kinetic equations with their parameters, and the experimental conditions under which these parameters were measured. The kinetic record data set provides information regarding the kinetic law, measurement conditions, parameter details and other reference information.

CSRDB is a bioinformatics resource for cereal crops consisting of large-scale datasets of maize and rice and small RNA sequences. The sequences were generated by 454 Life Science sequencing. The small RNA sequences have been mapped to the rice genome and available maize genome sequence and are presented in two genome browser datasets using the Generic Genome Browser. Potential target sequences representing mature mRNA sequences have been predicted using the FASTH software from the Zuker lab. and access to the resulting small RNA target pair (SRTP) dataset has been made available through a mysql based relational database. Within the genome browser the small RNAs have links to the SRTP database that will return a list of potential targets. The SRTP database may also be searched independently using both small RNA and target transcript queries. Data linking and integration is the main focus of this interface and to this aim links are present in the SRTP results pages back to the browser and the SRTP database as well as external sites.

SABIO-RK is a relational database system that contains information about biochemical reactions, their kinetic equations with their parameters, and the experimental conditions under which these parameters were measured. The EC record provides for a given enzyme classification (EC) the associated list of enzyme-catalysed reactions and their corresponding kinetic data.

The Cloud Database and DBaaS Market Report Segments the Industry Into by Component (Solution, and Services), Database Type (Relational (RDBMS), and NoSQL), Deployment (Public, Private, and Hybrid), Enterprise Size (SMEs, and Large Enterprises), End-User (BFSI, IT and Telecom, Retail, Retail and E-Commerce, Healthcare and Life-Sciences, Government and Public Sector, Manufacturing, and More), and Geography.

Timescale Creator–database customization

Features provided by Timescale Creator enhance the information which can be gleaned from the 2011 trees. These features can be provided either from functions already built into Timescale Creator, or via “in-house” programming within the database which has exploited the built-in functions to provide data and information on key issues of interest to the case study. It is this flexibility provided by the combination of Timescale Creator functions and datapacks programmed from the back-end relational database which is showcased below.

Groups

Colours were used in the original 2011 trees [1, Appendices 2, 3 ], and now in the Timescale Creator trees, to display eco- and morpho-groups (respectively). The Timescale Creator trees also add coloured group labels (rather than colouring the range labels as in the original trees), and this allows identification of groups without recourse to the legend. These group labels are positioned on ancestor–descendant branches, but have here been programmed to display only when the group membership changes from ancestor to descendant. As a result, they have the added advantage of highlighting origins and reappearances of the selected groups or properties in a phylogenetic context. A handy use of this feature is when, for example, this is programmed to apply to the generic assignment of morphospecies, making polyphyletic morphogenera, intentioned or otherwise, easy to spot.

Lineage labels

To label range lines on the lineage tree, the Timescale Creator version has been programmed to augment each lineage code with its list of contained morphospecies, e.g., the listing appended to Lineage N1-N3 is “H. holmdelensis > G. archeocompressa > G. planocompressa > G. compressa“. The morphospecies series in these listings is ordered by lowest occurrence, and so the >’s denote stratigraphic succession. (The >’s do not necessarily represent ancestor–descendant relationships; of course only a single line of descent could be expressed in such a format.) This allows the lineage and its proposed morphological succession to be grasped much more easily, including a ready comparison with the morphospecies tree.

Pop-ups

Pop-ups provide the most ample opportunity within Timescale Creator to provide access to supporting information for trees. Because pop-up windows are flexibly resizable and are coded in html, textual content has in effect few quota limitations and, in fact, can be employed to view external sources such as Internet sites and image files without the need to store them in the pop-up itself. They can also be programmed to follow a format tailored for the subject matter, as is done here.

Pop-ups for the morphospecies tree display the contents of the 2011 paper’s summary table [1, Appendix S1, Table S3], including decoding of eco- and morpho-group numbers, range statistics from the Neptune portal, and tailoring the reference list to each morphospecies. They also incorporate the ancestor [from 1, Appendix S5, worksheet aM], specify the type of cladogenetic event (all are, in fact, budding for this budding/bifurcating topology [2]), and level of support for the ancestor–descendant proposal (see § Branches). Lineages containing the morphospecies are listed, along with their morphospecies content and age range (for details, see § Linkages between morphospecies and lineage trees [3]). Also included are the binomen’s original assignation and, where available, links to portals, Chronos [4][5-7] and the World Register of Marine Species (WoRMS) [8].

Range lines

Range-line styles have been used for the Timescale Creator version of the 2011 trees to depict four levels of confidence for ranges. Apart from accepted ranges (lines of usual thickness), two less-confident records of stratigraphic occurrence are depicted: “questioned” (thin line) and “questioned-and-rare” (broken line). For extensions to ranges that are not based on stratigraphic occurrences but are hypothesized (for various reasons), a “conjectured” range is separately recognised (dotted line) to ensure that stratigraphic and hypothesized categories are not conflated. There is an option to attach age labels (in Ma) to range lines, providing the chart with an explicit deep-time positioning throughout.

Branches

Similarly to ranges, branch-line styles have been used to depict three levels of stratophenetic support for ancestry. Almost all ancestor–descendant proposals for the 2011 study are presumed to be “Well Supported” (correspondence between detailed stratigraphic sequences and plausible phyletic series; drawn as a broken line). A small number have been categorised as less or better supported than the usual: “Not Well Supported” (only broad correspondence between stratigraphic order and suggestive phyletic series; drawn as a dotted line); or “Strongly Supported” (detailed morphometric–stratigraphic sequences from ancestor to descendant; continuous line).

Linkages between morphospecies and lineage trees

Many range points of the lineages of the 2011 study are herein directly linked to those of included morphospecies: not quite half of start dates and almost all of end dates. Brief details of this linkage are displayed in the “Stratigraphic Range (continued)” section of the pop-up, where the linkage will usually result in the same precalibrated Ma value between lineage and morphospecies range points, but these values will differ where there has been a correction or amendment of the original Ma value. The reason for choosing the morphospecies range point is usually briefly indicated. Where the original Ma value of the lineage range point is retained and not directly linked to a morphospecies point, the morphospecies and its time scale that are employed nonetheless for calibration are indicated.

Pop-ups are also employed to more easily appreciate the linkages between morphospecies and lineages, following from the morphospecies content of lineages. These are displayed both in terms of the lineages in which a morphospecies occurs and in terms of the morphospecies included in a lineage, along with other information to help track these interrelationships.

1. Aze T, Ezard TH, Purvis A, Coxall HK, Stewart DR, Wade BS, et al. A phylogeny of Cenozoic macroperforate planktonic foraminifera from fossil data. Biological Reviews of the Cambridge Philosophical Society. 2011;86(4):900-27. doi: 10.1111/j.1469-185X.2011.00178.x.
2. see § Data, topologies, and taxa of the 2011 study’s trees: Tree topologies, above
3. a morphospecies contained in more than one lineage is depicted in Figure 20a
4. Support for on-going activity on the foraminiferal section of Chronos [116] no longer appears viable; other portals may need to be linked in later versions e.g., pforams@mikrotax [117, 118]
5. Huber BT. Foraminiferal databases (Mesozoic Paleocene, Eocene Planktonic Foraminifera Taxonomic databases), Chronos Portal Washington (DC, USA): Consortium for Ocean Leadership for the Chronos Internal Coordinating Committee (Iowa State University and the National Science Foundation). Available from: http://portal.chronos.org/gridsphere/gridsphere?cid=foram_working_group (not updated in recent years).
6. Young J, Huber BT, Bown P, Wade BS. pforams@mikrotax (UK Natural Environment Research Council), within mikrotax.org London: University College London. Available from: http://www.mikrotax.org/pforams/index.html.
7. Huber BT, Petrizzo MR, Young JR, Falzoni F, Gilardoni SE, Bown PR, et al. Pforams@microtax: a new online taxonomic database for planktonic foraminifera. Micropaleontology. 2017;62(6):429-38.
8. Hayward BW, Le Coze F, Gross O. World Foraminifera Database, World Register of Marine Species (WoRMS) Vlaams Instituut voor de Zee (Flanders Marine Institute), Oostende (Belgium): WoRMS Editorial Board; 2018 [2018-01-09]. Available from: http://www.marinespecies.org/foraminifera, http://www.marinespecies.org doi:10.14284/170

CephBase is a dynamic html (dhtml) relational database-driven interactive web site that has been online since 1998. The prototype version of CephBase was developed at Dalhousie Univeristy in Halifax, Canada and was sponsored by the Sloan Foundation following the Workshop on Non-Fish Nekton in Boston, December, 1997. As of 12/2000, CephBase has all the taxa, authorities, and the year the taxa was described online for all of the 703 known living species of cephalopods listed by Sweeney and Roper (1998). CephBase provides taxonomic data, distribution, images, videos, predator and prey data, size, references and scientific contact information for all living species of cephalopods (octopus, squid, cuttlefish and nautilus) in an easy to access, user-friendly manner.

Information on a particular species can be quickly located by using the search engine; results are listed in table format. Users simply click on a species cephalopod is displayed. Users can also display an alphabetized list of all cephalopod genera. Clicking on a genus leads to a list of all species it contains. For each species, synonymies, type repositories, type localities, references and common names are listed. References are listed in abbreviated form with access to full references.

Species Database:
Search by scientific, common name or synonym to call up species-specific pages with information such as full taxonomy, type species, names, size, predators, prey, biogeography, distribution maps, country lists, life history, images, videos, references, genetic information links and other internet resources.

Image Database:
Search our ~1650 cephalopod images which cover all life stages, behaviour, ecology, taxonomy as well as many other aspects of these amazing animals. Each image has a caption, key words, location, photographer and other data.

Video Database:
There are ~150 video clips in the video database.

Reference Database:
There are now over 6000 ceph papers in our reference database.

Researcher Directory:
Looking for a grad school supervisor or cephalopod expert? There are over 400 names in the International Directory of Cephalopod Workers.

Predators and Prey:
Search by predator, prey or cephalopod species in our predators and prey databases.

To answer the question, "Where does it live?", CephBase has 3,175 referenced localities for 328 species served by OBIS. All latitude and longitude data used to generate maps are from published sources and are listed in tables and referenced. In many cases, the individual specimens used to populate the database can be tracked to a museum repository.

The purpose of CephBase is to provide taxonomy, life history, distribution, fisheries, and ecology for all living cephalopod species (i.e., octopus, squid, cuttlefish and nautilus). Such a global database will facilitate collaboration both within the cephalopod community and among all marine sciences.

The data can be accessed through the following web portals (see Related URL field below):

-OBIS, Ocean Biogeographic Information System, CoML (Census of Marine Life) web portal.

-EurOBIS, the European Ocean Biogeographique Information System.

-SCAR-MarBIN, the Marine Biodiversity Information Network, Scientific Committee on Antarctic Research, International Council for Science.

DrugCentral (http://drugcentral.org) is an open-access online drug compendium. DrugCentral integrates structure, bioactivity, regulatory, pharmacologic actions and indications for active pharmaceutical ingredients approved by FDA and other regulatory agencies. Monitoring of regulatory agencies for new drugs approvals ensures the resource is up-to-date. DrugCentral integrates content for active ingredients with pharmaceutical formulations, indexing drugs and drug label annotations, complementing similar resources available online. Its complementarity with other online resources is facilitated by cross referencing to external resources. At the molecular level, DrugCentral bridges drug-target interactions with pharmacological action and indications. The integration with FDA drug labels enables text mining applications for drug adverse events and clinical trial information. Chemical structure overlap between DrugCentral and five online drug resources, and the overlap between DrugCentral FDA-approved drugs and their presence in four different chemical collections, are discussed. DrugCentral can be accessed via the web application or downloaded in relational database format.

The VBRC provides bioinformatics resources to support scientific research directed at viruses belonging to the Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, Paramyxoviridae, Poxviridae, and Togaviridae families. The Center consists of a relational database and web application that support the data storage, annotation, analysis, and information exchange goals of this work. Each data release contains the complete genomic sequences for all viral pathogens and related strains that are available for species in the above-named families. In addition to sequence data, the VBRC provides a curation for each virus species, resulting in a searchable, comprehensive mini-review of gene function relating genotype to biological phenotype, with special emphasis on pathogenesis.

Global Vector Database market size is expected to reach $7.13 billion by 2029 at 23.7%, segmented as by relational vector databases, traditional relational databases with vector support, enhanced query capabilities

Social Network Science (SNS) is the field concerned with studying social systems in a relational way from the perspectives of the social and natural sciences. This data set consists of 25,760 biographical records retrieved from the Web of Science, ranging from 1916 to 2012. Each publication belongs to one of five subfields. To facilitate analyses of the social aspect of SNS, the names of 45,580 distinct authors are provided, linked to the papers in 68,227 publication-author relations. Author names have been disambiguated semi-automatically. To enable analyses of the cultural aspect of SNS, 23,026 distinct linguistic concepts are provided. These concepts resemble words or word combinations extracted from titles (for all publication years) and from abstracts and author keywords (only for publications published after 1990/1991). They are linked to the papers in 202,181 publication-concept relations.

The data set comprises hydrographic, biogeochemical and biological data, including measurements of temperature, salinity and attenuance, plus concentrations of parameters such as nutrients, pigments, urea, hydrocarbons, sedimentation flux, sulphur and dissolved carbon. Analyses of bacterial, zooplankton and phytoplankton communities were also undertaken. The oceanographic data were supplemented by measurements of surface meteorological parameters. Data were collected across three repeated sections: one along the Gulf of Oman; a section at 67deg East from 8 to 14.5deg North; and a major section from 8deg North, 67 deg East to the coast of Oman. Other one-off sections were also traversed in the Arabian Sea and Gulf of Oman areas. Measurements were collected during two cruises: one between 27 August and the 4 October 1994 and the other between the 16 November and the 19 December 1994. Sections were covered by underway surface ocean measurements (one minute sampling of multiple parameters providing some 5 million measurements) complemented by a total of 21 CTD/water-bottle stations, 14 of which were repeated. ARABESQUE was organised by the Plymouth Marine Laboratory of NERC's Centre for Coastal and Marine Sciences and involved the University of Wales, Bangor; Queen's University of Belfast; University of East Anglia; University of Edinburgh; University of Newcastle; the Bedford Institute of Oceanography, Canada; the Max Planck Institute for Limnology, Germany and the Sultan Qaboos University, Oman. Data management support for the project was provided by the British Oceanographic Data Centre. All data collected as part of the project were lodged with BODC who had responsibility for assembling, calibrating, quality controlling and fully documenting the data. BODC checked for instrument spikes or malfunction, values beyond the calibration range, unreasonable ratios of chemical constituents and unreasonable deviations from climatological means. Data were assembled into a relational database, complete with supporting documentation and a user manual. The full data set has been published by BODC on CD-ROM complete with user interface.

The dataset contains physical, biological and chemical oceanographic measurements, and meteorological data. Hydrographic measurements include temperature, salinity, current velocities, attenuance, dissolved oxygen and fluorescence, while water samples were analysed for concentrations of nutrients, pigments, suspended particulates, metals and halocarbons. Samples were also collected for phytoplankton and zooplankton analyses, while results from production experiments are also included in the data set. These oceanographic data are supplemented by surface meteorological measurements. The data were collected at 357 sites in the NE Atlantic, 308 of which are from cruises centering on 20 W, 47 to 60 N, 16 from the Cape Verde Islands and 33 in a coccolithophore bloom just south of Iceland. Measurements were taken from 3 cruises in 1989, 6 cruises in 1990 and 2 cruises in 1991. The data were collected via (i) underway sampling (SeaSoar Undulating Oceanographic Recorder (UOR), hull-mounted acoustic Doppler current profiler (ADCP), meteorology and surface ocean parameters) of which there are 793430 records at 30 second intervals from 11 cruises and (ii) discrete sampling (conductivity-temperature-depth (CTD) and expendable bathythermograph (XBT) casts, bottle stations, net hauls, productivity incubations, stand alone pump (SAP) and sediment trap deployments, cores) of which there are 2215 deployments/experiments. The aim of the Biogeochemical Ocean Flux Study (BOFS) Community Research Project was to study the role of oceans in the global cycling of carbon. The data were collected and supplied by UK participants in the Joint Global Ocean Flux Study (JGOFS). The British Oceanographic Data Centre (BODC) had responsibility for calibrating, processing, quality controlling and documenting the data and assembling the final data set. The underway data are stored as time series for each cruise merged with the navigation data. The data are fully quality controlled. Checks were made for instrument malfunction, fouling, constant values, spikes, spurious values, calibration errors and baseline corrections. The discrete data are stored in a relational database (Oracle RDBMS), mainly as vertical profiles and are uniquely identified by a combination of deployment number and depth.

The Global Database Management System market was valued at USD 101.24 billion in 2023 and is expected to reach USD 213.92 billion by 2029 with a CAGR of 13.28% through 2029.

This data set was centralized for the Marine Gap Analysis Project of the Hawaii Natural Heritage Program. It was obtained from various principle investigators for a multitude of projects. It includes surveys from 183 locations on the eight main Hawaiian Islands. The data were placed in a relational database.

World Bird Database (WBDB)

      BirdLife has been investing in the development of information
    management tools for many years. This is a fully relational database,
    known as the World Bird Database (WBDB). The database architecture
    provides some 120 tables covering in excess of 1,400 data fields. Data
    are being added continually, and certain tables already hold in excess
    of 250,000 records.

      Development started in 1994 with the Important Bird Areas
    module. In 1998, with funds provided by RSPB (BirdLife partner in the
    UK), the database was revised and extended so that it now covers
    sites, species and Endemic Bird Areas. RSPB continues to provide
    essential funding for the ongoing development of the WBDB.

      The World Bird Database provides the information management tool
    through which the BirdLife Partnership manages, analyses and reports
    on the breadth of its scientific knowledge - Species, Important Bird
    Areas (IBAs) and Endemic Bird Areas (EBAs) ^? much of these data are
    available through the Data Zone.

      You can search for detailed information on Species, Sites and EBAs,
    see examples of recent analyses and download subsets of the database.

      With information on some 10,000 species of bird, over 8,000 IBAs
    and 218 EBAs managed through the WBDB, together with BirdLife's
    spatial data, multimedia files, other documents and links, the
    BirdLife Data Zone is truly a valuable information resource.

    Data URL: "http://www.birdlife.org/datazone/index.html"
    Information taken from "http://www.birdlife.org/datazone/index.html"