RO-Crate Time Series Exporter for the Building Consumption Data of KIT Campus North

The facility management (FM) of the Karlsruhe Institute of Technology (KIT) operates an infrastructure for measuring energy consumption to invoice other organizational units within KIT for the energy consumed. For this purpose, the measuring infrastructure automatically records and stores the energy consumption of all buildings on Campus North at a resolution of 15 minutes. The recorded and stored consumption comprises different energy types, namely electricity, gas, heat, water (warm, cooling, drinking, and several kinds of wastewater), and compressed air. Since this measurement infrastructure is already in operation since 2006, the consumption data stored as time series meanwhile cover a long period of time. The covered period of time makes these energy consumption time series highly interesting for the energy research community, especially for energy researchers at KIT. However, accessing the data is challenging. While the original infrastructure was designed for single-user access and limited data throughput, it now faces multiple users and high data throughput. Moreover, since the used technology does not scale with the ever-growing data volumes, FM finally updated the data infrastructure. However, despite improvements with regard to performance, the new data infrastructure brings new challenges, including data only partially moved to the new infrastructure. For this reason, retrieving time series whose time range spans data from both old and new infrastructure requires a researcher to write queries for both database systems, which in turn requires knowing the complicated logic of the used schemas of both databases. Even if a researcher successfully queried such a time series, she needs further queries to allow measurement units, measurement quantities, and scaling factors to be included in the interpretation of the data. Given both this challenging data access and the increasing interest in the data, we started to simplify the process of data querying by developing a web service with a simple REST (Fielding, 2000) interface. This interface allows researchers to query data in a unified way, without requiring any knowledge about the underlying databases and thereby lowering the hurdles of accessing the data. The interface requires only a time range, a list of buildings, and energy types as inputs and returns a ZIP file including the time series as CSV files and an RO-Crate (Soiland-Reyes et al., 2022) metadata file in JSON. The metadata file fully describes the requested energy consumption time series by using the RO-Crate data package standard with an extended, in-house developed profile for time series description. This RO-Crate metadata file enables an interpretation of the obtained data without any prior knowledge and reduces the burden on researchers to publish the data according to good scientific practice. Since a lot of research using energy consumption data benefits from including exogenous influences such as weather (Dannecker, 2015 & Haben et al., 2023), the developed web service also allows obtaining weather time series for the specified time range, which again is described in the RO-Crate metadata file. The present poster shows the steps taken to develop the web service: It starts with the analysis of the original database schemas, before it describes the agreement on the required information resulting in a shared database schema. The poster continues with the transformation of the original data into the shared schema that builds the data foundation of the service. Next, the poster presents the creation of the time series profile, the standards and vocabularies, the used technologies to develop the service, and the challenges during the development of the software. The poster concludes with an outlook on planned improvements and extensions of the developed web service

Report on research data management interviews conducted for HMC Hub Energy in 2022

The Energy Hub of the Helmholtz Metadata Collaboration (HMC) conducted interviews with various stakeholders from the Helmholtz Research Field Energy on the topic of research data management (RDM) in 2022. The intentions were to build and serve a metadata community in the energy research field and to extend the Helmholtz-wide survey conducted by HMC in 2021 Arndt et al., 2022). Besides the deeper insight into the current state of RDM and metadata handling at the Helmholtz sites relevant to the Energy Hub the interviews focused on the related needs and difficulties of researchers and their satisfaction with the current state. Furthermore, we tried to discover already existing workflows and software solutions, to establish contacts and to make HMC better known

A basic Helmholtz Kernel Information Profile for machine-actionable FAIR Digital Objects

To reach the declared goal of the Helmholtz Metadata Collaboration Platform, making the depth and breadth of research data produced by Helmholtz Centres findable, accessible, interoperable, and reusable (FAIR) for the whole science community, the concept of FAIR Digital Objects (FAIR DOs) has been chosen as top-level commonality across all research fields and their existing and future infrastructures. Over the last years, not only by the Helmholtz Metadata Collaboration Platform, but on an international level, the roads towards realizing FAIR DOs has been paved more and more by concretizing concepts and implementing base services required for realizing FAIR DOs, e.g., different instances of Data Type Registries for accessing, creating, and managing Data Types required by FAIR DOs and technical components to support the creation and management of FAIR DOs: The Typed PID Maker providing machine actionable interfaces for creating, validating, and managing PIDs with machine-actionable metadata stored in their PID record, or the FAIR DO testbed, currently evolving into the FAIR DO Lab, serving as reference implementation for setting up a FAIR DO ecosystem. However, introducing FAIR DOs is not only about providing technical services, but also requires the definition and agreement on interfaces, policies, and processes. A first step in this direction was made in the context of HMC by agreeing on a Helmholtz Kernel Information Profile. In the concept of FAIR DOs, PID Kernel Information is key to machine actionability of digital content. Strongly relying on Data Types and stored in the PID record directly at the PID resolution service, PID Kernel Information is allowed to be used by machines for fast decision making. In this session, we will shortly present the Helmholtz Kernel Information Profile and a first demonstrator allowing the semi-automatic creation of FAIR DOs for arbitrary DOIs accessible via the well-known Zenodo repository

A common PID Kernel Information Profile for the German Helmholtz Association of Research Centres

In the concept of FAIR Digital Objects, PID Kernel Information is key to machine actionability of digital content. Strongly relying on Data Types and stored in a PID record directly at the PID resolution service, allows PID Kernel Information to be used by machines for fast decision making. To make a first step into the direction of standardizing PID Kernel Information, the RDA Working Group on PID Kernel Information has defined a first proposal of a core Kernel Information Profile (KIP) together with a list of seven guiding principles helping to decide on which information could be part of a KIP and which information should be stored elsewhere. The Helmholtz Metadata Collaboration (HMC) Platform is a joint endeavor across all research areas of the Helmholtz Association, the largest association of large-scale research centers in Germany. The goal of HMC is to make the depth and breadth of research data produced by Helmholtz Centres findable, accessible, interoperable, and reusable (FAIR) for the whole science community. To reach this goal, the concept of FAIR Digital Objects has been chosen as top-level commonality across all research fields and their existing and future infrastructures. In order to fulfill this role, a common Helmholtz KIP has been agreed on serving as basis for all FAIR Digital Objects created in the context of HMC. This poster describes the Helmholtz KIP and elaborates on decisions leading to differences compared to the core KIP recommended by the RDA. While remaining mostly compatible to the RDA core KIP, the Helmholtz KIP adds some additional properties that satisfy the multidisciplinary environment it is made for. Thus, it serves as a good starting point for rolling out the FAIR Digital Object concept over all Research Data Management Infrastructures of the Helmholtz Association and beyond. In addition, the poster provides a first impression of a demonstrator, which is currently under development and should serve as showcase. In the first step, we will allow to transform arbitrary datasets from Zenodo into FAIR Digital Objects using our Helmholtz KIP. In a next step, we plan to also include datasets from infrastructures hosted at Helmholtz Centres to create a huge and unprecedented network of FAIR Digital Objects, which provides scientists with an incredible pool of linked and searchable research data. This work has been supported by the research program ‘Engineering Digital Futures’ of the Helmholtz Association of German Research Centers and the Helmholtz Metadata Collaboration Platform

Intrinsic androgen-dependent gene expression patterns revealed by comparison of genital fibroblasts from normal males and individuals with complete and partial androgen insensitivity syndrome

<p>Abstract</p> <p>Background</p> <p>To better understand the molecular programs of normal and abnormal genital development, clear-cut definition of androgen-dependent gene expression patterns, without the influence of genotype (46, XX vs. 46, XY), is warranted. Previously, we have identified global gene expression profiles in genital-derived fibroblasts that differ between 46, XY males and 46, XY females with complete androgen insensitivity syndrome (CAIS) due to inactivating mutations of the androgen receptor (AR). While these differences could be due to cell autonomous changes in gene expression induced by androgen programming, recent work suggests they could also be influenced by the location from which the fibroblasts were harvested (topology). To minimize the influence of topology, we compared gene expression patterns of fibroblasts derived from identical urogenital anlagen: the scrotum in normally virilized 46, XY males and the labia majora from completely feminized 46, XY individuals with CAIS.</p> <p>Results</p> <p>612 transcripts representing 440 unique genes differed significantly in expression levels between scrotum and CAIS labia majora, suggesting the effects of androgen programming. While some genes coincided with those we had identified previously (TBX3, IGFBP5, EGFR, CSPG2), a significant number did not, implying that topology had influenced gene expression in our previous experiments. Supervised clustering of gene expression data derived from a large set of fibroblast cultures from individuals with partial AIS revealed that the new, topology controlled data set better classified the specimens.</p> <p>Conclusion</p> <p>Inactivating mutations of the AR, in themselves, appear to induce lasting changes in gene expression in cultured fibroblasts, independent of topology and genotype. Genes identified are likely to be relevant candidates to decipher androgen-dependent normal and abnormal genital development.</p

Androgen receptor abnormalities

The human androgen receptor is a member of the superfamily of steroid hormone receptors. Proper functioning of this protein is a prerequisite for normal male sexual differentiation and development. The cloning of the human androgen receptor cDNA and the elucidation of the genomic organization of the corresponding gene has enabled us to study androgen receptors in subjects with the clinical manifestation of androgen insensitivity and in a human prostate carcinoma cell line (LNCaP). Using PCR amplification, subcloning and sequencing of exons 2–8, we identified a G → T mutation in the androgen receptor gene of a subject with the complete form of androgen insensitivity, which inactivates the splice donor site at the exon 4/intron 4 boundary. This mutation causes the inactivation of a cryptic splice donor site in exon 4, which results in the deletion of 41 amino acids from the steroid binding domain. In two other independently arising cases we identified two different nucleotide alterations in codon 686 (GAC; aspartic acid) located in exon 4. One mutation (G → C) results in an aspartic acid → histidine substitution (with negligible androgen binding), whereas the other mutation (G → A) leads to an aspartic acid → asparagine substitution (normal androgen binding, but a rapidly dissociating androgen receptor complex). Sequence analysis of the androgen receptor in human LNCaP-cells (lymph node carcinoma of the prostate) revealed a point mutation (A → G) in codon 868 in exon 8 resulting in the substitution of threonine by alanine. This mutation is the cause of the altered steroid binding specificity of the LNCaP-cell androgen receptor. The functional consequences of the observed mutations with respect to protein expression, specific ligand binding and transcriptional activation, were established after transient expression of the mutant receptors in COS and HeLa cells. These findings illustrate that functional error

Helmholtz Metadata Collaboration (HMC) - FAIr Metadata for Energy = FAIRe Metadaten für die Energieforschung

Ein Teil des Helmholtz-Inkubators Information und Data Science ist die Helmholtz Metadata Collaboration (HMC). HMC soll die Beschreibung von Forschungsdaten durch Metadaten zu deren besseren Auffindbarkeit vorantreiben sowie organisatorisch und technisch umsetzen. Metadaten sind essentielle Infor¬mationen über Forschungsdaten, die für deren Auffinden und Verstehen sowie für deren Vernetzung und Nachnut¬zung im Sinne der FAIR-Prinzipien erforderlich sind. Zur Umsetzung wird die wissenschaftliche Expertise zum Thema Metadaten aus einzelnen Fachdomainen in sogenannten Metadata Hubs der einzelnen Forschungsbereiche zusammengefasst, auf übergeordneter Ebene harmonisiert und, mit Hilfe zentral entwickelter Methoden und Werkzeugen, Metadatenplattformen bereitgestellt. Für den Forschungsbereich Energie ist der HMC Hub Energie verantwortlich. Aufgabe ist hierbei die vorhandenen Standards zur Energiedaten- und Metadatenbeschreibung, etablierte Beschreibungs- und Erfassungsprozesse sowie zugehörige Softwarewerkzeuge zu erfassen, Lücken zu identifizieren und Szenarien zur Ergänzung und Weiterentwicklung in der Domäne Energie zu entwerfen. Einheitliche Ziele von HMC sind die einfache und FAIRe Erschließung und Nutzung vorhandener und zukünftiger Datensammlungen der Forschungsbereiche sowie die Befähigung der Forschenden FAIRe Daten (semi-) automatisch zu erstellen. Das Poster beschreibt die Struktur von HMC allgemein und dem Hub Energie im speziellen, die entwickelten Methoden und Werkzeuge und gibt anhand von Anwendungsbeispielen Impulse für die Umsetzung der Methoden und Werkzeuge hin zu FAIRen Metadaten. Weiterhin werden Verknüpfungen zu Trainings- und Schulungsunterlagen von HMC hergestellt. Das Poster soll dazu einladen mit dem HMC Hub Energie Kontakt aufzunehmen um von den Arbeiten von HMC profitieren zu können